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Add manifests, eval harness (Claude Opus 5 / Bedrock), generation results

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README.md ADDED
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+ ---
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+ license: other
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+ task_categories:
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+ - text-to-video
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+ tags:
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+ - text-to-video
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+ - video-generation
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+ - benchmark
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+ - evaluation
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+ - world-model
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+ size_categories:
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+ - n<1K
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+ ---
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+
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+ # omini_time_space_eval
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+
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+ Text-to-video benchmark suite probing whether a video world model represents
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+ **time**, **space**, and **camera control** — 659 generated clips across four
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+ benchmarks, with the prompts that produced them and the eval harness that
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+ scores them.
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+
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+ | Bench | Items | What it tests |
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+ |---|---:|---|
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+ | `bench_t2v_time_comprehensive` | 200 | Time/weather transitions (20 variants incl. non-monotonic day→night→day) over outdoor scenes |
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+ | `bench_t2v_space` | 162 | Grounded knowledge of specific real-world places, each anchored to a real Wikimedia reference photo (103 worldwide + 59 USA) |
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+ | `bench_t2v_space_comprehensive` | 137 | Same space axis, hand-curated from 97 countries, no reference photo |
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+ | `bench_t2v_camera_time` | 160 | Instructed camera motion (8 types) crossed with time/weather transition (20 variants) — full 8×20 grid, no confounds |
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+
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+ ## Layout
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+
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+ ```
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+ bench_t2v_camera_time/
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+ manifest.json prompts + per-item metadata
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+ results.jsonl generation status/timing per item
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+ videos/*.mp4 the generated clips
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+ score_claude.py the eval judge
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+ summarize.py aggregation
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+ bench_t2v_space/
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+ manifest_worldwide.json, manifest_usa.json
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+ {worldwide,usa}/results.jsonl
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+ {worldwide,usa}/videos/*.mp4
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+ score_claude.py, summarize.py
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+ ...
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+ ```
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+
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+ Note the eval scripts' default `--manifest` / `--videos-dir` values point at the
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+ layout of the original working tree (`outputs/videos/`), not this repo's
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+ flattened layout — pass both flags explicitly when running against these files.
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+
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+ ## Evaluation
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+
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+ `score_claude.py` is the only judge: it samples 8 frames evenly across each clip,
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+ downscales them to 768px on the long edge, and sends them to **Claude Opus 5 on
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+ Amazon Bedrock** with a per-bench rubric (each axis scored 0–10).
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+
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+ | Bench | Axes | Pass criteria |
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+ |---|---|---|
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+ | `bench_t2v_camera_time` | `time_alignment`, `camera_motion`, `quality`, `smoothness` | ≥8, ≥6, ≥7 |
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+ | `bench_t2v_space`, `bench_t2v_space_comprehensive` | `alignment`, `quality`, `smoothness` | ≥8, ≥7 |
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+ | `bench_t2v_time_comprehensive` | `time_alignment`, `quality`, `smoothness` | ≥8, ≥7 |
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+
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+ ```bash
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+ pip install 'anthropic[bedrock]'
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+ export AWS_REGION=us-east-1 # region where Claude Opus 5 is enabled
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+
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+ python score_claude.py --manifest manifest.json --videos-dir videos --out-dir .
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+ python summarize.py --out-dir .
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+ ```
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+
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+ `score_claude.py` is resumable (skips ids already in `claude_scores.jsonl`) and
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+ concurrent (`--concurrency`, default 4). `summarize.py` writes `scores.jsonl`
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+ and `summary.json`.
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+
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+ **Score files are not yet included in this release** — the harness is published
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+ here, the results will be added in a later revision.
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+
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+ ## Provenance and licensing
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+
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+ Please read before reuse:
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+
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+ - **Videos** are generated by an internal `Cosmos3-Nano` checkpoint served
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+ through a modified vLLM; they are model outputs, not captured footage.
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+ - **Prompts** in the time/camera benches derive scene descriptions from
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+ **PAI-Bench-G** captions (`t2v_prompts.json`, outdoor subset). The
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+ `image_name` field carries the source identifier. PAI-Bench-G's own license
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+ governs reuse of that derived text.
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+ - **`ref_image` paths** in the space manifests point at Wikimedia Commons photos
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+ that are **not redistributed here** — only the relative filename and the
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+ `source_url` are included. Each such photo carries its own CC license; fetch
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+ and attribute individually if you need them.
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+ - Clips depict real landmarks. They are synthetic generations, not photographs
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+ of those places.
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+
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+ The `license: other` tag reflects that the components above carry different
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+ terms; there is no single blanket license for this repository.
bench_t2v_camera_time/manifest.json ADDED
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bench_t2v_camera_time/results.jsonl ADDED
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bench_t2v_camera_time/score_claude.py ADDED
@@ -0,0 +1,267 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # SPDX-License-Identifier: Apache-2.0
2
+ """Sole eval signal for bench_t2v_camera_time: Claude Opus 5 on Amazon Bedrock,
3
+ used as a VLM-as-judge over frames sampled from each generated video.
4
+
5
+ Replaces the previous two-model setup (local Qwen3.5-27B + TIGER-Lab/VideoScore2
6
+ combined by combine.py) -- there is now exactly one judge, so there is nothing
7
+ to combine; summarize.py just aggregates this scorer's output.
8
+
9
+ The rubric is unchanged from the Qwen3.5 version: four axes, each 0-10 --
10
+ `time_alignment` (did the described time/weather transition happen), `camera_motion`
11
+ (did the described camera move happen), `quality`, `smoothness`.
12
+
13
+ Claude takes images, not video, so each video is reduced to K evenly-spaced
14
+ frames sent as JPEG images in one user turn. Frames are downscaled to
15
+ --max-side (default 768px long edge) to keep per-request image tokens
16
+ reasonable: Claude bills roughly (w*h)/750 tokens per image, so 8 frames at
17
+ 768x432 is ~3.5k image tokens per video.
18
+
19
+ Requirements:
20
+ pip install 'anthropic[bedrock]' # boto3 is what signs the SigV4 request
21
+ AWS credentials resolvable the usual way (env vars, ~/.aws, instance role)
22
+ AWS_REGION (or --aws-region) set to a region where the model is enabled
23
+
24
+ Usage (CPU node is fine -- no local model is loaded):
25
+ python score_claude.py # scores outputs/videos/*.mp4
26
+ python score_claude.py --limit 5 # quick partial check
27
+ python score_claude.py --concurrency 8 # more in-flight requests
28
+ Output: outputs/claude_scores.jsonl (resumable -- skips ids already present).
29
+ """
30
+ from __future__ import annotations
31
+
32
+ import argparse
33
+ import base64
34
+ import json
35
+ import re
36
+ import threading
37
+ from concurrent.futures import ThreadPoolExecutor
38
+ from pathlib import Path
39
+
40
+ import cv2
41
+ import numpy as np
42
+
43
+ HERE = Path(__file__).resolve().parent
44
+
45
+ DEFAULT_MODEL = "anthropic.claude-opus-5"
46
+ DEFAULT_REGION = "us-east-1"
47
+
48
+ K_FRAMES = 8
49
+ MAX_SIDE = 768
50
+ JPEG_QUALITY = 90
51
+ MAX_TOKENS = 4000
52
+
53
+ AXES = ("time_alignment", "camera_motion", "quality", "smoothness")
54
+
55
+ JUDGE_PROMPT_TEMPLATE = """You are a STRICT, SKEPTICAL judge of an AI-generated video against the text prompt that produced it. Most generated videos have real flaws -- assume there are problems until the frames clearly prove otherwise. Do not give credit for "close enough" or "same general vibe."
56
+
57
+ Prompt: "{prompt}"
58
+
59
+ The prompt describes a scene, an instructed CAMERA MOVEMENT, and an instructed TIME/WEATHER transition. The {k} images above are frames sampled evenly across the video's duration, in order.
60
+
61
+ Rate the video on four axes, each an integer from 0 to 10. Use the full range -- most videos should land in the 3-6 band; reserve 9-10 for videos with essentially no flaws.
62
+
63
+ time_alignment (does the described time/weather transition actually happen, in the right direction?):
64
+ 10 = the transition clearly and correctly happens exactly as described (right direction, right end state)
65
+ 8-9 = the transition happens correctly, at most one minor detail off (e.g. slightly under/overshooting the described end state)
66
+ 6-7 = a transition happens and is recognizable as the right general kind (e.g. it does get darker/wetter/snowier) but is incomplete, weak, or has some wrong details
67
+ 4-5 = little to no visible transition, or the wrong kind of change (e.g. asked for rain, got only clouds)
68
+ 2-3 = the scene changes in some way but not toward what was described, or the requested state is contradicted
69
+ 0-1 = no transition at all, or the opposite of what was described
70
+
71
+ camera_motion (does the described camera movement -- dolly/pan/tilt/orbit/tracking -- actually happen, in the right direction?):
72
+ 10 = unmistakable camera movement exactly matching the described type and direction throughout
73
+ 8-9 = clearly the right camera movement, at most a minor inconsistency (e.g. motion slows/stops briefly)
74
+ 6-7 = some camera movement in roughly the right direction, but weaker, less consistent, or partially wrong axis than described
75
+ 4-5 = movement is ambiguous, very slight, or could plausibly be attributed to the subject moving rather than the camera
76
+ 2-3 = camera movement in the wrong direction, or movement doesn't match the described type at all (e.g. asked for a pan, got a static shot with subject motion)
77
+ 0-1 = the camera is completely static, or moves opposite to what was described
78
+
79
+ quality (sharpness, absence of warping/artifacts/melting geometry):
80
+ 10 = photoreal, no visible artifacts anywhere
81
+ 8-9 = very good, at most one small artifact on close inspection
82
+ 6-7 = noticeable but minor artifacts (soft warping, texture smearing) that don't dominate the frame
83
+ 4-5 = clear artifacts in multiple frames (melting geometry, garbled architectural detail, unstable structures)
84
+ 0-3 = pervasive artifacts, badly broken in most frames
85
+
86
+ smoothness (temporal coherence across the frames -- no flicker, no discontinuities, consistent object/architecture identity):
87
+ 10 = perfectly smooth and consistent throughout
88
+ 8-9 = very smooth, at most one minor discontinuity
89
+ 6-7 = mostly smooth but with a couple of noticeable jumps or identity drift
90
+ 4-5 = frequent flicker or objects/architecture changing shape or identity between frames
91
+ 0-3 = incoherent, frames barely relate to each other
92
+
93
+ Be honest and critical -- if you are uncertain whether a detail is correct, score it as if it is wrong, not right.
94
+
95
+ Respond with ONLY a JSON object, no other text, in exactly this form:
96
+ {{"time_alignment": <int 0-10>, "camera_motion": <int 0-10>, "quality": <int 0-10>, "smoothness": <int 0-10>, "reason": "<one short sentence, naming the specific flaw if any>"}}
97
+ """
98
+
99
+
100
+ def item_meta(it: dict) -> dict:
101
+ """Manifest fields carried through onto every score record."""
102
+ return {"domain": it["domain"], "camera_motion_name": it["camera_motion"],
103
+ "time_variant": it["time_variant"]}
104
+
105
+
106
+ # --- generic below this line -------------------------------------------------
107
+
108
+ def make_client(mode: str, region: str, max_retries: int):
109
+ """Bedrock client. `mantle` is the Messages-API Bedrock endpoint and the
110
+ recommended path; `legacy` is the older bedrock-runtime InvokeModel path,
111
+ kept for accounts that only have that enabled (its model ids look like
112
+ `us.anthropic.claude-opus-5-v1:0` -- pass one with --model)."""
113
+ try:
114
+ from anthropic import AnthropicBedrock, AnthropicBedrockMantle
115
+ except ImportError as exc: # pragma: no cover
116
+ raise SystemExit(f"anthropic SDK not available: {exc}") from exc
117
+ cls = AnthropicBedrockMantle if mode == "mantle" else AnthropicBedrock
118
+ return cls(aws_region=region, max_retries=max_retries)
119
+
120
+
121
+ def sample_frames(video_path: Path, k: int) -> list[np.ndarray]:
122
+ """K evenly-spaced BGR frames across the whole video."""
123
+ cap = cv2.VideoCapture(str(video_path))
124
+ n = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
125
+ if n <= 0:
126
+ cap.release()
127
+ raise RuntimeError(f"no frames read from {video_path}")
128
+ frames = []
129
+ for i in np.linspace(0, n - 1, num=min(k, n), dtype=int):
130
+ cap.set(cv2.CAP_PROP_POS_FRAMES, int(i))
131
+ ok, frame = cap.read()
132
+ if ok:
133
+ frames.append(frame)
134
+ cap.release()
135
+ if not frames:
136
+ raise RuntimeError(f"no frames decoded from {video_path}")
137
+ return frames
138
+
139
+
140
+ def encode_jpeg(frame_bgr: np.ndarray, max_side: int) -> str:
141
+ h, w = frame_bgr.shape[:2]
142
+ scale = max_side / max(h, w)
143
+ if scale < 1:
144
+ frame_bgr = cv2.resize(frame_bgr, (int(w * scale), int(h * scale)),
145
+ interpolation=cv2.INTER_AREA)
146
+ ok, buf = cv2.imencode(".jpg", frame_bgr, [int(cv2.IMWRITE_JPEG_QUALITY), JPEG_QUALITY])
147
+ if not ok:
148
+ raise RuntimeError("cv2.imencode failed")
149
+ return base64.standard_b64encode(buf.tobytes()).decode("ascii")
150
+
151
+
152
+ def parse_judge_json(text: str) -> dict:
153
+ """Pull the JSON object out of the judge's reply and clamp the axes."""
154
+ m = re.search(r"\{.*\}", text, re.S)
155
+ if not m:
156
+ raise ValueError(f"no JSON object found in judge output: {text[:200]!r}")
157
+ obj = json.loads(m.group(0))
158
+ for axis in AXES:
159
+ obj[axis] = max(0.0, min(10.0, float(obj[axis])))
160
+ return obj
161
+
162
+
163
+ def judge_video(client, model: str, effort: str, prompt: str,
164
+ video_path: Path, k_frames: int, max_side: int) -> dict:
165
+ frames = sample_frames(video_path, k_frames)
166
+ content = [
167
+ {"type": "image", "source": {"type": "base64", "media_type": "image/jpeg",
168
+ "data": encode_jpeg(f, max_side)}}
169
+ for f in frames
170
+ ]
171
+ content.append({"type": "text",
172
+ "text": JUDGE_PROMPT_TEMPLATE.format(prompt=prompt, k=len(frames))})
173
+
174
+ response = client.messages.create(
175
+ model=model,
176
+ max_tokens=MAX_TOKENS,
177
+ thinking={"type": "adaptive"},
178
+ output_config={"effort": effort},
179
+ messages=[{"role": "user", "content": content}],
180
+ )
181
+ if response.stop_reason == "refusal":
182
+ category = getattr(response.stop_details, "category", None)
183
+ raise RuntimeError(f"model refused (category={category})")
184
+ text = "".join(b.text for b in response.content if b.type == "text")
185
+ if not text.strip():
186
+ raise RuntimeError(f"empty response (stop_reason={response.stop_reason})")
187
+ return parse_judge_json(text)
188
+
189
+
190
+ def parse_args() -> argparse.Namespace:
191
+ p = argparse.ArgumentParser(description="Score bench_t2v_camera_time with Claude Opus 5 on Bedrock.")
192
+ p.add_argument("--manifest", default=str(HERE / "manifest.json"))
193
+ p.add_argument("--videos-dir", default=str(HERE / "outputs" / "videos"))
194
+ p.add_argument("--out-dir", default=str(HERE / "outputs"))
195
+ p.add_argument("--model", default=DEFAULT_MODEL)
196
+ p.add_argument("--aws-region", default=None,
197
+ help=f"defaults to $AWS_REGION, else {DEFAULT_REGION}")
198
+ p.add_argument("--bedrock-mode", choices=("mantle", "legacy"), default="mantle")
199
+ p.add_argument("--effort", choices=("low", "medium", "high", "xhigh", "max"), default="medium")
200
+ p.add_argument("--limit", type=int, default=None)
201
+ p.add_argument("--k-frames", type=int, default=K_FRAMES)
202
+ p.add_argument("--max-side", type=int, default=MAX_SIDE)
203
+ p.add_argument("--concurrency", type=int, default=4)
204
+ p.add_argument("--max-retries", type=int, default=5)
205
+ return p.parse_args()
206
+
207
+
208
+ def main() -> None:
209
+ import os
210
+
211
+ args = parse_args()
212
+ region = args.aws_region or os.environ.get("AWS_REGION") or DEFAULT_REGION
213
+
214
+ manifest = json.load(open(args.manifest))
215
+ items = manifest["items"]
216
+ if args.limit is not None:
217
+ items = items[: args.limit]
218
+
219
+ videos_dir = Path(args.videos_dir)
220
+ out_dir = Path(args.out_dir)
221
+ out_dir.mkdir(parents=True, exist_ok=True)
222
+ scores_path = out_dir / "claude_scores.jsonl"
223
+ already = set()
224
+ if scores_path.exists():
225
+ for line in scores_path.read_text().splitlines():
226
+ if line.strip():
227
+ already.add(json.loads(line)["id"])
228
+
229
+ todo = [it for it in items if it["id"] not in already]
230
+ print(f"{len(items)} items, {len(already)} already scored, {len(todo)} to score")
231
+ print(f"judge: {args.model} via bedrock ({args.bedrock_mode}, region={region}, effort={args.effort})")
232
+
233
+ client = make_client(args.bedrock_mode, region, args.max_retries)
234
+ write_lock = threading.Lock()
235
+ counter = {"n": 0}
236
+
237
+ def work(it: dict) -> None:
238
+ video_path = videos_dir / f"{it['id']}.mp4"
239
+ meta = {"id": it["id"], **item_meta(it)}
240
+ if not video_path.exists():
241
+ with write_lock:
242
+ counter["n"] += 1
243
+ print(f"[{counter['n']}/{len(todo)}] SKIP {it['id']}: video not found")
244
+ return
245
+ try:
246
+ judge = judge_video(client, args.model, args.effort, it["prompt"],
247
+ video_path, args.k_frames, args.max_side)
248
+ record = {**meta, **{axis: judge[axis] for axis in AXES},
249
+ "reason": judge.get("reason", "")}
250
+ line = " ".join(f"{axis.split('_')[0]}={judge[axis]:.0f}" for axis in AXES)
251
+ except Exception as exc:
252
+ record = {**meta, "error": f"{type(exc).__name__}: {exc}"[:300]}
253
+ line = f"ERROR {exc}"
254
+ with write_lock:
255
+ counter["n"] += 1
256
+ print(f"[{counter['n']}/{len(todo)}] {it['id']}: {line}", flush=True)
257
+ with open(scores_path, "a") as f:
258
+ f.write(json.dumps(record) + "\n")
259
+
260
+ with ThreadPoolExecutor(max_workers=max(1, args.concurrency)) as pool:
261
+ list(pool.map(work, todo))
262
+
263
+ print(f"done -> {scores_path}")
264
+
265
+
266
+ if __name__ == "__main__":
267
+ main()
bench_t2v_camera_time/summarize.py ADDED
@@ -0,0 +1,98 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # SPDX-License-Identifier: Apache-2.0
2
+ """Aggregate score_claude.py output into a per-video score file and a summary.
3
+
4
+ Replaces the old combine.py, which merged two judges (Qwen3.5 + VideoScore2).
5
+ Claude Opus 5 is now the only judge, so there is nothing to combine -- the
6
+ score is just the mean of the four rubric axes:
7
+
8
+ score = mean(time_alignment, camera_motion, quality, smoothness) / 10
9
+ pass = time_alignment >= 8 and camera_motion >= 6 and quality >= 7
10
+
11
+ Thresholds are carried over unchanged from combine.py (camera_motion stays at
12
+ 6, not 8, since camera-motion-following is a harder, less-established
13
+ capability than the transition/quality axes); the VideoScore2 `min(v,t,p) >= 4`
14
+ gate is gone with the model that produced it.
15
+
16
+ Usage:
17
+ python summarize.py
18
+ python summarize.py --out-dir outputs
19
+ Output: outputs/scores.jsonl (per-video) + outputs/summary.json.
20
+ """
21
+ from __future__ import annotations
22
+
23
+ import argparse
24
+ import json
25
+ from pathlib import Path
26
+
27
+ import numpy as np
28
+
29
+ HERE = Path(__file__).resolve().parent
30
+
31
+ AXES = ("time_alignment", "camera_motion", "quality", "smoothness")
32
+ GROUP_KEYS = ("camera_motion_name", "time_variant", "domain")
33
+
34
+ PASS_TIME_ALIGNMENT = 8.0
35
+ PASS_CAMERA_MOTION = 6.0
36
+ PASS_QUALITY = 7.0
37
+
38
+
39
+ def passed(r: dict) -> bool:
40
+ return (r["time_alignment"] >= PASS_TIME_ALIGNMENT
41
+ and r["camera_motion"] >= PASS_CAMERA_MOTION
42
+ and r["quality"] >= PASS_QUALITY)
43
+
44
+
45
+ # --- generic below this line -------------------------------------------------
46
+
47
+ def parse_args() -> argparse.Namespace:
48
+ p = argparse.ArgumentParser(description="Summarize Claude judge scores.")
49
+ p.add_argument("--out-dir", default=str(HERE / "outputs"))
50
+ return p.parse_args()
51
+
52
+
53
+ def load_jsonl(path: Path) -> list[dict]:
54
+ if not path.exists():
55
+ raise SystemExit(f"missing {path} -- run score_claude.py first")
56
+ return [json.loads(l) for l in path.read_text().splitlines() if l.strip()]
57
+
58
+
59
+ def main() -> None:
60
+ args = parse_args()
61
+ out_dir = Path(args.out_dir)
62
+ records = load_jsonl(out_dir / "claude_scores.jsonl")
63
+
64
+ merged = []
65
+ for r in sorted(records, key=lambda x: x["id"]):
66
+ if "error" in r:
67
+ merged.append({**{k: v for k, v in r.items() if k != "reason"}, "pass": False})
68
+ continue
69
+ score = sum(r[axis] for axis in AXES) / (10.0 * len(AXES))
70
+ merged.append({**r, "score": round(score, 4), "pass": passed(r)})
71
+
72
+ scores_path = out_dir / "scores.jsonl"
73
+ scores_path.write_text("\n".join(json.dumps(r) for r in merged) + "\n")
74
+
75
+ ok = [r for r in merged if "error" not in r]
76
+ summary = {
77
+ "judge": "claude-opus-5 (bedrock)",
78
+ "num_scored": len(merged),
79
+ "num_ok": len(ok),
80
+ "num_errors": len(merged) - len(ok),
81
+ "pass_rate": round(sum(r["pass"] for r in ok) / len(ok), 3) if ok else None,
82
+ "mean_score": round(float(np.mean([r["score"] for r in ok])), 3) if ok else None,
83
+ }
84
+ for axis in AXES:
85
+ summary[f"mean_{axis}"] = round(float(np.mean([r[axis] for r in ok])), 3) if ok else None
86
+ for key in GROUP_KEYS:
87
+ groups: dict = {}
88
+ for r in ok:
89
+ groups.setdefault(r[key], []).append(r["score"])
90
+ summary[f"mean_score_by_{key}"] = {k: round(float(np.mean(v)), 3)
91
+ for k, v in sorted(groups.items())}
92
+
93
+ (out_dir / "summary.json").write_text(json.dumps(summary, indent=2))
94
+ print(json.dumps(summary, indent=2))
95
+
96
+
97
+ if __name__ == "__main__":
98
+ main()
bench_t2v_space/manifest_usa.json ADDED
@@ -0,0 +1,728 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "dataset": "wikimedia-photo-grounded US state-by-state landmarks (build_places.py + grounding_usa.py)",
3
+ "num_items": 59,
4
+ "modes": [
5
+ "driving",
6
+ "walking"
7
+ ],
8
+ "sampling": {
9
+ "width": 1280,
10
+ "height": 720,
11
+ "num_frames": 189,
12
+ "fps": 24,
13
+ "num_inference_steps": 35,
14
+ "guidance_scale": 6.0,
15
+ "flow_shift": 10.0,
16
+ "seed": 0
17
+ },
18
+ "items": [
19
+ {
20
+ "id": "statue_of_liberty",
21
+ "place": "Statue of Liberty",
22
+ "city": "New York City",
23
+ "country": "United States",
24
+ "continent": "North America",
25
+ "mode": "walking",
26
+ "prompt": "A first-person POV walking through the green copper Statue of Liberty with her raised torch and spiked crown standing on Liberty Island, the Manhattan skyline visible across the harbor.",
27
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
28
+ "ref_image": "wikimedia_famous_places_usa/001_Statue_of_Liberty.jpg",
29
+ "source_url": "https://en.wikipedia.org/wiki/Statue_of_Liberty"
30
+ },
31
+ {
32
+ "id": "golden_gate_bridge",
33
+ "place": "Golden Gate Bridge",
34
+ "city": "San Francisco",
35
+ "country": "United States",
36
+ "continent": "North America",
37
+ "mode": "driving",
38
+ "prompt": "A dashcam POV driving through the burnt-orange towers and suspension cables of the Golden Gate Bridge stretching across the bay fog toward the San Francisco skyline.",
39
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
40
+ "ref_image": "wikimedia_famous_places_usa/002_Golden_Gate_Bridge.jpg",
41
+ "source_url": "https://en.wikipedia.org/wiki/Golden_Gate_Bridge"
42
+ },
43
+ {
44
+ "id": "grand_canyon",
45
+ "place": "Grand Canyon",
46
+ "city": "Arizona",
47
+ "country": "United States",
48
+ "continent": "North America",
49
+ "mode": "driving",
50
+ "prompt": "A dashcam POV driving through a rim-side highway along the Grand Canyon's South Rim, layered red-and-orange rock walls plunging away into a vast eroded gorge.",
51
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
52
+ "ref_image": "wikimedia_famous_places_usa/003_Grand_Canyon.jpeg",
53
+ "source_url": "https://en.wikipedia.org/wiki/Grand_Canyon"
54
+ },
55
+ {
56
+ "id": "mount_rushmore",
57
+ "place": "Mount Rushmore",
58
+ "city": "South Dakota",
59
+ "country": "United States",
60
+ "continent": "North America",
61
+ "mode": "walking",
62
+ "prompt": "A first-person POV walking through the four monumental granite presidential faces of Mount Rushmore carved into the pine-covered Black Hills mountainside.",
63
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
64
+ "ref_image": "wikimedia_famous_places_usa/004_Mount_Rushmore.jpg",
65
+ "source_url": "https://en.wikipedia.org/wiki/Mount_Rushmore"
66
+ },
67
+ {
68
+ "id": "times_square",
69
+ "place": "Times Square",
70
+ "city": "New York City",
71
+ "country": "United States",
72
+ "continent": "North America",
73
+ "mode": "walking",
74
+ "prompt": "A first-person POV walking through the towering, densely packed digital billboards and neon signage of Times Square glowing over crowded sidewalks and yellow taxis.",
75
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
76
+ "ref_image": "wikimedia_famous_places_usa/005_Times_Square.jpg",
77
+ "source_url": "https://en.wikipedia.org/wiki/Times_Square"
78
+ },
79
+ {
80
+ "id": "niagara_falls",
81
+ "place": "Niagara Falls",
82
+ "city": "Niagara Falls, NY",
83
+ "country": "United States",
84
+ "continent": "North America",
85
+ "mode": "walking",
86
+ "prompt": "A first-person POV walking through the thundering curtain of Niagara Falls' American Falls throwing up clouds of mist, tour boats visible in the churning water below.",
87
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
88
+ "ref_image": "wikimedia_famous_places_usa/006_Niagara_Falls.jpg",
89
+ "source_url": "https://en.wikipedia.org/wiki/Niagara_Falls"
90
+ },
91
+ {
92
+ "id": "empire_state_building",
93
+ "place": "Empire State Building",
94
+ "city": "New York City",
95
+ "country": "United States",
96
+ "continent": "North America",
97
+ "mode": "walking",
98
+ "prompt": "A first-person POV walking through the tiered Art Deco setbacks and spire of the Empire State Building rising above Fifth Avenue's yellow-taxi traffic.",
99
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
100
+ "ref_image": "wikimedia_famous_places_usa/007_Empire_State_Building.jpg",
101
+ "source_url": "https://en.wikipedia.org/wiki/Empire_State_Building"
102
+ },
103
+ {
104
+ "id": "brooklyn_bridge",
105
+ "place": "Brooklyn Bridge",
106
+ "city": "New York City",
107
+ "country": "United States",
108
+ "continent": "North America",
109
+ "mode": "walking",
110
+ "prompt": "A first-person POV walking through the stone Gothic arches and web of suspension cables of the Brooklyn Bridge's pedestrian walkway, Manhattan's skyline framed ahead.",
111
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
112
+ "ref_image": "wikimedia_famous_places_usa/008_Brooklyn_Bridge.jpg",
113
+ "source_url": "https://en.wikipedia.org/wiki/Brooklyn_Bridge"
114
+ },
115
+ {
116
+ "id": "hollywood_sign",
117
+ "place": "Hollywood Sign",
118
+ "city": "Los Angeles",
119
+ "country": "United States",
120
+ "continent": "North America",
121
+ "mode": "walking",
122
+ "prompt": "A first-person POV walking through a dusty chaparral trail climbing Mount Lee toward the giant white block letters of the Hollywood Sign, the LA basin sprawling below.",
123
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
124
+ "ref_image": "wikimedia_famous_places_usa/009_Hollywood_Sign.jpg",
125
+ "source_url": "https://en.wikipedia.org/wiki/Hollywood_Sign"
126
+ },
127
+ {
128
+ "id": "alcatraz_island",
129
+ "place": "Alcatraz Island",
130
+ "city": "San Francisco",
131
+ "country": "United States",
132
+ "continent": "North America",
133
+ "mode": "walking",
134
+ "prompt": "A first-person POV walking through the weathered cellblock walls and lighthouse of Alcatraz prison rising from its rocky island, San Francisco's skyline visible across the bay.",
135
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
136
+ "ref_image": "wikimedia_famous_places_usa/010_Alcatraz_Island.jpg",
137
+ "source_url": "https://en.wikipedia.org/wiki/Alcatraz_Island"
138
+ },
139
+ {
140
+ "id": "yellowstone_national_park",
141
+ "place": "Yellowstone National Park",
142
+ "city": "Wyoming",
143
+ "country": "United States",
144
+ "continent": "North America",
145
+ "mode": "driving",
146
+ "prompt": "A dashcam POV driving through a two-lane park road winding past steaming geysers and mineral-terraced hot springs in Yellowstone's high alpine basin.",
147
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
148
+ "ref_image": "wikimedia_famous_places_usa/011_Yellowstone_National_Park.jpg",
149
+ "source_url": "https://en.wikipedia.org/wiki/Yellowstone_National_Park"
150
+ },
151
+ {
152
+ "id": "yosemite_national_park",
153
+ "place": "Yosemite National Park",
154
+ "city": "California",
155
+ "country": "United States",
156
+ "continent": "North America",
157
+ "mode": "driving",
158
+ "prompt": "A dashcam POV driving through a valley road beneath the sheer granite face of El Capitan and Half Dome, waterfalls streaking down the Yosemite valley walls.",
159
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
160
+ "ref_image": "wikimedia_famous_places_usa/012_Yosemite_National_Park.jpg",
161
+ "source_url": "https://en.wikipedia.org/wiki/Yosemite_National_Park"
162
+ },
163
+ {
164
+ "id": "hoover_dam",
165
+ "place": "Hoover Dam",
166
+ "city": "Nevada/Arizona border",
167
+ "country": "United States",
168
+ "continent": "North America",
169
+ "mode": "driving",
170
+ "prompt": "A dashcam POV driving through the massive curved concrete face of Hoover Dam plunging into Black Canyon, the turquoise waters of Lake Mead pooling behind it.",
171
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
172
+ "ref_image": "wikimedia_famous_places_usa/013_Hoover_Dam.jpg",
173
+ "source_url": "https://en.wikipedia.org/wiki/Hoover_Dam"
174
+ },
175
+ {
176
+ "id": "space_needle",
177
+ "place": "Space Needle",
178
+ "city": "Seattle",
179
+ "country": "United States",
180
+ "continent": "North America",
181
+ "mode": "walking",
182
+ "prompt": "A first-person POV walking through the flying-saucer observation deck of the Space Needle atop its slender tapered tower, Seattle's skyline and Mount Rainier visible beyond.",
183
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
184
+ "ref_image": "wikimedia_famous_places_usa/014_Space_Needle.jpg",
185
+ "source_url": "https://en.wikipedia.org/wiki/Space_Needle"
186
+ },
187
+ {
188
+ "id": "antelope_canyon",
189
+ "place": "Antelope Canyon",
190
+ "city": "Page, Arizona",
191
+ "country": "United States",
192
+ "continent": "North America",
193
+ "mode": "walking",
194
+ "prompt": "A first-person POV walking through the smooth swirling sandstone walls of Antelope Canyon glowing orange and purple where shafts of sunlight reach the narrow slot floor.",
195
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
196
+ "ref_image": "wikimedia_famous_places_usa/015_Antelope_Canyon.jpg",
197
+ "source_url": "https://en.wikipedia.org/wiki/Antelope_Canyon"
198
+ },
199
+ {
200
+ "id": "monument_valley",
201
+ "place": "Monument Valley",
202
+ "city": "Arizona/Utah border",
203
+ "country": "United States",
204
+ "continent": "North America",
205
+ "mode": "driving",
206
+ "prompt": "A dashcam POV driving through a lone highway crossing the flat red desert of Monument Valley, isolated sandstone buttes and mesas rising against the horizon.",
207
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
208
+ "ref_image": "wikimedia_famous_places_usa/016_Monument_Valley.jpg",
209
+ "source_url": "https://en.wikipedia.org/wiki/Monument_Valley"
210
+ },
211
+ {
212
+ "id": "u_s__space___rocket_center",
213
+ "place": "U.S. Space & Rocket Center",
214
+ "city": "Huntsville, Alabama",
215
+ "country": "United States",
216
+ "continent": "North America",
217
+ "mode": "walking",
218
+ "prompt": "A first-person POV walking through towering rockets, including a full-scale Saturn V displayed upright and horizontally, on the grounds of the U.S. Space & Rocket Center.",
219
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
220
+ "ref_image": "wikimedia_famous_places_usa/017_Alabama_U_S_Space_Rocket_Center.png",
221
+ "source_url": "https://en.wikipedia.org/wiki/U.S._Space_%26_Rocket_Center"
222
+ },
223
+ {
224
+ "id": "denali",
225
+ "place": "Denali",
226
+ "city": "Alaska",
227
+ "country": "United States",
228
+ "continent": "North America",
229
+ "mode": "driving",
230
+ "prompt": "A dashcam POV driving through a gravel park road across Alaskan tundra with the massive snow-capped bulk of Denali, North America's tallest peak, rising above the clouds.",
231
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
232
+ "ref_image": "wikimedia_famous_places_usa/018_Alaska_Denali.jpg",
233
+ "source_url": "https://en.wikipedia.org/wiki/Denali"
234
+ },
235
+ {
236
+ "id": "hot_springs_national_park",
237
+ "place": "Hot Springs National Park",
238
+ "city": "Hot Springs, Arkansas",
239
+ "country": "United States",
240
+ "continent": "North America",
241
+ "mode": "walking",
242
+ "prompt": "A first-person POV walking through the row of ornate bathhouse facades along Bathhouse Row, steam rising from thermal springs at the edge of the forested Ouachita mountains.",
243
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
244
+ "ref_image": "wikimedia_famous_places_usa/019_Arkansas_Hot_Springs_National_Park.jpg",
245
+ "source_url": "https://en.wikipedia.org/wiki/Hot_Springs_National_Park"
246
+ },
247
+ {
248
+ "id": "rocky_mountain_national_park",
249
+ "place": "Rocky Mountain National Park",
250
+ "city": "Colorado",
251
+ "country": "United States",
252
+ "continent": "North America",
253
+ "mode": "driving",
254
+ "prompt": "A dashcam POV driving through Trail Ridge Road switchbacking above the treeline through Rocky Mountain National Park, jagged snow-streaked peaks and alpine tundra stretching in every direction.",
255
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
256
+ "ref_image": "wikimedia_famous_places_usa/020_Colorado_Rocky_Mountain_National_Park.JPG",
257
+ "source_url": "https://en.wikipedia.org/wiki/Rocky_Mountain_National_Park"
258
+ },
259
+ {
260
+ "id": "mystic_seaport",
261
+ "place": "Mystic Seaport",
262
+ "city": "Mystic, Connecticut",
263
+ "country": "United States",
264
+ "continent": "North America",
265
+ "mode": "walking",
266
+ "prompt": "A first-person POV walking through the tall wooden masts of historic sailing ships docked along the waterfront of Mystic Seaport, weathered clapboard buildings lining the quay.",
267
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
268
+ "ref_image": "wikimedia_famous_places_usa/021_Connecticut_Mystic_Seaport.png",
269
+ "source_url": "https://en.wikipedia.org/wiki/Mystic_Seaport"
270
+ },
271
+ {
272
+ "id": "first_state_national_historical_park",
273
+ "place": "First State National Historical Park",
274
+ "city": "Delaware",
275
+ "country": "United States",
276
+ "continent": "North America",
277
+ "mode": "walking",
278
+ "prompt": "A first-person POV walking through a wooded colonial-era trail past stone mill buildings and a historic courthouse green in Delaware's First State National Historical Park.",
279
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
280
+ "ref_image": "wikimedia_famous_places_usa/022_Delaware_First_State_National_Historical_Park.jpg",
281
+ "source_url": "https://en.wikipedia.org/wiki/First_State_National_Historical_Park"
282
+ },
283
+ {
284
+ "id": "kennedy_space_center",
285
+ "place": "Kennedy Space Center",
286
+ "city": "Cape Canaveral, Florida",
287
+ "country": "United States",
288
+ "continent": "North America",
289
+ "mode": "walking",
290
+ "prompt": "A first-person POV walking through a massive vertical rocket, gantry towers, and the iconic countdown clock at Kennedy Space Center's visitor complex against the flat Florida coastline.",
291
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
292
+ "ref_image": "wikimedia_famous_places_usa/023_Florida_Kennedy_Space_Center.png",
293
+ "source_url": "https://en.wikipedia.org/wiki/Kennedy_Space_Center"
294
+ },
295
+ {
296
+ "id": "stone_mountain",
297
+ "place": "Stone Mountain",
298
+ "city": "Georgia",
299
+ "country": "United States",
300
+ "continent": "North America",
301
+ "mode": "walking",
302
+ "prompt": "A first-person POV walking through a bald granite dome trail up Stone Mountain with its giant carved memorial relief, the Atlanta skyline visible far in the haze.",
303
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
304
+ "ref_image": "wikimedia_famous_places_usa/024_Georgia_Stone_Mountain.jpg",
305
+ "source_url": "https://en.wikipedia.org/wiki/Stone_Mountain"
306
+ },
307
+ {
308
+ "id": "diamond_head",
309
+ "place": "Diamond Head",
310
+ "city": "Honolulu, Hawaii",
311
+ "country": "United States",
312
+ "continent": "North America",
313
+ "mode": "walking",
314
+ "prompt": "A first-person POV walking through a switchback crater-rim trail up Diamond Head's volcanic tuff cone, Waikiki's beaches and turquoise Pacific water spread out below.",
315
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
316
+ "ref_image": "wikimedia_famous_places_usa/060_Hawaii_Diamond_Head.JPG",
317
+ "source_url": "https://en.wikipedia.org/wiki/Diamond_Head%2C_Hawaii"
318
+ },
319
+ {
320
+ "id": "craters_of_the_moon_national_monument_and_preserve",
321
+ "place": "Craters of the Moon National Monument and Preserve",
322
+ "city": "Idaho",
323
+ "country": "United States",
324
+ "continent": "North America",
325
+ "mode": "driving",
326
+ "prompt": "A dashcam POV driving through a loop road across the black volcanic cinder cones and hardened lava fields of Craters of the Moon, sparse vegetation breaking through the basalt.",
327
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
328
+ "ref_image": "wikimedia_famous_places_usa/026_Idaho_Craters_of_the_Moon_National_Monument_and_Preserve.jpg",
329
+ "source_url": "https://en.wikipedia.org/wiki/Craters_of_the_Moon_National_Monument_and_Preserve"
330
+ },
331
+ {
332
+ "id": "cloud_gate",
333
+ "place": "Cloud Gate",
334
+ "city": "Chicago",
335
+ "country": "United States",
336
+ "continent": "North America",
337
+ "mode": "walking",
338
+ "prompt": "A first-person POV walking through the polished mirrored surface of Cloud Gate ('The Bean') reflecting Chicago's skyline and Millennium Park crowds around it.",
339
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
340
+ "ref_image": "wikimedia_famous_places_usa/027_Illinois_Cloud_Gate.jpg",
341
+ "source_url": "https://en.wikipedia.org/wiki/Cloud_Gate"
342
+ },
343
+ {
344
+ "id": "indianapolis_motor_speedway",
345
+ "place": "Indianapolis Motor Speedway",
346
+ "city": "Indianapolis",
347
+ "country": "United States",
348
+ "continent": "North America",
349
+ "mode": "driving",
350
+ "prompt": "A dashcam POV driving through the wide banked front straightaway and iconic yard of bricks at Indianapolis Motor Speedway, grandstands towering along the track.",
351
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
352
+ "ref_image": "wikimedia_famous_places_usa/028_Indiana_Indianapolis_Motor_Speedway.png",
353
+ "source_url": "https://en.wikipedia.org/wiki/Indianapolis_Motor_Speedway"
354
+ },
355
+ {
356
+ "id": "iowa_state_capitol",
357
+ "place": "Iowa State Capitol",
358
+ "city": "Des Moines",
359
+ "country": "United States",
360
+ "continent": "North America",
361
+ "mode": "walking",
362
+ "prompt": "A first-person POV walking through the gold-leafed central dome and ornate stone facade of the Iowa State Capitol rising above its landscaped grounds.",
363
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
364
+ "ref_image": "wikimedia_famous_places_usa/029_Iowa_Iowa_State_Capitol.jpg",
365
+ "source_url": "https://en.wikipedia.org/wiki/Iowa_State_Capitol"
366
+ },
367
+ {
368
+ "id": "monument_rocks",
369
+ "place": "Monument Rocks",
370
+ "city": "Kansas",
371
+ "country": "United States",
372
+ "continent": "North America",
373
+ "mode": "driving",
374
+ "prompt": "A dashcam POV driving through a dirt track across the flat Kansas prairie leading to the chalky white spires and arches of Monument Rocks rising from the grassland.",
375
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
376
+ "ref_image": "wikimedia_famous_places_usa/065_Kansas_Monument_Rocks.jpg",
377
+ "source_url": "https://en.wikipedia.org/wiki/Monument_Rocks_(Kansas)"
378
+ },
379
+ {
380
+ "id": "mammoth_cave_national_park",
381
+ "place": "Mammoth Cave National Park",
382
+ "city": "Kentucky",
383
+ "country": "United States",
384
+ "continent": "North America",
385
+ "mode": "walking",
386
+ "prompt": "A first-person POV walking through a lantern-lit path through the vast limestone passages and towering ceiling of Mammoth Cave, the world's longest known cave system.",
387
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
388
+ "ref_image": "wikimedia_famous_places_usa/031_Kentucky_Mammoth_Cave_National_Park.jpg",
389
+ "source_url": "https://en.wikipedia.org/wiki/Mammoth_Cave_National_Park"
390
+ },
391
+ {
392
+ "id": "french_quarter",
393
+ "place": "French Quarter",
394
+ "city": "New Orleans",
395
+ "country": "United States",
396
+ "continent": "North America",
397
+ "mode": "walking",
398
+ "prompt": "A first-person POV walking through the wrought-iron balconies and colorful Creole townhouses lining a narrow French Quarter street, jazz spilling from open doorways.",
399
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
400
+ "ref_image": "wikimedia_famous_places_usa/032_Louisiana_French_Quarter.jpg",
401
+ "source_url": "https://en.wikipedia.org/wiki/French_Quarter"
402
+ },
403
+ {
404
+ "id": "acadia_national_park",
405
+ "place": "Acadia National Park",
406
+ "city": "Maine",
407
+ "country": "United States",
408
+ "continent": "North America",
409
+ "mode": "driving",
410
+ "prompt": "A dashcam POV driving through Park Loop Road hugging Acadia's granite coastline, pink granite cliffs and wind-bent pines meeting the cold Atlantic surf.",
411
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
412
+ "ref_image": "wikimedia_famous_places_usa/066_Maine_Acadia_National_Park.JPG",
413
+ "source_url": "https://en.wikipedia.org/wiki/Acadia_National_Park"
414
+ },
415
+ {
416
+ "id": "fort_mchenry",
417
+ "place": "Fort McHenry",
418
+ "city": "Baltimore",
419
+ "country": "United States",
420
+ "continent": "North America",
421
+ "mode": "walking",
422
+ "prompt": "A first-person POV walking through the star-shaped brick ramparts and giant American flag of Fort McHenry overlooking Baltimore's harbor.",
423
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
424
+ "ref_image": "wikimedia_famous_places_usa/034_Maryland_Fort_McHenry.jpg",
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+ "source_url": "https://en.wikipedia.org/wiki/Fort_McHenry"
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+ },
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+ {
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+ "id": "fenway_park",
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+ "place": "Fenway Park",
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+ "city": "Boston",
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+ "country": "United States",
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+ "continent": "North America",
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+ "mode": "walking",
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+ "prompt": "A first-person POV walking through the Green Monster's towering left-field wall and worn brick facade of Fenway Park, Boston's skyline visible beyond the stands.",
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+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
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+ "ref_image": "wikimedia_famous_places_usa/035_Massachusetts_Fenway_Park.jpg",
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+ "source_url": "https://en.wikipedia.org/wiki/Fenway_Park"
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+ },
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+ {
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+ "id": "mackinac_bridge",
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+ "place": "Mackinac Bridge",
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+ "city": "Michigan",
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+ "country": "United States",
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+ "continent": "North America",
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+ "mode": "driving",
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+ "prompt": "A dashcam POV driving through the tall suspension towers and long green deck of the Mackinac Bridge spanning the straits between Michigan's two peninsulas.",
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+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
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+ "ref_image": "wikimedia_famous_places_usa/036_Michigan_Mackinac_Bridge.jpg",
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+ "source_url": "https://en.wikipedia.org/wiki/Mackinac_Bridge"
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+ },
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+ {
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+ "id": "mall_of_america",
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+ "place": "Mall of America",
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+ "city": "Bloomington, Minnesota",
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+ "country": "United States",
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+ "continent": "North America",
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+ "mode": "walking",
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+ "prompt": "A first-person POV walking through the glass-roofed atrium and indoor amusement rides of the Mall of America's central Nickelodeon Universe park.",
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+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
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+ "ref_image": "wikimedia_famous_places_usa/037_Minnesota_Mall_of_America.jpg",
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+ "source_url": "https://en.wikipedia.org/wiki/Mall_of_America"
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+ },
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+ {
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+ "id": "vicksburg_national_military_park",
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+ "place": "Vicksburg National Military Park",
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+ "city": "Mississippi",
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+ "country": "United States",
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+ "continent": "North America",
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+ "mode": "driving",
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+ "prompt": "A dashcam POV driving through a park tour road winding past rows of cannons and stone monuments across the wooded battlefield ridges of Vicksburg National Military Park.",
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+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
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+ "ref_image": "wikimedia_famous_places_usa/038_Mississippi_Vicksburg_National_Military_Park.jpg",
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+ "source_url": "https://en.wikipedia.org/wiki/Vicksburg_National_Military_Park"
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+ },
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+ {
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+ "id": "gateway_arch",
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+ "place": "Gateway Arch",
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+ "city": "St. Louis",
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+ "country": "United States",
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+ "continent": "North America",
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+ "mode": "walking",
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+ "prompt": "A first-person POV walking through the gleaming stainless-steel catenary curve of the Gateway Arch rising above the Mississippi riverfront.",
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+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
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+ "ref_image": "wikimedia_famous_places_usa/039_Missouri_Gateway_Arch.jpg",
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+ "source_url": "https://en.wikipedia.org/wiki/Gateway_Arch"
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+ },
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+ {
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+ "id": "glacier_national_park",
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+ "place": "Glacier National Park",
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+ "city": "Montana",
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+ "country": "United States",
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+ "continent": "North America",
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+ "mode": "driving",
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+ "prompt": "A dashcam POV driving through Going-to-the-Sun Road cut into sheer mountainsides in Glacier National Park, snowfields and turquoise alpine lakes framed by jagged peaks.",
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+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
496
+ "ref_image": "wikimedia_famous_places_usa/061_Montana_Glacier_National_Park.jpg",
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+ "source_url": "https://en.wikipedia.org/wiki/Glacier_National_Park_(U.S.)"
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+ },
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+ {
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+ "id": "chimney_rock__nebraska",
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+ "place": "Chimney Rock (Nebraska)",
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+ "city": "Nebraska",
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+ "country": "United States",
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+ "continent": "North America",
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+ "mode": "driving",
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+ "prompt": "A dashcam POV driving through a lone highway across the flat Nebraska plains with the narrow spire of Chimney Rock rising abruptly from the prairie.",
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+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
508
+ "ref_image": "wikimedia_famous_places_usa/062_Nebraska_Chimney_Rock_Nebraska.jpg",
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+ "source_url": "https://en.wikipedia.org/wiki/Chimney_Rock_National_Historic_Site"
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+ },
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+ {
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+ "id": "mount_washington__new_hampshire",
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+ "place": "Mount Washington (New Hampshire)",
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+ "city": "New Hampshire",
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+ "country": "United States",
516
+ "continent": "North America",
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+ "mode": "driving",
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+ "prompt": "A dashcam POV driving through the Mount Washington Auto Road climbing a steep, rocky, often fog-wrapped New England peak toward its exposed summit.",
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+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
520
+ "ref_image": "wikimedia_famous_places_usa/042_New_Hampshire_Mount_Washington_New_Hampshire.jpg",
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+ "source_url": "https://en.wikipedia.org/wiki/Mount_Washington"
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+ },
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+ {
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+ "id": "atlantic_city_boardwalk",
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+ "place": "Atlantic City Boardwalk",
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+ "city": "Atlantic City",
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+ "country": "United States",
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+ "continent": "North America",
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+ "mode": "walking",
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+ "prompt": "A first-person POV walking through the wide wooden Atlantic City Boardwalk lined with casinos and amusement piers, the Atlantic Ocean surf visible just beyond the railing.",
531
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
532
+ "ref_image": "wikimedia_famous_places_usa/043_New_Jersey_Atlantic_City_Boardwalk.jpg",
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+ "source_url": "https://en.wikipedia.org/wiki/Atlantic_City_Boardwalk"
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+ },
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+ {
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+ "id": "carlsbad_caverns_national_park",
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+ "place": "Carlsbad Caverns National Park",
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+ "city": "New Mexico",
539
+ "country": "United States",
540
+ "continent": "North America",
541
+ "mode": "walking",
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+ "prompt": "A first-person POV walking through a winding underground trail descending into Carlsbad Caverns' vast limestone chambers, stalactites and stalagmites lit dramatically from below.",
543
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
544
+ "ref_image": "wikimedia_famous_places_usa/044_New_Mexico_Carlsbad_Caverns_National_Park.jpg",
545
+ "source_url": "https://en.wikipedia.org/wiki/Carlsbad_Caverns_National_Park"
546
+ },
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+ {
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+ "id": "biltmore_estate",
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+ "place": "Biltmore Estate",
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+ "city": "Asheville, North Carolina",
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+ "country": "United States",
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+ "continent": "North America",
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+ "mode": "walking",
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+ "prompt": "A first-person POV walking through the sprawling chateau-style stone facade and manicured formal gardens of the Biltmore Estate.",
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+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
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+ "ref_image": "wikimedia_famous_places_usa/045_North_Carolina_Biltmore_Estate.jpg",
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+ "source_url": "https://en.wikipedia.org/wiki/Biltmore_Estate"
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+ },
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+ {
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+ "id": "theodore_roosevelt_national_park",
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+ "place": "Theodore Roosevelt National Park",
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+ "city": "North Dakota",
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+ "country": "United States",
564
+ "continent": "North America",
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+ "mode": "driving",
566
+ "prompt": "A dashcam POV driving through a scenic loop road through the eroded, striped badlands buttes of Theodore Roosevelt National Park, bison grazing near the roadside.",
567
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
568
+ "ref_image": "wikimedia_famous_places_usa/067_North_Dakota_Theodore_Roosevelt_National_Park.jpg",
569
+ "source_url": "https://en.wikipedia.org/wiki/Theodore_Roosevelt_National_Park"
570
+ },
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+ {
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+ "id": "rock_and_roll_hall_of_fame",
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+ "place": "Rock and Roll Hall of Fame",
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+ "city": "Cleveland",
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+ "country": "United States",
576
+ "continent": "North America",
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+ "mode": "walking",
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+ "prompt": "A first-person POV walking through the glass pyramid facade of the Rock and Roll Hall of Fame on Cleveland's Lake Erie waterfront.",
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+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
580
+ "ref_image": "wikimedia_famous_places_usa/068_Ohio_Rock_and_Roll_Hall_of_Fame.jpg",
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+ "source_url": "https://en.wikipedia.org/wiki/Rock_and_Roll_Hall_of_Fame"
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+ },
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+ {
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+ "id": "oklahoma_city_national_memorial",
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+ "place": "Oklahoma City National Memorial",
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+ "city": "Oklahoma City",
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+ "country": "United States",
588
+ "continent": "North America",
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+ "mode": "walking",
590
+ "prompt": "A first-person POV walking through rows of empty bronze chairs on the reflecting pool lawn of the Oklahoma City National Memorial, the Survivor Tree standing nearby.",
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+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
592
+ "ref_image": "wikimedia_famous_places_usa/063_Oklahoma_Oklahoma_City_National_Memorial.jpg",
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+ "source_url": "https://en.wikipedia.org/wiki/Oklahoma_City_National_Memorial"
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+ },
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+ {
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+ "id": "crater_lake_national_park",
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+ "place": "Crater Lake National Park",
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+ "city": "Oregon",
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+ "country": "United States",
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+ "continent": "North America",
601
+ "mode": "driving",
602
+ "prompt": "A dashcam POV driving through Rim Drive circling high above Crater Lake's impossibly deep blue volcanic caldera water, Wizard Island visible below.",
603
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
604
+ "ref_image": "wikimedia_famous_places_usa/049_Oregon_Crater_Lake_National_Park.jpg",
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+ "source_url": "https://en.wikipedia.org/wiki/Crater_Lake_National_Park"
606
+ },
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+ {
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+ "id": "liberty_bell",
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+ "place": "Liberty Bell",
610
+ "city": "Philadelphia",
611
+ "country": "United States",
612
+ "continent": "North America",
613
+ "mode": "walking",
614
+ "prompt": "A first-person POV walking through the cracked bronze Liberty Bell displayed in its glass pavilion, Independence Hall's brick facade visible through the windows behind it.",
615
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
616
+ "ref_image": "wikimedia_famous_places_usa/069_Pennsylvania_Liberty_Bell.jpg",
617
+ "source_url": "https://en.wikipedia.org/wiki/Liberty_Bell"
618
+ },
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+ {
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+ "id": "the_breakers",
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+ "place": "The Breakers",
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+ "city": "Newport, Rhode Island",
623
+ "country": "United States",
624
+ "continent": "North America",
625
+ "mode": "walking",
626
+ "prompt": "A first-person POV walking through the ornate limestone facade and manicured oceanfront lawn of The Breakers mansion, waves crashing on the rocks below.",
627
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
628
+ "ref_image": "wikimedia_famous_places_usa/051_Rhode_Island_The_Breakers.jpg",
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+ "source_url": "https://en.wikipedia.org/wiki/The_Breakers"
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+ },
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+ {
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+ "id": "fort_sumter",
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+ "place": "Fort Sumter",
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+ "city": "Charleston, South Carolina",
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+ "country": "United States",
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+ "continent": "North America",
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+ "mode": "walking",
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+ "prompt": "A first-person POV walking through the low brick ramparts and cannons of Fort Sumter rising from its small island in Charleston harbor.",
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+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
640
+ "ref_image": "wikimedia_famous_places_usa/070_South_Carolina_Fort_Sumter.jpg",
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+ "source_url": "https://en.wikipedia.org/wiki/Fort_Sumter"
642
+ },
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+ {
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+ "id": "great_smoky_mountains_national_park",
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+ "place": "Great Smoky Mountains National Park",
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+ "city": "Tennessee",
647
+ "country": "United States",
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+ "continent": "North America",
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+ "mode": "driving",
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+ "prompt": "A dashcam POV driving through Newfound Gap Road climbing through misty blue-tinged ridgelines of the Great Smoky Mountains, dense forest stretching to the horizon.",
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+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
652
+ "ref_image": "wikimedia_famous_places_usa/064_Tennessee_Great_Smoky_Mountains_National_Park.jpg",
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+ "source_url": "https://en.wikipedia.org/wiki/Great_Smoky_Mountains_National_Park"
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+ },
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+ {
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+ "id": "the_alamo",
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+ "place": "The Alamo",
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+ "city": "San Antonio",
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+ "country": "United States",
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+ "continent": "North America",
661
+ "mode": "walking",
662
+ "prompt": "A first-person POV walking through the curved stone facade and bell-shaped parapet of the Alamo mission chapel in downtown San Antonio.",
663
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
664
+ "ref_image": "wikimedia_famous_places_usa/054_Texas_The_Alamo.jpg",
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+ "source_url": "https://en.wikipedia.org/wiki/Battle_of_the_Alamo"
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+ },
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+ {
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+ "id": "shelburne_farms",
669
+ "place": "Shelburne Farms",
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+ "city": "Shelburne, Vermont",
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+ "country": "United States",
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+ "continent": "North America",
673
+ "mode": "driving",
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+ "prompt": "A dashcam POV driving through a pastoral farm road past red barns and grazing fields at Shelburne Farms, Lake Champlain and the Adirondacks visible in the distance.",
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+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
676
+ "ref_image": "wikimedia_famous_places_usa/055_Vermont_Shelburne_Farms.png",
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+ "source_url": "https://en.wikipedia.org/wiki/Shelburne_Farms"
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+ },
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+ {
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+ "id": "monticello",
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+ "place": "Monticello",
682
+ "city": "Charlottesville, Virginia",
683
+ "country": "United States",
684
+ "continent": "North America",
685
+ "mode": "walking",
686
+ "prompt": "A first-person POV walking through the red-brick, white-domed neoclassical facade of Monticello overlooking its terraced gardens in the Virginia hills.",
687
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
688
+ "ref_image": "wikimedia_famous_places_usa/056_Virginia_Monticello.JPG",
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+ "source_url": "https://en.wikipedia.org/wiki/Monticello"
690
+ },
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+ {
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+ "id": "new_river_gorge_bridge",
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+ "place": "New River Gorge Bridge",
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+ "city": "West Virginia",
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+ "country": "United States",
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+ "continent": "North America",
697
+ "mode": "driving",
698
+ "prompt": "A dashcam POV driving through a steel arch bridge deck crossing high above the deep forested New River Gorge.",
699
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
700
+ "ref_image": "wikimedia_famous_places_usa/057_West_Virginia_New_River_Gorge_Bridge.jpg",
701
+ "source_url": "https://en.wikipedia.org/wiki/New_River_Gorge_Bridge"
702
+ },
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+ {
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+ "id": "wisconsin_state_capitol",
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+ "place": "Wisconsin State Capitol",
706
+ "city": "Madison",
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+ "country": "United States",
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+ "continent": "North America",
709
+ "mode": "walking",
710
+ "prompt": "A first-person POV walking through the white granite dome of the Wisconsin State Capitol rising above Capitol Square, State Street stretching away from its base.",
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+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
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+ "ref_image": "wikimedia_famous_places_usa/058_Wisconsin_Wisconsin_State_Capitol.jpg",
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+ "source_url": "https://en.wikipedia.org/wiki/Wisconsin_State_Capitol"
714
+ },
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+ {
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+ "id": "lincoln_memorial",
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+ "place": "Lincoln Memorial",
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+ "city": "Washington, D.C.",
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+ "country": "United States",
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+ "continent": "North America",
721
+ "mode": "walking",
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+ "prompt": "A first-person POV walking through the towering marble columns and seated Lincoln statue inside the Lincoln Memorial, the National Mall's reflecting pool stretching out front.",
723
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
724
+ "ref_image": "wikimedia_famous_places_usa/059_Washington_D_C_Lincoln_Memorial.JPG",
725
+ "source_url": "https://en.wikipedia.org/wiki/Lincoln_Memorial"
726
+ }
727
+ ]
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+ }
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+ "place": "Eiffel Tower",
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+ "city": "Paris",
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+ "country": "France",
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+ "continent": "Europe",
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+ "mode": "walking",
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+ "prompt": "A first-person POV walking through the Eiffel Tower's iron lattice legs and arched base rising directly overhead, the Champ de Mars lawns and Trocadero fountains framing it from below.",
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+ "id": "great_wall_of_china",
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+ "continent": "Asia",
37
+ "mode": "walking",
38
+ "prompt": "A first-person POV walking through the Great Wall's crenellated stone ramparts and watchtowers snaking along steep forested mountain ridges as far as the eye can see.",
39
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
40
+ "ref_image": "wikimedia_famous_places/002_Great_Wall_of_China.jpg",
41
+ "source_url": "https://en.wikipedia.org/wiki/Great_Wall_of_China"
42
+ },
43
+ {
44
+ "id": "taj_mahal",
45
+ "place": "Taj Mahal",
46
+ "city": "Agra",
47
+ "country": "India",
48
+ "continent": "Asia",
49
+ "mode": "walking",
50
+ "prompt": "A first-person POV walking through the Taj Mahal's white marble dome and four minarets mirrored in the long reflecting pool of its Mughal garden.",
51
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
52
+ "ref_image": "wikimedia_famous_places/003_Taj_Mahal.jpg",
53
+ "source_url": "https://en.wikipedia.org/wiki/Taj_Mahal"
54
+ },
55
+ {
56
+ "id": "colosseum",
57
+ "place": "Colosseum",
58
+ "city": "Rome",
59
+ "country": "Italy",
60
+ "continent": "Europe",
61
+ "mode": "walking",
62
+ "prompt": "A first-person POV walking through the Colosseum's tiered stone arches and broken upper tier looming over the ancient paving stones of the Roman Forum nearby.",
63
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
64
+ "ref_image": "wikimedia_famous_places/004_Colosseum.jpg",
65
+ "source_url": "https://en.wikipedia.org/wiki/Colosseum"
66
+ },
67
+ {
68
+ "id": "statue_of_liberty",
69
+ "place": "Statue of Liberty",
70
+ "city": "New York",
71
+ "country": "United States",
72
+ "continent": "North America",
73
+ "mode": "walking",
74
+ "prompt": "A first-person POV walking through the green copper Statue of Liberty with her raised torch and spiked crown standing on Liberty Island, the Manhattan skyline visible across the harbor.",
75
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
76
+ "ref_image": "wikimedia_famous_places/005_Statue_of_Liberty.jpg",
77
+ "source_url": "https://en.wikipedia.org/wiki/Statue_of_Liberty"
78
+ },
79
+ {
80
+ "id": "great_pyramid_of_giza",
81
+ "place": "Great Pyramid of Giza",
82
+ "city": "Giza",
83
+ "country": "Egypt",
84
+ "continent": "Africa",
85
+ "mode": "walking",
86
+ "prompt": "A first-person POV walking through the massive limestone blocks of the Great Pyramid rising from the sandy Giza plateau, the Sphinx crouched nearby and desert stretching to the horizon.",
87
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
88
+ "ref_image": "wikimedia_famous_places/006_Great_Pyramid_of_Giza.jpg",
89
+ "source_url": "https://en.wikipedia.org/wiki/Great_Pyramid_of_Giza"
90
+ },
91
+ {
92
+ "id": "machu_picchu",
93
+ "place": "Machu Picchu",
94
+ "city": "Cusco Region",
95
+ "country": "Peru",
96
+ "continent": "South America",
97
+ "mode": "walking",
98
+ "prompt": "A first-person POV walking through the terraced stone ruins of Machu Picchu perched on a green mountain saddle, steep jungle-covered peaks and Huayna Picchu rising behind.",
99
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
100
+ "ref_image": "wikimedia_famous_places/007_Machu_Picchu.jpg",
101
+ "source_url": "https://en.wikipedia.org/wiki/Machu_Picchu"
102
+ },
103
+ {
104
+ "id": "christ_the_redeemer",
105
+ "place": "Christ the Redeemer",
106
+ "city": "Rio de Janeiro",
107
+ "country": "Brazil",
108
+ "continent": "South America",
109
+ "mode": "walking",
110
+ "prompt": "A first-person POV walking through the towering Art Deco statue of Christ the Redeemer with outstretched arms atop Corcovado mountain, Rio's beaches and Sugarloaf visible far below.",
111
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
112
+ "ref_image": "wikimedia_famous_places/008_Christ_the_Redeemer.jpg",
113
+ "source_url": "https://commons.wikimedia.org/wiki/File:Christ_the_Redeemer_-_Cristo_Redentor.jpg"
114
+ },
115
+ {
116
+ "id": "sydney_opera_house",
117
+ "place": "Sydney Opera House",
118
+ "city": "Sydney",
119
+ "country": "Australia",
120
+ "continent": "Oceania",
121
+ "mode": "walking",
122
+ "prompt": "A first-person POV walking through the white sail-shaped shells of the Sydney Opera House on Bennelong Point, the Harbour Bridge's steel arch spanning the water behind it.",
123
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
124
+ "ref_image": "wikimedia_famous_places/009_Sydney_Opera_House.jpg",
125
+ "source_url": "https://en.wikipedia.org/wiki/Sydney_Opera_House"
126
+ },
127
+ {
128
+ "id": "big_ben",
129
+ "place": "Big Ben",
130
+ "city": "London",
131
+ "country": "United Kingdom",
132
+ "continent": "Europe",
133
+ "mode": "walking",
134
+ "prompt": "A first-person POV walking through the Gothic clock tower of Big Ben rising above the Palace of Westminster, red buses crossing Westminster Bridge over the Thames alongside.",
135
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
136
+ "ref_image": "wikimedia_famous_places/010_Big_Ben.jpg",
137
+ "source_url": "https://en.wikipedia.org/wiki/Big_Ben"
138
+ },
139
+ {
140
+ "id": "stonehenge",
141
+ "place": "Stonehenge",
142
+ "city": "Wiltshire",
143
+ "country": "United Kingdom",
144
+ "continent": "Europe",
145
+ "mode": "walking",
146
+ "prompt": "A first-person POV walking through the massive gray sarsen stones of Stonehenge arranged in their ancient circle on the open, windswept Salisbury Plain.",
147
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
148
+ "ref_image": "wikimedia_famous_places/011_Stonehenge.jpg",
149
+ "source_url": "https://en.wikipedia.org/wiki/Stonehenge"
150
+ },
151
+ {
152
+ "id": "acropolis_of_athens",
153
+ "place": "Acropolis of Athens",
154
+ "city": "Athens",
155
+ "country": "Greece",
156
+ "continent": "Europe",
157
+ "mode": "walking",
158
+ "prompt": "A first-person POV walking through the marble columns of the Parthenon crowning the rocky Acropolis hill, whitewashed Athens sprawling beneath in every direction.",
159
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
160
+ "ref_image": "wikimedia_famous_places/012_Acropolis_of_Athens.jpg",
161
+ "source_url": "https://en.wikipedia.org/wiki/Acropolis_of_Athens"
162
+ },
163
+ {
164
+ "id": "sagrada_familia",
165
+ "place": "Sagrada Familia",
166
+ "city": "Barcelona",
167
+ "country": "Spain",
168
+ "continent": "Europe",
169
+ "mode": "walking",
170
+ "prompt": "A first-person POV walking through Gaudi's Sagrada Familia with its organic stone spires and intricate carved facades towering over the surrounding Barcelona street grid.",
171
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
172
+ "ref_image": "wikimedia_famous_places/013_Sagrada_Familia.jpg",
173
+ "source_url": "https://en.wikipedia.org/wiki/Sagrada_Fam%C3%ADlia"
174
+ },
175
+ {
176
+ "id": "neuschwanstein_castle",
177
+ "place": "Neuschwanstein Castle",
178
+ "city": "Schwangau",
179
+ "country": "Germany",
180
+ "continent": "Europe",
181
+ "mode": "driving",
182
+ "prompt": "A dashcam POV driving through a forested mountain road curving up toward the fairy-tale white towers and turrets of Neuschwanstein Castle perched on its rocky outcrop.",
183
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
184
+ "ref_image": "wikimedia_famous_places/014_Neuschwanstein_Castle.jpg",
185
+ "source_url": "https://en.wikipedia.org/wiki/Neuschwanstein_Castle"
186
+ },
187
+ {
188
+ "id": "leaning_tower_of_pisa",
189
+ "place": "Leaning Tower of Pisa",
190
+ "city": "Pisa",
191
+ "country": "Italy",
192
+ "continent": "Europe",
193
+ "mode": "walking",
194
+ "prompt": "A first-person POV walking through the white marble tiers of the Leaning Tower of Pisa tilting above the green lawn of the Field of Miracles, the cathedral and baptistery nearby.",
195
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
196
+ "ref_image": "wikimedia_famous_places/015_Leaning_Tower_of_Pisa.jpg",
197
+ "source_url": "https://en.wikipedia.org/wiki/Leaning_Tower_of_Pisa"
198
+ },
199
+ {
200
+ "id": "mount_fuji",
201
+ "place": "Mount Fuji",
202
+ "city": "Honshu",
203
+ "country": "Japan",
204
+ "continent": "Asia",
205
+ "mode": "driving",
206
+ "prompt": "A dashcam POV driving through a winding highway through pine forest with the snow-capped, near-perfect cone of Mount Fuji rising alone against the sky.",
207
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
208
+ "ref_image": "wikimedia_famous_places/016_Mount_Fuji.jpg",
209
+ "source_url": "https://en.wikipedia.org/wiki/Mount_Fuji"
210
+ },
211
+ {
212
+ "id": "golden_gate_bridge",
213
+ "place": "Golden Gate Bridge",
214
+ "city": "San Francisco",
215
+ "country": "United States",
216
+ "continent": "North America",
217
+ "mode": "driving",
218
+ "prompt": "A dashcam POV driving through the burnt-orange towers and suspension cables of the Golden Gate Bridge stretching across the bay fog toward the San Francisco skyline.",
219
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
220
+ "ref_image": "wikimedia_famous_places/017_Golden_Gate_Bridge.jpg",
221
+ "source_url": "https://en.wikipedia.org/wiki/Golden_Gate_Bridge"
222
+ },
223
+ {
224
+ "id": "burj_khalifa",
225
+ "place": "Burj Khalifa",
226
+ "city": "Dubai",
227
+ "country": "United Arab Emirates",
228
+ "continent": "Asia",
229
+ "mode": "walking",
230
+ "prompt": "A first-person POV walking through the needle-thin, tiered glass spire of the Burj Khalifa soaring above Dubai's fountain plaza and surrounding glass towers.",
231
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
232
+ "ref_image": "wikimedia_famous_places/018_Burj_Khalifa.jpg",
233
+ "source_url": "https://en.wikipedia.org/wiki/Burj_Khalifa"
234
+ },
235
+ {
236
+ "id": "petra",
237
+ "place": "Petra",
238
+ "city": "Petra",
239
+ "country": "Jordan",
240
+ "continent": "Asia",
241
+ "mode": "walking",
242
+ "prompt": "A first-person POV walking through the narrow sandstone canyon of the Siq opening onto Petra's rose-colored Treasury facade carved directly into the cliff face.",
243
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
244
+ "ref_image": "wikimedia_famous_places/019_Petra.jpg",
245
+ "source_url": "https://en.wikipedia.org/wiki/Petra"
246
+ },
247
+ {
248
+ "id": "angkor_wat",
249
+ "place": "Angkor Wat",
250
+ "city": "Siem Reap",
251
+ "country": "Cambodia",
252
+ "continent": "Asia",
253
+ "mode": "walking",
254
+ "prompt": "A first-person POV walking through Angkor Wat's five lotus-bud stone towers reflected in its moat, the causeway lined with naga balustrades leading toward the temple.",
255
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
256
+ "ref_image": "wikimedia_famous_places/020_Angkor_Wat.jpg",
257
+ "source_url": "https://en.wikipedia.org/wiki/Angkor_Wat"
258
+ },
259
+ {
260
+ "id": "chichen_itza",
261
+ "place": "Chichen Itza",
262
+ "city": "Yucatan",
263
+ "country": "Mexico",
264
+ "continent": "North America",
265
+ "mode": "walking",
266
+ "prompt": "A first-person POV walking through the stepped stone pyramid of El Castillo at Chichen Itza rising from a flat grassy plaza ringed by carved Mayan ruins.",
267
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
268
+ "ref_image": "wikimedia_famous_places/021_Chichen_Itza.jpg",
269
+ "source_url": "https://en.wikipedia.org/wiki/Chichen_Itza"
270
+ },
271
+ {
272
+ "id": "niagara_falls",
273
+ "place": "Niagara Falls",
274
+ "city": "Niagara Falls",
275
+ "country": "Canada",
276
+ "continent": "North America",
277
+ "mode": "walking",
278
+ "prompt": "A first-person POV walking through the thundering curtain of Niagara Falls' Horseshoe Falls throwing up clouds of mist, tour boats visible in the churning water below.",
279
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
280
+ "ref_image": "wikimedia_famous_places/022_Niagara_Falls.jpg",
281
+ "source_url": "https://en.wikipedia.org/wiki/Niagara_Falls"
282
+ },
283
+ {
284
+ "id": "grand_canyon",
285
+ "place": "Grand Canyon",
286
+ "city": "Arizona",
287
+ "country": "United States",
288
+ "continent": "North America",
289
+ "mode": "driving",
290
+ "prompt": "A dashcam POV driving through a rim-side highway along the Grand Canyon's South Rim, layered red-and-orange rock walls plunging away into a vast eroded gorge.",
291
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
292
+ "ref_image": "wikimedia_famous_places/023_Grand_Canyon.jpg",
293
+ "source_url": "https://en.wikipedia.org/wiki/Grand_Canyon"
294
+ },
295
+ {
296
+ "id": "mount_rushmore",
297
+ "place": "Mount Rushmore",
298
+ "city": "South Dakota",
299
+ "country": "United States",
300
+ "continent": "North America",
301
+ "mode": "walking",
302
+ "prompt": "A first-person POV walking through the four monumental granite presidential faces of Mount Rushmore carved into the pine-covered Black Hills mountainside.",
303
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
304
+ "ref_image": "wikimedia_famous_places/024_Mount_Rushmore.jpg",
305
+ "source_url": "https://en.wikipedia.org/wiki/Mount_Rushmore"
306
+ },
307
+ {
308
+ "id": "times_square",
309
+ "place": "Times Square",
310
+ "city": "New York",
311
+ "country": "United States",
312
+ "continent": "North America",
313
+ "mode": "walking",
314
+ "prompt": "A first-person POV walking through the towering, densely packed digital billboards and neon signage of Times Square glowing over crowded sidewalks and yellow taxis.",
315
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
316
+ "ref_image": "wikimedia_famous_places/025_Times_Square.jpg",
317
+ "source_url": "https://en.wikipedia.org/wiki/Times_Square"
318
+ },
319
+ {
320
+ "id": "notre_dame_de_paris",
321
+ "place": "Notre-Dame de Paris",
322
+ "city": "Paris",
323
+ "country": "France",
324
+ "continent": "Europe",
325
+ "mode": "walking",
326
+ "prompt": "A first-person POV walking through the twin Gothic towers and flying buttresses of Notre-Dame cathedral rising above the Ile de la Cite on the Seine.",
327
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
328
+ "ref_image": "wikimedia_famous_places/026_Notre_Dame_de_Paris.jpg",
329
+ "source_url": "https://en.wikipedia.org/wiki/Notre-Dame_de_Paris"
330
+ },
331
+ {
332
+ "id": "palace_of_versailles",
333
+ "place": "Palace of Versailles",
334
+ "city": "Versailles",
335
+ "country": "France",
336
+ "continent": "Europe",
337
+ "mode": "walking",
338
+ "prompt": "A first-person POV walking through the gilded facade and manicured geometric gardens of the Palace of Versailles stretching toward the Grand Canal fountain.",
339
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
340
+ "ref_image": "wikimedia_famous_places/027_Palace_of_Versailles.jpg",
341
+ "source_url": "https://en.wikipedia.org/wiki/Palace_of_Versailles"
342
+ },
343
+ {
344
+ "id": "buckingham_palace",
345
+ "place": "Buckingham Palace",
346
+ "city": "London",
347
+ "country": "United Kingdom",
348
+ "continent": "Europe",
349
+ "mode": "walking",
350
+ "prompt": "A first-person POV walking through the neoclassical facade of Buckingham Palace behind its iron gates, the Victoria Memorial statue and the Mall avenue leading toward it.",
351
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
352
+ "ref_image": "wikimedia_famous_places/028_Buckingham_Palace.jpg",
353
+ "source_url": "https://en.wikipedia.org/wiki/Buckingham_Palace"
354
+ },
355
+ {
356
+ "id": "tower_bridge",
357
+ "place": "Tower Bridge",
358
+ "city": "London",
359
+ "country": "United Kingdom",
360
+ "continent": "Europe",
361
+ "mode": "driving",
362
+ "prompt": "A dashcam POV driving through Tower Bridge's twin Victorian Gothic towers spanning the Thames, London's skyline and river traffic visible beneath the raised walkway.",
363
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
364
+ "ref_image": "wikimedia_famous_places/029_Tower_Bridge.jpg",
365
+ "source_url": "https://en.wikipedia.org/wiki/Tower_Bridge"
366
+ },
367
+ {
368
+ "id": "st__basil_s_cathedral",
369
+ "place": "St. Basil's Cathedral",
370
+ "city": "Moscow",
371
+ "country": "Russia",
372
+ "continent": "Europe",
373
+ "mode": "walking",
374
+ "prompt": "A first-person POV walking through the colorful swirling onion domes of St. Basil's Cathedral rising at the edge of Red Square's cobblestone expanse.",
375
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
376
+ "ref_image": "wikimedia_famous_places/030_St_Basil_s_Cathedral.jpg",
377
+ "source_url": "https://en.wikipedia.org/wiki/Saint_Basil%27s_Cathedral"
378
+ },
379
+ {
380
+ "id": "red_square",
381
+ "place": "Red Square",
382
+ "city": "Moscow",
383
+ "country": "Russia",
384
+ "continent": "Europe",
385
+ "mode": "walking",
386
+ "prompt": "A first-person POV walking through the vast cobblestone expanse of Red Square with the Kremlin's red brick walls and towers running along one side.",
387
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
388
+ "ref_image": "wikimedia_famous_places/031_Red_Square.jpg",
389
+ "source_url": "https://commons.wikimedia.org/wiki/File:Kremlin_and_Red_Square.1.jpg"
390
+ },
391
+ {
392
+ "id": "forbidden_city",
393
+ "place": "Forbidden City",
394
+ "city": "Beijing",
395
+ "country": "China",
396
+ "continent": "Asia",
397
+ "mode": "walking",
398
+ "prompt": "A first-person POV walking through the vermilion walls and golden-tiled roofs of the Forbidden City's palace halls arranged along its long central courtyard axis.",
399
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
400
+ "ref_image": "wikimedia_famous_places/032_Forbidden_City.jpg",
401
+ "source_url": "https://en.wikipedia.org/wiki/Forbidden_City"
402
+ },
403
+ {
404
+ "id": "terracotta_army",
405
+ "place": "Terracotta Army",
406
+ "city": "Xi'an",
407
+ "country": "China",
408
+ "continent": "Asia",
409
+ "mode": "walking",
410
+ "prompt": "A first-person POV walking through rows upon rows of life-sized terracotta soldier statues standing in excavated pits beneath a vast hangar-like museum roof.",
411
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
412
+ "ref_image": "wikimedia_famous_places/033_Terracotta_Army.jpg",
413
+ "source_url": "https://commons.wikimedia.org/wiki/File:51714-Terracota-Army.jpg"
414
+ },
415
+ {
416
+ "id": "himeji_castle",
417
+ "place": "Himeji Castle",
418
+ "city": "Himeji",
419
+ "country": "Japan",
420
+ "continent": "Asia",
421
+ "mode": "walking",
422
+ "prompt": "A first-person POV walking through the brilliant white plastered walls and stacked curved roofs of Himeji Castle rising above its stone ramparts and moat.",
423
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
424
+ "ref_image": "wikimedia_famous_places/034_Himeji_Castle.jpg",
425
+ "source_url": "https://en.wikipedia.org/wiki/Himeji_Castle"
426
+ },
427
+ {
428
+ "id": "mount_everest",
429
+ "place": "Mount Everest",
430
+ "city": "Khumbu",
431
+ "country": "Nepal",
432
+ "continent": "Asia",
433
+ "mode": "walking",
434
+ "prompt": "A first-person POV walking through a rocky Himalayan trekking trail with the jagged snow-and-rock pyramid of Mount Everest towering above prayer-flag-strung ridgelines.",
435
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
436
+ "ref_image": "wikimedia_famous_places/035_Mount_Everest.jpg",
437
+ "source_url": "https://en.wikipedia.org/wiki/Mount_Everest"
438
+ },
439
+ {
440
+ "id": "table_mountain",
441
+ "place": "Table Mountain",
442
+ "city": "Cape Town",
443
+ "country": "South Africa",
444
+ "continent": "Africa",
445
+ "mode": "walking",
446
+ "prompt": "A first-person POV walking through the flat-topped sandstone summit of Table Mountain seen from its plateau boardwalk, Cape Town and the Atlantic coastline spread out far below.",
447
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
448
+ "ref_image": "wikimedia_famous_places/036_Table_Mountain.jpg",
449
+ "source_url": "https://commons.wikimedia.org/wiki/File:Table_Mountain_DanieVDM.jpg"
450
+ },
451
+ {
452
+ "id": "victoria_falls",
453
+ "place": "Victoria Falls",
454
+ "city": "Livingstone",
455
+ "country": "Zambia",
456
+ "continent": "Africa",
457
+ "mode": "walking",
458
+ "prompt": "A first-person POV walking through the immense curtain of Victoria Falls plunging into the Zambezi gorge, spray rising in a permanent mist cloud over the rainforest edge.",
459
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
460
+ "ref_image": "wikimedia_famous_places/037_Victoria_Falls.jpg",
461
+ "source_url": "https://en.wikipedia.org/wiki/Victoria_Falls"
462
+ },
463
+ {
464
+ "id": "uluru",
465
+ "place": "Uluru",
466
+ "city": "Uluru",
467
+ "country": "Australia",
468
+ "continent": "Oceania",
469
+ "mode": "walking",
470
+ "prompt": "A first-person POV walking through the massive red sandstone monolith of Uluru glowing rust-orange against the flat desert scrub stretching to the horizon.",
471
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
472
+ "ref_image": "wikimedia_famous_places/038_Uluru.jpg",
473
+ "source_url": "https://en.wikipedia.org/wiki/Uluru"
474
+ },
475
+ {
476
+ "id": "great_barrier_reef",
477
+ "place": "Great Barrier Reef",
478
+ "city": "Queensland",
479
+ "country": "Australia",
480
+ "continent": "Oceania",
481
+ "mode": "walking",
482
+ "prompt": "A first-person POV walking through a wooden pontoon deck over the turquoise water of the Great Barrier Reef, coral formations visible just beneath the surface.",
483
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
484
+ "ref_image": "wikimedia_famous_places/039_Great_Barrier_Reef.jpg",
485
+ "source_url": "https://en.wikipedia.org/wiki/Great_Barrier_Reef"
486
+ },
487
+ {
488
+ "id": "sydney_harbour_bridge",
489
+ "place": "Sydney Harbour Bridge",
490
+ "city": "Sydney",
491
+ "country": "Australia",
492
+ "continent": "Oceania",
493
+ "mode": "driving",
494
+ "prompt": "A dashcam POV driving through the steel arch of the Sydney Harbour Bridge spanning the harbor, the Opera House's white sails visible across the water.",
495
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
496
+ "ref_image": "wikimedia_famous_places/040_Sydney_Harbour_Bridge.jpg",
497
+ "source_url": "https://en.wikipedia.org/wiki/Sydney_Harbour_Bridge"
498
+ },
499
+ {
500
+ "id": "cn_tower",
501
+ "place": "CN Tower",
502
+ "city": "Toronto",
503
+ "country": "Canada",
504
+ "continent": "North America",
505
+ "mode": "walking",
506
+ "prompt": "A first-person POV walking through the slender concrete CN Tower with its bulging observation pod rising above Toronto's downtown skyline and Lake Ontario waterfront.",
507
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
508
+ "ref_image": "wikimedia_famous_places/041_CN_Tower.jpg",
509
+ "source_url": "https://commons.wikimedia.org/wiki/File:Toronto_skyline_(13949978148).jpg"
510
+ },
511
+ {
512
+ "id": "empire_state_building",
513
+ "place": "Empire State Building",
514
+ "city": "New York",
515
+ "country": "United States",
516
+ "continent": "North America",
517
+ "mode": "walking",
518
+ "prompt": "A first-person POV walking through the tiered Art Deco setbacks and spire of the Empire State Building rising above Fifth Avenue's yellow-taxi traffic.",
519
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
520
+ "ref_image": "wikimedia_famous_places/042_Empire_State_Building.jpg",
521
+ "source_url": "https://en.wikipedia.org/wiki/Empire_State_Building"
522
+ },
523
+ {
524
+ "id": "brooklyn_bridge",
525
+ "place": "Brooklyn Bridge",
526
+ "city": "New York",
527
+ "country": "United States",
528
+ "continent": "North America",
529
+ "mode": "walking",
530
+ "prompt": "A first-person POV walking through the stone Gothic arches and web of suspension cables of the Brooklyn Bridge's pedestrian walkway, Manhattan's skyline framed ahead.",
531
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
532
+ "ref_image": "wikimedia_famous_places/043_Brooklyn_Bridge.jpg",
533
+ "source_url": "https://en.wikipedia.org/wiki/Brooklyn_Bridge"
534
+ },
535
+ {
536
+ "id": "hollywood_sign",
537
+ "place": "Hollywood Sign",
538
+ "city": "Los Angeles",
539
+ "country": "United States",
540
+ "continent": "North America",
541
+ "mode": "walking",
542
+ "prompt": "A first-person POV walking through a dusty chaparral trail climbing Mount Lee toward the giant white block letters of the Hollywood Sign, the LA basin sprawling below.",
543
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
544
+ "ref_image": "wikimedia_famous_places/044_Hollywood_Sign.jpg",
545
+ "source_url": "https://en.wikipedia.org/wiki/Hollywood_Sign"
546
+ },
547
+ {
548
+ "id": "alcatraz_island",
549
+ "place": "Alcatraz Island",
550
+ "city": "San Francisco",
551
+ "country": "United States",
552
+ "continent": "North America",
553
+ "mode": "walking",
554
+ "prompt": "A first-person POV walking through the weathered cellblock walls and lighthouse of Alcatraz prison rising from its rocky island, San Francisco's skyline visible across the bay.",
555
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
556
+ "ref_image": "wikimedia_famous_places/045_Alcatraz_Island.jpg",
557
+ "source_url": "https://en.wikipedia.org/wiki/Alcatraz_Island"
558
+ },
559
+ {
560
+ "id": "yellowstone_national_park",
561
+ "place": "Yellowstone National Park",
562
+ "city": "Wyoming",
563
+ "country": "United States",
564
+ "continent": "North America",
565
+ "mode": "driving",
566
+ "prompt": "A dashcam POV driving through a two-lane park road winding past steaming geysers and mineral-terraced hot springs in Yellowstone's high alpine basin.",
567
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
568
+ "ref_image": "wikimedia_famous_places/046_Yellowstone_National_Park.jpg",
569
+ "source_url": "https://en.wikipedia.org/wiki/Yellowstone_National_Park"
570
+ },
571
+ {
572
+ "id": "yosemite_national_park",
573
+ "place": "Yosemite National Park",
574
+ "city": "California",
575
+ "country": "United States",
576
+ "continent": "North America",
577
+ "mode": "driving",
578
+ "prompt": "A dashcam POV driving through a valley road beneath the sheer granite face of El Capitan and Half Dome, waterfalls streaking down the Yosemite valley walls.",
579
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
580
+ "ref_image": "wikimedia_famous_places/047_Yosemite_National_Park.jpg",
581
+ "source_url": "https://en.wikipedia.org/wiki/Yosemite_National_Park"
582
+ },
583
+ {
584
+ "id": "hoover_dam",
585
+ "place": "Hoover Dam",
586
+ "city": "Nevada/Arizona border",
587
+ "country": "United States",
588
+ "continent": "North America",
589
+ "mode": "driving",
590
+ "prompt": "A dashcam POV driving through the massive curved concrete face of Hoover Dam plunging into Black Canyon, the turquoise waters of Lake Mead pooling behind it.",
591
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
592
+ "ref_image": "wikimedia_famous_places/048_Hoover_Dam.jpg",
593
+ "source_url": "https://commons.wikimedia.org/wiki/File:2017_Aerial_view_Hoover_Dam_4774.jpg"
594
+ },
595
+ {
596
+ "id": "space_needle",
597
+ "place": "Space Needle",
598
+ "city": "Seattle",
599
+ "country": "United States",
600
+ "continent": "North America",
601
+ "mode": "walking",
602
+ "prompt": "A first-person POV walking through the flying-saucer observation deck of the Space Needle atop its slender tapered tower, Seattle's skyline and Mount Rainier visible beyond.",
603
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
604
+ "ref_image": "wikimedia_famous_places/049_Space_Needle.jpg",
605
+ "source_url": "https://en.wikipedia.org/wiki/Space_Needle"
606
+ },
607
+ {
608
+ "id": "salar_de_uyuni",
609
+ "place": "Salar de Uyuni",
610
+ "city": "Potosi",
611
+ "country": "Bolivia",
612
+ "continent": "South America",
613
+ "mode": "driving",
614
+ "prompt": "A dashcam POV driving through an endless flat white expanse of salt crust stretching to the horizon on the Salar de Uyuni, distant volcanic peaks shimmering in the heat.",
615
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
616
+ "ref_image": "wikimedia_famous_places/050_Salar_de_Uyuni.jpg",
617
+ "source_url": "https://commons.wikimedia.org/wiki/File:Salar_Uyuni_au01.jpg"
618
+ },
619
+ {
620
+ "id": "iguazu_falls",
621
+ "place": "Iguazu Falls",
622
+ "city": "Misiones/Parana",
623
+ "country": "Argentina",
624
+ "continent": "South America",
625
+ "mode": "walking",
626
+ "prompt": "A first-person POV walking through a network of metal walkways threading through spray and rainbows in front of Iguazu Falls' horseshoe of cascading waterfalls.",
627
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
628
+ "ref_image": "wikimedia_famous_places/051_Iguazu_Falls.jpg",
629
+ "source_url": "https://en.wikipedia.org/wiki/Iguazu_Falls"
630
+ },
631
+ {
632
+ "id": "easter_island_moai",
633
+ "place": "Easter Island Moai",
634
+ "city": "Rapa Nui",
635
+ "country": "Chile",
636
+ "continent": "South America",
637
+ "mode": "walking",
638
+ "prompt": "A first-person POV walking through a row of giant stone Moai statues standing shoulder to shoulder on a grassy coastal platform, the Pacific Ocean behind them.",
639
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
640
+ "ref_image": "wikimedia_famous_places/052_Easter_Island_Moai.jpg",
641
+ "source_url": "https://commons.wikimedia.org/wiki/File:AhuTongariki.JPG"
642
+ },
643
+ {
644
+ "id": "galapagos_islands",
645
+ "place": "Galapagos Islands",
646
+ "city": "Galapagos",
647
+ "country": "Ecuador",
648
+ "continent": "South America",
649
+ "mode": "walking",
650
+ "prompt": "A first-person POV walking through a rocky volcanic shoreline trail on the Galapagos Islands with marine iguanas basking and blue-footed boobies nesting among the black lava rocks.",
651
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
652
+ "ref_image": "wikimedia_famous_places/053_Galapagos_Islands.jpg",
653
+ "source_url": "https://en.wikipedia.org/wiki/Gal%C3%A1pagos_Islands"
654
+ },
655
+ {
656
+ "id": "amazon_rainforest",
657
+ "place": "Amazon Rainforest",
658
+ "city": "Amazonas",
659
+ "country": "Brazil",
660
+ "continent": "South America",
661
+ "mode": "walking",
662
+ "prompt": "A first-person POV walking through a narrow jungle trail beneath the dense emerald canopy of the Amazon Rainforest, vines and buttressed tree trunks crowding the path.",
663
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
664
+ "ref_image": "wikimedia_famous_places/054_Amazon_Rainforest.jpg",
665
+ "source_url": "https://en.wikipedia.org/wiki/Amazon_rainforest"
666
+ },
667
+ {
668
+ "id": "cristo_rei",
669
+ "place": "Cristo Rei",
670
+ "city": "Almada",
671
+ "country": "Portugal",
672
+ "continent": "Europe",
673
+ "mode": "walking",
674
+ "prompt": "A first-person POV walking through the tall white statue of Cristo Rei with outstretched arms overlooking the Tagus River and the 25 de Abril suspension bridge to Lisbon.",
675
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
676
+ "ref_image": "wikimedia_famous_places/055_Cristo_Rei.jpg",
677
+ "source_url": "https://commons.wikimedia.org/wiki/File:Cristo_Rei_(36211699613)_(cropped).jpg"
678
+ },
679
+ {
680
+ "id": "belem_tower",
681
+ "place": "Belem Tower",
682
+ "city": "Lisbon",
683
+ "country": "Portugal",
684
+ "continent": "Europe",
685
+ "mode": "walking",
686
+ "prompt": "A first-person POV walking through the fortified stone turrets and Manueline carvings of Belem Tower rising from the banks of the Tagus River.",
687
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
688
+ "ref_image": "wikimedia_famous_places/056_Belem_Tower.jpg",
689
+ "source_url": "https://commons.wikimedia.org/wiki/File:Bel%C3%A9m_Tower_in_Lisbon,_Portugal.jpg"
690
+ },
691
+ {
692
+ "id": "alhambra",
693
+ "place": "Alhambra",
694
+ "city": "Granada",
695
+ "country": "Spain",
696
+ "continent": "Europe",
697
+ "mode": "walking",
698
+ "prompt": "A first-person POV walking through the intricate carved archways and reflecting pools of the Alhambra's Nasrid palaces, the Sierra Nevada mountains rising behind its red fortress walls.",
699
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
700
+ "ref_image": "wikimedia_famous_places/057_Alhambra.jpg",
701
+ "source_url": "https://en.wikipedia.org/wiki/Alhambra"
702
+ },
703
+ {
704
+ "id": "park_guell",
705
+ "place": "Park Guell",
706
+ "city": "Barcelona",
707
+ "country": "Spain",
708
+ "continent": "Europe",
709
+ "mode": "walking",
710
+ "prompt": "A first-person POV walking through Gaudi's mosaic-tiled serpentine bench and colorful gatehouse pavilions in Park Guell, overlooking Barcelona's rooftops toward the sea.",
711
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
712
+ "ref_image": "wikimedia_famous_places/058_Park_Guell.jpg",
713
+ "source_url": "https://commons.wikimedia.org/wiki/File:Parc_guell_-_panoramio.jpg"
714
+ },
715
+ {
716
+ "id": "mont_saint_michel",
717
+ "place": "Mont Saint-Michel",
718
+ "city": "Normandy",
719
+ "country": "France",
720
+ "continent": "Europe",
721
+ "mode": "walking",
722
+ "prompt": "A first-person POV walking through the spired abbey of Mont Saint-Michel rising from its rocky tidal island, medieval stone ramparts encircling the base.",
723
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
724
+ "ref_image": "wikimedia_famous_places/059_Mont_Saint_Michel.jpg",
725
+ "source_url": "https://en.wikipedia.org/wiki/Mont-Saint-Michel"
726
+ },
727
+ {
728
+ "id": "louvre_museum",
729
+ "place": "Louvre Museum",
730
+ "city": "Paris",
731
+ "country": "France",
732
+ "continent": "Europe",
733
+ "mode": "walking",
734
+ "prompt": "A first-person POV walking through the glass Louvre Pyramid set in the palace's grand courtyard, the Louvre's ornate stone wings framing it on three sides.",
735
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
736
+ "ref_image": "wikimedia_famous_places/060_Louvre_Museum.jpg",
737
+ "source_url": "https://en.wikipedia.org/wiki/Louvre"
738
+ },
739
+ {
740
+ "id": "arc_de_triomphe",
741
+ "place": "Arc de Triomphe",
742
+ "city": "Paris",
743
+ "country": "France",
744
+ "continent": "Europe",
745
+ "mode": "walking",
746
+ "prompt": "A first-person POV walking through the massive stone Arc de Triomphe with its carved reliefs standing at the hub of Paris's radiating avenues.",
747
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
748
+ "ref_image": "wikimedia_famous_places/061_Arc_de_Triomphe.jpg",
749
+ "source_url": "https://en.wikipedia.org/wiki/Arc_de_Triomphe"
750
+ },
751
+ {
752
+ "id": "palace_of_westminster",
753
+ "place": "Palace of Westminster",
754
+ "city": "London",
755
+ "country": "United Kingdom",
756
+ "continent": "Europe",
757
+ "mode": "walking",
758
+ "prompt": "A first-person POV walking through the Gothic Revival spires and riverside terrace of the Palace of Westminster along the Thames, Big Ben's clock tower anchoring one end.",
759
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
760
+ "ref_image": "wikimedia_famous_places/062_Palace_of_Westminster.jpg",
761
+ "source_url": "https://en.wikipedia.org/wiki/Palace_of_Westminster"
762
+ },
763
+ {
764
+ "id": "edinburgh_castle",
765
+ "place": "Edinburgh Castle",
766
+ "city": "Edinburgh",
767
+ "country": "United Kingdom",
768
+ "continent": "Europe",
769
+ "mode": "walking",
770
+ "prompt": "A first-person POV walking through the dark volcanic-rock ramparts of Edinburgh Castle looming above the Royal Mile's cobblestones and gabled stone buildings.",
771
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
772
+ "ref_image": "wikimedia_famous_places/063_Edinburgh_Castle.jpg",
773
+ "source_url": "https://en.wikipedia.org/wiki/Edinburgh_Castle"
774
+ },
775
+ {
776
+ "id": "loch_ness",
777
+ "place": "Loch Ness",
778
+ "city": "Scottish Highlands",
779
+ "country": "United Kingdom",
780
+ "continent": "Europe",
781
+ "mode": "driving",
782
+ "prompt": "A dashcam POV driving through a narrow lochside road along the dark, deep waters of Loch Ness, misty green hills rising steeply from the shoreline.",
783
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
784
+ "ref_image": "wikimedia_famous_places/064_Loch_Ness.jpg",
785
+ "source_url": "https://commons.wikimedia.org/wiki/File:LochNessUrquhart.jpg"
786
+ },
787
+ {
788
+ "id": "cliffs_of_moher",
789
+ "place": "Cliffs of Moher",
790
+ "city": "County Clare",
791
+ "country": "Ireland",
792
+ "continent": "Europe",
793
+ "mode": "walking",
794
+ "prompt": "A first-person POV walking through a grassy clifftop trail along the sheer dark rock face of the Cliffs of Moher, the Atlantic Ocean crashing far below.",
795
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
796
+ "ref_image": "wikimedia_famous_places/065_Cliffs_of_Moher.jpg",
797
+ "source_url": "https://en.wikipedia.org/wiki/Cliffs_of_Moher"
798
+ },
799
+ {
800
+ "id": "trevi_fountain",
801
+ "place": "Trevi Fountain",
802
+ "city": "Rome",
803
+ "country": "Italy",
804
+ "continent": "Europe",
805
+ "mode": "walking",
806
+ "prompt": "A first-person POV walking through the baroque marble sculptures and cascading pools of the Trevi Fountain set against a palazzo facade in a narrow Roman piazza.",
807
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
808
+ "ref_image": "wikimedia_famous_places/066_Trevi_Fountain.jpg",
809
+ "source_url": "https://en.wikipedia.org/wiki/Trevi_Fountain"
810
+ },
811
+ {
812
+ "id": "vatican_museums",
813
+ "place": "Vatican Museums",
814
+ "city": "Vatican City",
815
+ "country": "Vatican City",
816
+ "continent": "Europe",
817
+ "mode": "walking",
818
+ "prompt": "A first-person POV walking through the frescoed galleries and famous spiral staircase of the Vatican Museums leading toward St. Peter's Basilica's dome.",
819
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
820
+ "ref_image": "wikimedia_famous_places/067_Vatican_Museums.jpg",
821
+ "source_url": "https://commons.wikimedia.org/wiki/File:Circular_staircase_of_the_Vatican_Museums_02.jpg"
822
+ },
823
+ {
824
+ "id": "st__peter_s_basilica",
825
+ "place": "St. Peter's Basilica",
826
+ "city": "Vatican City",
827
+ "country": "Vatican City",
828
+ "continent": "Europe",
829
+ "mode": "walking",
830
+ "prompt": "A first-person POV walking through the vast colonnaded expanse of St. Peter's Square opening onto the massive dome and facade of St. Peter's Basilica.",
831
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
832
+ "ref_image": "wikimedia_famous_places/068_St_Peter_s_Basilica.jpg",
833
+ "source_url": "https://en.wikipedia.org/wiki/St._Peter%27s_Basilica"
834
+ },
835
+ {
836
+ "id": "pantheon_rome",
837
+ "place": "Pantheon Rome",
838
+ "city": "Rome",
839
+ "country": "Italy",
840
+ "continent": "Europe",
841
+ "mode": "walking",
842
+ "prompt": "A first-person POV walking through the massive coffered dome and columned portico of the Pantheon rising over a small piazza in the middle of old Rome.",
843
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
844
+ "ref_image": "wikimedia_famous_places/069_Pantheon_Rome.jpg",
845
+ "source_url": "https://en.wikipedia.org/wiki/Pantheon%2C_Rome"
846
+ },
847
+ {
848
+ "id": "pompeii",
849
+ "place": "Pompeii",
850
+ "city": "Campania",
851
+ "country": "Italy",
852
+ "continent": "Europe",
853
+ "mode": "walking",
854
+ "prompt": "A first-person POV walking through the excavated stone streets and roofless ruined houses of Pompeii, Mount Vesuvius's silhouette looming in the background.",
855
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
856
+ "ref_image": "wikimedia_famous_places/070_Pompeii.jpg",
857
+ "source_url": "https://en.wikipedia.org/wiki/Pompeii"
858
+ },
859
+ {
860
+ "id": "venice_grand_canal",
861
+ "place": "Venice Grand Canal",
862
+ "city": "Venice",
863
+ "country": "Italy",
864
+ "continent": "Europe",
865
+ "mode": "walking",
866
+ "prompt": "A first-person POV walking through gondolas gliding down the Grand Canal past Venice's tilting Gothic palazzo facades and the arched Rialto Bridge.",
867
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
868
+ "ref_image": "wikimedia_famous_places/071_Venice_Grand_Canal.jpg",
869
+ "source_url": "https://en.wikipedia.org/wiki/Grand_Canal_%28Venice%29"
870
+ },
871
+ {
872
+ "id": "amalfi_coast",
873
+ "place": "Amalfi Coast",
874
+ "city": "Campania",
875
+ "country": "Italy",
876
+ "continent": "Europe",
877
+ "mode": "driving",
878
+ "prompt": "A dashcam POV driving through a narrow cliffside highway hugging the Amalfi Coast, pastel-colored towns clinging to terraced hillsides above the deep blue Tyrrhenian Sea.",
879
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
880
+ "ref_image": "wikimedia_famous_places/072_Amalfi_Coast.jpg",
881
+ "source_url": "https://en.wikipedia.org/wiki/Amalfi_Coast"
882
+ },
883
+ {
884
+ "id": "matterhorn",
885
+ "place": "Matterhorn",
886
+ "city": "Zermatt",
887
+ "country": "Switzerland",
888
+ "continent": "Europe",
889
+ "mode": "walking",
890
+ "prompt": "A first-person POV walking through an alpine trail below the Matterhorn's sheer pyramidal rock face, its snow-streaked flanks cutting a jagged silhouette against the sky.",
891
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
892
+ "ref_image": "wikimedia_famous_places/073_Matterhorn.jpg",
893
+ "source_url": "https://commons.wikimedia.org/wiki/File:Matterhorn_from_Domh%C3%BCtte_-_2.jpg"
894
+ },
895
+ {
896
+ "id": "swiss_alps",
897
+ "place": "Swiss Alps",
898
+ "city": "Bernese Oberland",
899
+ "country": "Switzerland",
900
+ "continent": "Europe",
901
+ "mode": "driving",
902
+ "prompt": "A dashcam POV driving through a mountain pass road winding through the snow-capped peaks of the Swiss Alps, green valley pastures and chalets far below.",
903
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
904
+ "ref_image": "wikimedia_famous_places/074_Swiss_Alps.jpg",
905
+ "source_url": "https://commons.wikimedia.org/wiki/Category:Bernese_Oberland"
906
+ },
907
+ {
908
+ "id": "charles_bridge_prague",
909
+ "place": "Charles Bridge Prague",
910
+ "city": "Prague",
911
+ "country": "Czech Republic",
912
+ "continent": "Europe",
913
+ "mode": "walking",
914
+ "prompt": "A first-person POV walking through the Gothic stone arches and rows of baroque statues lining Charles Bridge, Prague Castle's spires visible across the Vltava.",
915
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
916
+ "ref_image": "wikimedia_famous_places/075_Charles_Bridge_Prague.jpg",
917
+ "source_url": "https://en.wikipedia.org/wiki/Charles_Bridge"
918
+ },
919
+ {
920
+ "id": "prague_castle",
921
+ "place": "Prague Castle",
922
+ "city": "Prague",
923
+ "country": "Czech Republic",
924
+ "continent": "Europe",
925
+ "mode": "walking",
926
+ "prompt": "A first-person POV walking through the spires of St. Vitus Cathedral rising within Prague Castle's walled complex, red-tiled rooftops spreading down the hill below.",
927
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
928
+ "ref_image": "wikimedia_famous_places/076_Prague_Castle.jpg",
929
+ "source_url": "https://en.wikipedia.org/wiki/Prague_Castle"
930
+ },
931
+ {
932
+ "id": "brandenburg_gate",
933
+ "place": "Brandenburg Gate",
934
+ "city": "Berlin",
935
+ "country": "Germany",
936
+ "continent": "Europe",
937
+ "mode": "walking",
938
+ "prompt": "A first-person POV walking through the neoclassical columns and bronze quadriga of the Brandenburg Gate at the end of the wide Pariser Platz.",
939
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
940
+ "ref_image": "wikimedia_famous_places/077_Brandenburg_Gate.jpg",
941
+ "source_url": "https://en.wikipedia.org/wiki/Brandenburg_Gate"
942
+ },
943
+ {
944
+ "id": "cologne_cathedral",
945
+ "place": "Cologne Cathedral",
946
+ "city": "Cologne",
947
+ "country": "Germany",
948
+ "continent": "Europe",
949
+ "mode": "walking",
950
+ "prompt": "A first-person POV walking through the twin blackened Gothic spires of Cologne Cathedral towering directly above the plaza and rail station square at its base.",
951
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
952
+ "ref_image": "wikimedia_famous_places/078_Cologne_Cathedral.jpg",
953
+ "source_url": "https://en.wikipedia.org/wiki/Cologne_Cathedral"
954
+ },
955
+ {
956
+ "id": "hagia_sophia",
957
+ "place": "Hagia Sophia",
958
+ "city": "Istanbul",
959
+ "country": "Turkey",
960
+ "continent": "Europe",
961
+ "mode": "walking",
962
+ "prompt": "A first-person POV walking through the massive central dome and minarets of Hagia Sophia rising above Istanbul's old city rooftops near the Bosphorus.",
963
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
964
+ "ref_image": "wikimedia_famous_places/079_Hagia_Sophia.jpg",
965
+ "source_url": "https://en.wikipedia.org/wiki/Hagia_Sophia"
966
+ },
967
+ {
968
+ "id": "blue_mosque",
969
+ "place": "Blue Mosque",
970
+ "city": "Istanbul",
971
+ "country": "Turkey",
972
+ "continent": "Europe",
973
+ "mode": "walking",
974
+ "prompt": "A first-person POV walking through the cascading domes and six slender minarets of the Blue Mosque overlooking its courtyard fountain in Istanbul's Sultanahmet district.",
975
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
976
+ "ref_image": "wikimedia_famous_places/080_Blue_Mosque.jpg",
977
+ "source_url": "https://en.wikipedia.org/wiki/Blue_Mosque%2C_Istanbul"
978
+ },
979
+ {
980
+ "id": "cappadocia",
981
+ "place": "Cappadocia",
982
+ "city": "Nevsehir",
983
+ "country": "Turkey",
984
+ "continent": "Asia",
985
+ "mode": "driving",
986
+ "prompt": "A dashcam POV driving through a valley road winding among Cappadocia's cone-shaped rock formations and cave dwellings carved into pale volcanic tuff.",
987
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
988
+ "ref_image": "wikimedia_famous_places/081_Cappadocia.jpg",
989
+ "source_url": "https://en.wikipedia.org/wiki/Cappadocia"
990
+ },
991
+ {
992
+ "id": "luxor_temple",
993
+ "place": "Luxor Temple",
994
+ "city": "Luxor",
995
+ "country": "Egypt",
996
+ "continent": "Africa",
997
+ "mode": "walking",
998
+ "prompt": "A first-person POV walking through the towering carved pylons and avenue of sphinxes leading into Luxor Temple's colonnaded courtyards along the Nile.",
999
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
1000
+ "ref_image": "wikimedia_famous_places/082_Luxor_Temple.jpg",
1001
+ "source_url": "https://en.wikipedia.org/wiki/Luxor_Temple"
1002
+ },
1003
+ {
1004
+ "id": "abu_simbel",
1005
+ "place": "Abu Simbel",
1006
+ "city": "Aswan",
1007
+ "country": "Egypt",
1008
+ "continent": "Africa",
1009
+ "mode": "walking",
1010
+ "prompt": "A first-person POV walking through the four colossal seated statues of Ramesses II carved into the sandstone facade of Abu Simbel temple beside Lake Nasser.",
1011
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
1012
+ "ref_image": "wikimedia_famous_places/083_Abu_Simbel.jpg",
1013
+ "source_url": "https://commons.wikimedia.org/wiki/File:Ramsis,_Aswan_Governorate,_Egypt_-_panoramio.jpg"
1014
+ },
1015
+ {
1016
+ "id": "marrakech_medina",
1017
+ "place": "Marrakech Medina",
1018
+ "city": "Marrakech",
1019
+ "country": "Morocco",
1020
+ "continent": "Africa",
1021
+ "mode": "walking",
1022
+ "prompt": "A first-person POV walking through the maze of narrow alleys and market stalls in Marrakech's medina, the Koutoubia minaret rising above the rooftops.",
1023
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
1024
+ "ref_image": "wikimedia_famous_places/084_Marrakech_Medina.jpg",
1025
+ "source_url": "https://en.wikipedia.org/wiki/Marrakesh"
1026
+ },
1027
+ {
1028
+ "id": "sahara_desert",
1029
+ "place": "Sahara Desert",
1030
+ "city": "Merzouga",
1031
+ "country": "Morocco",
1032
+ "continent": "Africa",
1033
+ "mode": "driving",
1034
+ "prompt": "A dashcam POV driving through a dirt track winding across the rippling golden dunes of the Sahara Desert, a camel caravan silhouette crossing in the distance.",
1035
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
1036
+ "ref_image": "wikimedia_famous_places/085_Sahara_Desert.jpg",
1037
+ "source_url": "https://commons.wikimedia.org/wiki/Category:Western_Desert_(Egypt)"
1038
+ },
1039
+ {
1040
+ "id": "mount_kilimanjaro",
1041
+ "place": "Mount Kilimanjaro",
1042
+ "city": "Kilimanjaro Region",
1043
+ "country": "Tanzania",
1044
+ "continent": "Africa",
1045
+ "mode": "walking",
1046
+ "prompt": "A first-person POV walking through a dusty trekking trail across Kilimanjaro's alpine moorland, the mountain's flat glacier-capped summit rising above the clouds.",
1047
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
1048
+ "ref_image": "wikimedia_famous_places/086_Mount_Kilimanjaro.jpg",
1049
+ "source_url": "https://commons.wikimedia.org/wiki/File:Kilimanjaro_from_Amboseli.jpg"
1050
+ },
1051
+ {
1052
+ "id": "serengeti_national_park",
1053
+ "place": "Serengeti National Park",
1054
+ "city": "Serengeti",
1055
+ "country": "Tanzania",
1056
+ "continent": "Africa",
1057
+ "mode": "driving",
1058
+ "prompt": "A dashcam POV driving through a dirt safari track across the endless golden grass plains of the Serengeti, herds of wildebeest and acacia trees dotting the horizon.",
1059
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
1060
+ "ref_image": "wikimedia_famous_places/087_Serengeti_National_Park.jpg",
1061
+ "source_url": "https://en.wikipedia.org/wiki/Serengeti_National_Park"
1062
+ },
1063
+ {
1064
+ "id": "zanzibar",
1065
+ "place": "Zanzibar",
1066
+ "city": "Zanzibar City",
1067
+ "country": "Tanzania",
1068
+ "continent": "Africa",
1069
+ "mode": "walking",
1070
+ "prompt": "A first-person POV walking through the narrow whitewashed alleys and carved wooden doors of Stone Town, Zanzibar, palm trees and dhow boats visible near the waterfront.",
1071
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
1072
+ "ref_image": "wikimedia_famous_places/088_Zanzibar.jpg",
1073
+ "source_url": "https://commons.wikimedia.org/wiki/File:Boutres_pr%C3%A8s_de_la_plage_de_Stone_Town,_Zanzibar_-_panoramio.jpg"
1074
+ },
1075
+ {
1076
+ "id": "table_mountain_cape_town",
1077
+ "place": "Table Mountain Cape Town",
1078
+ "city": "Cape Town",
1079
+ "country": "South Africa",
1080
+ "continent": "Africa",
1081
+ "mode": "driving",
1082
+ "prompt": "A dashcam POV driving through a scenic coastal road curving along the Cape Town waterfront, the flat silhouette of Table Mountain rising above the city skyline.",
1083
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
1084
+ "ref_image": "wikimedia_famous_places/089_Table_Mountain_Cape_Town.jpg",
1085
+ "source_url": "https://commons.wikimedia.org/wiki/File:Table_Mountain_DanieVDM.jpg"
1086
+ },
1087
+ {
1088
+ "id": "robben_island",
1089
+ "place": "Robben Island",
1090
+ "city": "Cape Town",
1091
+ "country": "South Africa",
1092
+ "continent": "Africa",
1093
+ "mode": "walking",
1094
+ "prompt": "A first-person POV walking through the low whitewashed prison buildings and limestone quarry of Robben Island, Table Mountain visible across the water toward Cape Town.",
1095
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
1096
+ "ref_image": "wikimedia_famous_places/090_Robben_Island.jpg",
1097
+ "source_url": "https://en.wikipedia.org/wiki/Robben_Island"
1098
+ },
1099
+ {
1100
+ "id": "bagan_temples",
1101
+ "place": "Bagan Temples",
1102
+ "city": "Bagan",
1103
+ "country": "Myanmar",
1104
+ "continent": "Asia",
1105
+ "mode": "walking",
1106
+ "prompt": "A first-person POV walking through thousands of ancient red-brick stupas and temple spires of Bagan spreading across a dusty plain toward the horizon.",
1107
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
1108
+ "ref_image": "wikimedia_famous_places/091_Bagan_Temples.jpg",
1109
+ "source_url": "https://en.wikipedia.org/wiki/Bagan"
1110
+ },
1111
+ {
1112
+ "id": "ha_long_bay",
1113
+ "place": "Ha Long Bay",
1114
+ "city": "Ha Long",
1115
+ "country": "Vietnam",
1116
+ "continent": "Asia",
1117
+ "mode": "walking",
1118
+ "prompt": "A first-person POV walking through a wooden junk boat deck gliding among the towering limestone karst islands of Ha Long Bay rising from the emerald water.",
1119
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
1120
+ "ref_image": "wikimedia_famous_places/092_Ha_Long_Bay.jpg",
1121
+ "source_url": "https://commons.wikimedia.org/wiki/File:Ha_Long_Bay_in_2019.jpg"
1122
+ },
1123
+ {
1124
+ "id": "angkor_thom",
1125
+ "place": "Angkor Thom",
1126
+ "city": "Siem Reap",
1127
+ "country": "Cambodia",
1128
+ "continent": "Asia",
1129
+ "mode": "walking",
1130
+ "prompt": "A first-person POV walking through the giant serene stone faces carved into the towers of the Bayon temple at the heart of Angkor Thom.",
1131
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
1132
+ "ref_image": "wikimedia_famous_places/093_Angkor_Thom.jpg",
1133
+ "source_url": "https://en.wikipedia.org/wiki/Angkor_Thom"
1134
+ },
1135
+ {
1136
+ "id": "borobudur",
1137
+ "place": "Borobudur",
1138
+ "city": "Central Java",
1139
+ "country": "Indonesia",
1140
+ "continent": "Asia",
1141
+ "mode": "walking",
1142
+ "prompt": "A first-person POV walking through the stepped stone terraces and bell-shaped stupas of Borobudur temple rising in tiers against a backdrop of volcanic mountains.",
1143
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
1144
+ "ref_image": "wikimedia_famous_places/094_Borobudur.jpg",
1145
+ "source_url": "https://en.wikipedia.org/wiki/Borobudur"
1146
+ },
1147
+ {
1148
+ "id": "mount_bromo",
1149
+ "place": "Mount Bromo",
1150
+ "city": "East Java",
1151
+ "country": "Indonesia",
1152
+ "continent": "Asia",
1153
+ "mode": "driving",
1154
+ "prompt": "A dashcam POV driving through a dusty track across the vast Sea of Sand crater floor toward Mount Bromo's smoking volcanic cone rising from the mist.",
1155
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
1156
+ "ref_image": "wikimedia_famous_places/095_Mount_Bromo.jpg",
1157
+ "source_url": "https://en.wikipedia.org/wiki/Mount_Bromo"
1158
+ },
1159
+ {
1160
+ "id": "petronas_towers",
1161
+ "place": "Petronas Towers",
1162
+ "city": "Kuala Lumpur",
1163
+ "country": "Malaysia",
1164
+ "continent": "Asia",
1165
+ "mode": "walking",
1166
+ "prompt": "A first-person POV walking through the twin steel-and-glass spires of the Petronas Towers connected by their sky bridge, rising above Kuala Lumpur's park plaza.",
1167
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
1168
+ "ref_image": "wikimedia_famous_places/096_Petronas_Towers.jpg",
1169
+ "source_url": "https://commons.wikimedia.org/wiki/File:2012-11-11_Kuala_Lumpur_03.JPG"
1170
+ },
1171
+ {
1172
+ "id": "marina_bay_sands",
1173
+ "place": "Marina Bay Sands",
1174
+ "city": "Singapore",
1175
+ "country": "Singapore",
1176
+ "continent": "Asia",
1177
+ "mode": "walking",
1178
+ "prompt": "A first-person POV walking through the three towers of Marina Bay Sands topped by their surfboard-shaped SkyPark, Singapore's skyline reflected in the bay waterfront.",
1179
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
1180
+ "ref_image": "wikimedia_famous_places/097_Marina_Bay_Sands.jpg",
1181
+ "source_url": "https://en.wikipedia.org/wiki/Marina_Bay_Sands"
1182
+ },
1183
+ {
1184
+ "id": "milford_sound",
1185
+ "place": "Milford Sound",
1186
+ "city": "Fiordland",
1187
+ "country": "New Zealand",
1188
+ "continent": "Oceania",
1189
+ "mode": "driving",
1190
+ "prompt": "A dashcam POV driving through a narrow road threading through steep rainforested cliffs toward Milford Sound's dark fjord waters and cascading waterfalls.",
1191
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
1192
+ "ref_image": "wikimedia_famous_places/098_Milford_Sound.jpg",
1193
+ "source_url": "https://en.wikipedia.org/wiki/Milford_Sound"
1194
+ },
1195
+ {
1196
+ "id": "sky_tower_auckland",
1197
+ "place": "Sky Tower Auckland",
1198
+ "city": "Auckland",
1199
+ "country": "New Zealand",
1200
+ "continent": "Oceania",
1201
+ "mode": "walking",
1202
+ "prompt": "A first-person POV walking through the slender concrete Sky Tower rising above Auckland's harbor-front streets, its observation deck ringed by glass.",
1203
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
1204
+ "ref_image": "wikimedia_famous_places/099_Sky_Tower_Auckland.jpg",
1205
+ "source_url": "https://en.wikipedia.org/wiki/Sky_Tower_%28Auckland%29"
1206
+ },
1207
+ {
1208
+ "id": "twelve_apostles_australia",
1209
+ "place": "Twelve Apostles Australia",
1210
+ "city": "Victoria",
1211
+ "country": "Australia",
1212
+ "continent": "Oceania",
1213
+ "mode": "driving",
1214
+ "prompt": "A dashcam POV driving through a coastal highway along Victoria's Great Ocean Road, limestone sea stacks of the Twelve Apostles rising from the surf below sheer cliffs.",
1215
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
1216
+ "ref_image": "wikimedia_famous_places/100_Twelve_Apostles_Australia.jpg",
1217
+ "source_url": "https://en.wikipedia.org/wiki/The_Twelve_Apostles_%28Victoria%29"
1218
+ },
1219
+ {
1220
+ "id": "antelope_canyon",
1221
+ "place": "Antelope Canyon",
1222
+ "city": "Page, Arizona",
1223
+ "country": "United States",
1224
+ "continent": "North America",
1225
+ "mode": "walking",
1226
+ "prompt": "A first-person POV walking through the smooth swirling sandstone walls of Antelope Canyon glowing orange and purple where shafts of sunlight reach the narrow slot floor.",
1227
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
1228
+ "ref_image": "wikimedia_famous_places/101_Antelope_Canyon.jpg",
1229
+ "source_url": "https://commons.wikimedia.org/wiki/File:USA_Antelope-Canyon.jpg"
1230
+ },
1231
+ {
1232
+ "id": "monument_valley",
1233
+ "place": "Monument Valley",
1234
+ "city": "Arizona/Utah border",
1235
+ "country": "United States",
1236
+ "continent": "North America",
1237
+ "mode": "driving",
1238
+ "prompt": "A dashcam POV driving through a lone highway crossing the flat red desert of Monument Valley, isolated sandstone buttes and mesas rising against the horizon.",
1239
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
1240
+ "ref_image": "wikimedia_famous_places/102_Monument_Valley.jpg",
1241
+ "source_url": "https://en.wikipedia.org/wiki/Monument_Valley"
1242
+ },
1243
+ {
1244
+ "id": "banff_national_park",
1245
+ "place": "Banff National Park",
1246
+ "city": "Alberta",
1247
+ "country": "Canada",
1248
+ "continent": "North America",
1249
+ "mode": "driving",
1250
+ "prompt": "A dashcam POV driving through a mountain highway along turquoise Banff lakes, snow-capped Canadian Rockies peaks reflected in the still glacial water.",
1251
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location",
1252
+ "ref_image": "wikimedia_famous_places/103_Banff_National_Park.jpg",
1253
+ "source_url": "https://en.wikipedia.org/wiki/Banff_National_Park"
1254
+ }
1255
+ ]
1256
+ }
bench_t2v_space/score_claude.py ADDED
@@ -0,0 +1,261 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # SPDX-License-Identifier: Apache-2.0
2
+ """Sole eval signal for bench_t2v_space: Claude Opus 5 on Amazon Bedrock, used
3
+ as a VLM-as-judge over frames sampled from each generated video.
4
+
5
+ Replaces the previous two-model setup (local Qwen3.5-27B + TIGER-Lab/VideoScore2
6
+ combined by combine.py) -- there is now exactly one judge, so there is nothing
7
+ to combine; summarize.py just aggregates this scorer's output.
8
+
9
+ The rubric is unchanged from the Qwen3.5 version: three axes, each 0-10 --
10
+ `alignment` (is this the SPECIFIC named real-world place?), `quality`,
11
+ `smoothness`.
12
+
13
+ This bench has TWO manifests (worldwide, usa); run once per manifest with an
14
+ explicit --manifest/--videos-dir/--out-dir (the defaults point at worldwide).
15
+
16
+ Claude takes images, not video, so each video is reduced to K evenly-spaced
17
+ frames sent as JPEG images in one user turn. Frames are downscaled to
18
+ --max-side (default 768px long edge) to keep per-request image tokens
19
+ reasonable: Claude bills roughly (w*h)/750 tokens per image, so 8 frames at
20
+ 768x432 is ~3.5k image tokens per video.
21
+
22
+ Requirements:
23
+ pip install 'anthropic[bedrock]' # boto3 is what signs the SigV4 request
24
+ AWS credentials resolvable the usual way (env vars, ~/.aws, instance role)
25
+ AWS_REGION (or --aws-region) set to a region where the model is enabled
26
+
27
+ Usage (CPU node is fine -- no local model is loaded):
28
+ python score_claude.py --manifest manifest_worldwide.json --videos-dir outputs/worldwide/videos --out-dir outputs/worldwide
29
+ python score_claude.py --manifest manifest_usa.json --videos-dir outputs/usa/videos --out-dir outputs/usa
30
+ Output: <out-dir>/claude_scores.jsonl (resumable -- skips ids already present).
31
+ """
32
+ from __future__ import annotations
33
+
34
+ import argparse
35
+ import base64
36
+ import json
37
+ import re
38
+ import threading
39
+ from concurrent.futures import ThreadPoolExecutor
40
+ from pathlib import Path
41
+
42
+ import cv2
43
+ import numpy as np
44
+
45
+ HERE = Path(__file__).resolve().parent
46
+
47
+ DEFAULT_MODEL = "anthropic.claude-opus-5"
48
+ DEFAULT_REGION = "us-east-1"
49
+
50
+ K_FRAMES = 8
51
+ MAX_SIDE = 768
52
+ JPEG_QUALITY = 90
53
+ MAX_TOKENS = 4000
54
+
55
+ AXES = ("alignment", "quality", "smoothness")
56
+
57
+ JUDGE_PROMPT_TEMPLATE = """You are a STRICT, SKEPTICAL judge of an AI-generated video against the text prompt that produced it. Most generated videos have real flaws -- assume there are problems until the frames clearly prove otherwise. Do not give credit for "close enough" or "same general vibe."
58
+
59
+ Prompt: "{prompt}"
60
+
61
+ The prompt names a specific real-world place. The {k} images above are frames sampled evenly across the video's duration, in order.
62
+
63
+ Rate the video on three axes, each an integer from 0 to 10. Use the full range -- most videos should land in the 3-6 band; reserve 9-10 for videos with essentially no flaws.
64
+
65
+ alignment (does this show the SPECIFIC named place, not a generic lookalike?):
66
+ 10 = unmistakably the named place, every distinctive identifying feature (exact architecture, layout, landmarks) present and correct
67
+ 8-9 = clearly the named place, at most one minor identifying detail off
68
+ 6-7 = recognizable as the named place but missing or altering several distinctive features
69
+ 4-5 = generic scene of the right broad category (e.g. "a plaza", "a bridge") that could be anywhere -- does NOT capture what makes this place specific
70
+ 2-3 = only a loose thematic connection; a knowledgeable viewer would not identify this as the named place
71
+ 0-1 = wrong place entirely or unrecognizable
72
+
73
+ quality (sharpness, absence of warping/artifacts/melting geometry):
74
+ 10 = photoreal, no visible artifacts anywhere
75
+ 8-9 = very good, at most one small artifact on close inspection
76
+ 6-7 = noticeable but minor artifacts (soft warping, texture smearing) that don't dominate the frame
77
+ 4-5 = clear artifacts in multiple frames (melting geometry, garbled architectural detail, unstable structures)
78
+ 0-3 = pervasive artifacts, badly broken in most frames
79
+
80
+ smoothness (temporal coherence across the frames -- no flicker, no discontinuities, consistent object/architecture identity):
81
+ 10 = perfectly smooth and consistent throughout
82
+ 8-9 = very smooth, at most one minor discontinuity
83
+ 6-7 = mostly smooth but with a couple of noticeable jumps or identity drift
84
+ 4-5 = frequent flicker or objects/architecture changing shape or identity between frames
85
+ 0-3 = incoherent, frames barely relate to each other
86
+
87
+ Be honest and critical -- if you are uncertain whether a detail is correct, score it as if it is wrong, not right.
88
+
89
+ Respond with ONLY a JSON object, no other text, in exactly this form:
90
+ {{"alignment": <int 0-10>, "quality": <int 0-10>, "smoothness": <int 0-10>, "reason": "<one short sentence, naming the specific flaw if any>"}}
91
+ """
92
+
93
+
94
+ def item_meta(it: dict) -> dict:
95
+ """Manifest fields carried through onto every score record."""
96
+ return {"place": it["place"], "country": it["country"],
97
+ "continent": it["continent"], "mode": it["mode"]}
98
+
99
+
100
+ # --- generic below this line -------------------------------------------------
101
+
102
+ def make_client(mode: str, region: str, max_retries: int):
103
+ """Bedrock client. `mantle` is the Messages-API Bedrock endpoint and the
104
+ recommended path; `legacy` is the older bedrock-runtime InvokeModel path,
105
+ kept for accounts that only have that enabled (its model ids look like
106
+ `us.anthropic.claude-opus-5-v1:0` -- pass one with --model)."""
107
+ try:
108
+ from anthropic import AnthropicBedrock, AnthropicBedrockMantle
109
+ except ImportError as exc: # pragma: no cover
110
+ raise SystemExit(f"anthropic SDK not available: {exc}") from exc
111
+ cls = AnthropicBedrockMantle if mode == "mantle" else AnthropicBedrock
112
+ return cls(aws_region=region, max_retries=max_retries)
113
+
114
+
115
+ def sample_frames(video_path: Path, k: int) -> list[np.ndarray]:
116
+ """K evenly-spaced BGR frames across the whole video."""
117
+ cap = cv2.VideoCapture(str(video_path))
118
+ n = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
119
+ if n <= 0:
120
+ cap.release()
121
+ raise RuntimeError(f"no frames read from {video_path}")
122
+ frames = []
123
+ for i in np.linspace(0, n - 1, num=min(k, n), dtype=int):
124
+ cap.set(cv2.CAP_PROP_POS_FRAMES, int(i))
125
+ ok, frame = cap.read()
126
+ if ok:
127
+ frames.append(frame)
128
+ cap.release()
129
+ if not frames:
130
+ raise RuntimeError(f"no frames decoded from {video_path}")
131
+ return frames
132
+
133
+
134
+ def encode_jpeg(frame_bgr: np.ndarray, max_side: int) -> str:
135
+ h, w = frame_bgr.shape[:2]
136
+ scale = max_side / max(h, w)
137
+ if scale < 1:
138
+ frame_bgr = cv2.resize(frame_bgr, (int(w * scale), int(h * scale)),
139
+ interpolation=cv2.INTER_AREA)
140
+ ok, buf = cv2.imencode(".jpg", frame_bgr, [int(cv2.IMWRITE_JPEG_QUALITY), JPEG_QUALITY])
141
+ if not ok:
142
+ raise RuntimeError("cv2.imencode failed")
143
+ return base64.standard_b64encode(buf.tobytes()).decode("ascii")
144
+
145
+
146
+ def parse_judge_json(text: str) -> dict:
147
+ """Pull the JSON object out of the judge's reply and clamp the axes."""
148
+ m = re.search(r"\{.*\}", text, re.S)
149
+ if not m:
150
+ raise ValueError(f"no JSON object found in judge output: {text[:200]!r}")
151
+ obj = json.loads(m.group(0))
152
+ for axis in AXES:
153
+ obj[axis] = max(0.0, min(10.0, float(obj[axis])))
154
+ return obj
155
+
156
+
157
+ def judge_video(client, model: str, effort: str, prompt: str,
158
+ video_path: Path, k_frames: int, max_side: int) -> dict:
159
+ frames = sample_frames(video_path, k_frames)
160
+ content = [
161
+ {"type": "image", "source": {"type": "base64", "media_type": "image/jpeg",
162
+ "data": encode_jpeg(f, max_side)}}
163
+ for f in frames
164
+ ]
165
+ content.append({"type": "text",
166
+ "text": JUDGE_PROMPT_TEMPLATE.format(prompt=prompt, k=len(frames))})
167
+
168
+ response = client.messages.create(
169
+ model=model,
170
+ max_tokens=MAX_TOKENS,
171
+ thinking={"type": "adaptive"},
172
+ output_config={"effort": effort},
173
+ messages=[{"role": "user", "content": content}],
174
+ )
175
+ if response.stop_reason == "refusal":
176
+ category = getattr(response.stop_details, "category", None)
177
+ raise RuntimeError(f"model refused (category={category})")
178
+ text = "".join(b.text for b in response.content if b.type == "text")
179
+ if not text.strip():
180
+ raise RuntimeError(f"empty response (stop_reason={response.stop_reason})")
181
+ return parse_judge_json(text)
182
+
183
+
184
+ def parse_args() -> argparse.Namespace:
185
+ p = argparse.ArgumentParser(description="Score bench_t2v_space with Claude Opus 5 on Bedrock.")
186
+ p.add_argument("--manifest", default=str(HERE / "manifest_worldwide.json"))
187
+ p.add_argument("--videos-dir", default=str(HERE / "outputs" / "worldwide" / "videos"))
188
+ p.add_argument("--out-dir", default=str(HERE / "outputs" / "worldwide"))
189
+ p.add_argument("--model", default=DEFAULT_MODEL)
190
+ p.add_argument("--aws-region", default=None,
191
+ help=f"defaults to $AWS_REGION, else {DEFAULT_REGION}")
192
+ p.add_argument("--bedrock-mode", choices=("mantle", "legacy"), default="mantle")
193
+ p.add_argument("--effort", choices=("low", "medium", "high", "xhigh", "max"), default="medium")
194
+ p.add_argument("--limit", type=int, default=None)
195
+ p.add_argument("--k-frames", type=int, default=K_FRAMES)
196
+ p.add_argument("--max-side", type=int, default=MAX_SIDE)
197
+ p.add_argument("--concurrency", type=int, default=4)
198
+ p.add_argument("--max-retries", type=int, default=5)
199
+ return p.parse_args()
200
+
201
+
202
+ def main() -> None:
203
+ import os
204
+
205
+ args = parse_args()
206
+ region = args.aws_region or os.environ.get("AWS_REGION") or DEFAULT_REGION
207
+
208
+ manifest = json.load(open(args.manifest))
209
+ items = manifest["items"]
210
+ if args.limit is not None:
211
+ items = items[: args.limit]
212
+
213
+ videos_dir = Path(args.videos_dir)
214
+ out_dir = Path(args.out_dir)
215
+ out_dir.mkdir(parents=True, exist_ok=True)
216
+ scores_path = out_dir / "claude_scores.jsonl"
217
+ already = set()
218
+ if scores_path.exists():
219
+ for line in scores_path.read_text().splitlines():
220
+ if line.strip():
221
+ already.add(json.loads(line)["id"])
222
+
223
+ todo = [it for it in items if it["id"] not in already]
224
+ print(f"{len(items)} items, {len(already)} already scored, {len(todo)} to score")
225
+ print(f"judge: {args.model} via bedrock ({args.bedrock_mode}, region={region}, effort={args.effort})")
226
+
227
+ client = make_client(args.bedrock_mode, region, args.max_retries)
228
+ write_lock = threading.Lock()
229
+ counter = {"n": 0}
230
+
231
+ def work(it: dict) -> None:
232
+ video_path = videos_dir / f"{it['id']}.mp4"
233
+ meta = {"id": it["id"], **item_meta(it)}
234
+ if not video_path.exists():
235
+ with write_lock:
236
+ counter["n"] += 1
237
+ print(f"[{counter['n']}/{len(todo)}] SKIP {it['id']}: video not found")
238
+ return
239
+ try:
240
+ judge = judge_video(client, args.model, args.effort, it["prompt"],
241
+ video_path, args.k_frames, args.max_side)
242
+ record = {**meta, **{axis: judge[axis] for axis in AXES},
243
+ "reason": judge.get("reason", "")}
244
+ line = " ".join(f"{axis.split('_')[0]}={judge[axis]:.0f}" for axis in AXES)
245
+ except Exception as exc:
246
+ record = {**meta, "error": f"{type(exc).__name__}: {exc}"[:300]}
247
+ line = f"ERROR {exc}"
248
+ with write_lock:
249
+ counter["n"] += 1
250
+ print(f"[{counter['n']}/{len(todo)}] {it['id']}: {line}", flush=True)
251
+ with open(scores_path, "a") as f:
252
+ f.write(json.dumps(record) + "\n")
253
+
254
+ with ThreadPoolExecutor(max_workers=max(1, args.concurrency)) as pool:
255
+ list(pool.map(work, todo))
256
+
257
+ print(f"done -> {scores_path}")
258
+
259
+
260
+ if __name__ == "__main__":
261
+ main()
bench_t2v_space/summarize.py ADDED
@@ -0,0 +1,94 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # SPDX-License-Identifier: Apache-2.0
2
+ """Aggregate score_claude.py output into a per-video score file and a summary.
3
+
4
+ Replaces the old combine.py, which merged two judges (Qwen3.5 + VideoScore2).
5
+ Claude Opus 5 is now the only judge, so there is nothing to combine -- the
6
+ score is just the mean of the three rubric axes:
7
+
8
+ score = mean(alignment, quality, smoothness) / 10
9
+ pass = alignment >= 8 and quality >= 7
10
+
11
+ Thresholds are carried over unchanged from combine.py (alignment >= 8 means a
12
+ near-perfect place match, not just "recognizable"); the VideoScore2
13
+ `min(v,t,p) >= 4` gate is gone with the model that produced it.
14
+
15
+ Run once per manifest, matching score_claude.py's --out-dir:
16
+ python summarize.py --out-dir outputs/worldwide
17
+ python summarize.py --out-dir outputs/usa
18
+ Output: <out-dir>/scores.jsonl (per-video) + <out-dir>/summary.json.
19
+ """
20
+ from __future__ import annotations
21
+
22
+ import argparse
23
+ import json
24
+ from pathlib import Path
25
+
26
+ import numpy as np
27
+
28
+ HERE = Path(__file__).resolve().parent
29
+
30
+ AXES = ("alignment", "quality", "smoothness")
31
+ GROUP_KEYS = ("mode", "continent")
32
+
33
+ PASS_ALIGNMENT = 8.0
34
+ PASS_QUALITY = 7.0
35
+
36
+
37
+ def passed(r: dict) -> bool:
38
+ return r["alignment"] >= PASS_ALIGNMENT and r["quality"] >= PASS_QUALITY
39
+
40
+
41
+ # --- generic below this line -------------------------------------------------
42
+
43
+ def parse_args() -> argparse.Namespace:
44
+ p = argparse.ArgumentParser(description="Summarize Claude judge scores.")
45
+ p.add_argument("--out-dir", default=str(HERE / "outputs" / "worldwide"))
46
+ return p.parse_args()
47
+
48
+
49
+ def load_jsonl(path: Path) -> list[dict]:
50
+ if not path.exists():
51
+ raise SystemExit(f"missing {path} -- run score_claude.py first")
52
+ return [json.loads(l) for l in path.read_text().splitlines() if l.strip()]
53
+
54
+
55
+ def main() -> None:
56
+ args = parse_args()
57
+ out_dir = Path(args.out_dir)
58
+ records = load_jsonl(out_dir / "claude_scores.jsonl")
59
+
60
+ merged = []
61
+ for r in sorted(records, key=lambda x: x["id"]):
62
+ if "error" in r:
63
+ merged.append({**{k: v for k, v in r.items() if k != "reason"}, "pass": False})
64
+ continue
65
+ score = sum(r[axis] for axis in AXES) / (10.0 * len(AXES))
66
+ merged.append({**r, "score": round(score, 4), "pass": passed(r)})
67
+
68
+ scores_path = out_dir / "scores.jsonl"
69
+ scores_path.write_text("\n".join(json.dumps(r) for r in merged) + "\n")
70
+
71
+ ok = [r for r in merged if "error" not in r]
72
+ summary = {
73
+ "judge": "claude-opus-5 (bedrock)",
74
+ "num_scored": len(merged),
75
+ "num_ok": len(ok),
76
+ "num_errors": len(merged) - len(ok),
77
+ "pass_rate": round(sum(r["pass"] for r in ok) / len(ok), 3) if ok else None,
78
+ "mean_score": round(float(np.mean([r["score"] for r in ok])), 3) if ok else None,
79
+ }
80
+ for axis in AXES:
81
+ summary[f"mean_{axis}"] = round(float(np.mean([r[axis] for r in ok])), 3) if ok else None
82
+ for key in GROUP_KEYS:
83
+ groups: dict = {}
84
+ for r in ok:
85
+ groups.setdefault(r[key], []).append(r["score"])
86
+ summary[f"mean_score_by_{key}"] = {k: round(float(np.mean(v)), 3)
87
+ for k, v in sorted(groups.items())}
88
+
89
+ (out_dir / "summary.json").write_text(json.dumps(summary, indent=2))
90
+ print(json.dumps(summary, indent=2))
91
+
92
+
93
+ if __name__ == "__main__":
94
+ main()
bench_t2v_space/usa/results.jsonl ADDED
@@ -0,0 +1,59 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {"id": "statue_of_liberty", "started_at": 1786161065.04787, "status": "ok", "bytes": 7563158, "inference_s": "204.657", "wall_s": 204.7}
2
+ {"id": "golden_gate_bridge", "started_at": 1786161269.720669, "status": "ok", "bytes": 7493197, "inference_s": "204.728", "wall_s": 204.7}
3
+ {"id": "grand_canyon", "started_at": 1786161474.4630237, "status": "ok", "bytes": 7494778, "inference_s": "204.772", "wall_s": 204.8}
4
+ {"id": "mount_rushmore", "started_at": 1786161679.248931, "status": "ok", "bytes": 8552413, "inference_s": "204.697", "wall_s": 204.7}
5
+ {"id": "times_square", "started_at": 1786161883.9616501, "status": "ok", "bytes": 10791387, "inference_s": "204.766", "wall_s": 204.8}
6
+ {"id": "niagara_falls", "started_at": 1786162088.745365, "status": "ok", "bytes": 8148886, "inference_s": "204.711", "wall_s": 204.7}
7
+ {"id": "empire_state_building", "started_at": 1786162293.4707496, "status": "ok", "bytes": 8931753, "inference_s": "204.748", "wall_s": 204.8}
8
+ {"id": "brooklyn_bridge", "started_at": 1786162498.2355442, "status": "ok", "bytes": 13649711, "inference_s": "204.821", "wall_s": 204.8}
9
+ {"id": "hollywood_sign", "started_at": 1786162703.0782042, "status": "ok", "bytes": 6677622, "inference_s": "204.634", "wall_s": 204.6}
10
+ {"id": "alcatraz_island", "started_at": 1786162907.7248933, "status": "ok", "bytes": 6839826, "inference_s": "204.607", "wall_s": 204.6}
11
+ {"id": "yellowstone_national_park", "started_at": 1786163112.343973, "status": "ok", "bytes": 10447099, "inference_s": "204.485", "wall_s": 204.5}
12
+ {"id": "yosemite_national_park", "started_at": 1786163316.8470333, "status": "ok", "bytes": 10055586, "inference_s": "204.722", "wall_s": 204.7}
13
+ {"id": "hoover_dam", "started_at": 1786163521.586486, "status": "ok", "bytes": 6840557, "inference_s": "204.726", "wall_s": 204.7}
14
+ {"id": "space_needle", "started_at": 1786163726.3255637, "status": "ok", "bytes": 8861649, "inference_s": "204.836", "wall_s": 204.9}
15
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+ {"id": "cologne_cathedral", "started_at": 1786155742.6550658, "status": "ok", "bytes": 10446037, "inference_s": "204.625", "wall_s": 204.6}
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+ {"id": "hagia_sophia", "started_at": 1786155947.3014364, "status": "ok", "bytes": 9835684, "inference_s": "204.508", "wall_s": 204.5}
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+ {"id": "blue_mosque", "started_at": 1786156151.8319929, "status": "ok", "bytes": 10945383, "inference_s": "204.522", "wall_s": 204.5}
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+ {"id": "cappadocia", "started_at": 1786156356.3757846, "status": "ok", "bytes": 6655812, "inference_s": "204.631", "wall_s": 204.6}
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+ {"id": "luxor_temple", "started_at": 1786156561.024548, "status": "ok", "bytes": 8073811, "inference_s": "204.817", "wall_s": 204.8}
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+ {"id": "abu_simbel", "started_at": 1786156765.8581717, "status": "ok", "bytes": 8809169, "inference_s": "204.678", "wall_s": 204.7}
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+ {"id": "marrakech_medina", "started_at": 1786156970.5511818, "status": "ok", "bytes": 10237718, "inference_s": "204.734", "wall_s": 204.8}
85
+ {"id": "sahara_desert", "started_at": 1786157175.3036757, "status": "ok", "bytes": 7566733, "inference_s": "204.526", "wall_s": 204.5}
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+ {"id": "mount_kilimanjaro", "started_at": 1786157379.8458123, "status": "ok", "bytes": 7119700, "inference_s": "204.509", "wall_s": 204.5}
87
+ {"id": "serengeti_national_park", "started_at": 1786157584.3680782, "status": "ok", "bytes": 8465284, "inference_s": "204.419", "wall_s": 204.4}
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+ {"id": "zanzibar", "started_at": 1786157788.801241, "status": "ok", "bytes": 8570182, "inference_s": "204.469", "wall_s": 204.5}
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+ {"id": "table_mountain_cape_town", "started_at": 1786157993.2854335, "status": "ok", "bytes": 9139585, "inference_s": "204.628", "wall_s": 204.6}
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+ {"id": "robben_island", "started_at": 1786158197.9329846, "status": "ok", "bytes": 9568118, "inference_s": "204.812", "wall_s": 204.8}
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+ {"id": "bagan_temples", "started_at": 1786158402.7623878, "status": "ok", "bytes": 6212212, "inference_s": "204.661", "wall_s": 204.7}
92
+ {"id": "ha_long_bay", "started_at": 1786158607.4362333, "status": "ok", "bytes": 8307356, "inference_s": "204.631", "wall_s": 204.6}
93
+ {"id": "angkor_thom", "started_at": 1786158812.0815642, "status": "ok", "bytes": 10661859, "inference_s": "204.646", "wall_s": 204.7}
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+ {"id": "borobudur", "started_at": 1786159016.7439947, "status": "ok", "bytes": 8699572, "inference_s": "204.665", "wall_s": 204.7}
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+ {"id": "mount_bromo", "started_at": 1786159221.4224873, "status": "ok", "bytes": 6676498, "inference_s": "204.484", "wall_s": 204.5}
96
+ {"id": "petronas_towers", "started_at": 1786159425.919704, "status": "ok", "bytes": 11168634, "inference_s": "204.649", "wall_s": 204.7}
97
+ {"id": "marina_bay_sands", "started_at": 1786159630.5872703, "status": "ok", "bytes": 8865299, "inference_s": "204.510", "wall_s": 204.5}
98
+ {"id": "milford_sound", "started_at": 1786159835.111812, "status": "ok", "bytes": 13223153, "inference_s": "204.740", "wall_s": 204.8}
99
+ {"id": "sky_tower_auckland", "started_at": 1786160039.8757138, "status": "ok", "bytes": 9584361, "inference_s": "204.837", "wall_s": 204.9}
100
+ {"id": "twelve_apostles_australia", "started_at": 1786160244.7306328, "status": "ok", "bytes": 7180694, "inference_s": "204.671", "wall_s": 204.7}
101
+ {"id": "antelope_canyon", "started_at": 1786160449.4154937, "status": "ok", "bytes": 6843699, "inference_s": "204.576", "wall_s": 204.6}
102
+ {"id": "monument_valley", "started_at": 1786160654.0051894, "status": "ok", "bytes": 6283709, "inference_s": "204.656", "wall_s": 204.7}
103
+ {"id": "banff_national_park", "started_at": 1786160858.6731758, "status": "ok", "bytes": 6830347, "inference_s": "204.677", "wall_s": 204.7}
bench_t2v_space_comprehensive/manifest.json ADDED
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1
+ {
2
+ "dataset": "hand-curated famous cities/places (places.py), one driving-or-walking POV prompt each",
3
+ "num_items": 137,
4
+ "modes": [
5
+ "driving",
6
+ "walking"
7
+ ],
8
+ "sampling": {
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+ "width": 1280,
10
+ "height": 720,
11
+ "num_frames": 189,
12
+ "fps": 24,
13
+ "num_inference_steps": 35,
14
+ "guidance_scale": 6.0,
15
+ "flow_shift": 10.0,
16
+ "seed": 0
17
+ },
18
+ "items": [
19
+ {
20
+ "id": "eiffel_tower___champ_de_mars",
21
+ "place": "Eiffel Tower & Champ de Mars",
22
+ "city": "Paris",
23
+ "country": "France",
24
+ "continent": "Europe",
25
+ "mode": "walking",
26
+ "prompt": "A first-person POV walking through the Eiffel Tower's iron lattice structure rising over the green lawns of the Champ de Mars, with Parisian Haussmann-style buildings lining the surrounding avenues.",
27
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
28
+ },
29
+ {
30
+ "id": "tower_bridge___the_thames",
31
+ "place": "Tower Bridge & the Thames",
32
+ "city": "London",
33
+ "country": "United Kingdom",
34
+ "continent": "Europe",
35
+ "mode": "driving",
36
+ "prompt": "A dashcam POV driving through Tower Bridge's twin Victorian Gothic towers spanning the River Thames, with London's skyline and red double-decker buses nearby.",
37
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
38
+ },
39
+ {
40
+ "id": "sagrada_familia",
41
+ "place": "Sagrada Familia",
42
+ "city": "Barcelona",
43
+ "country": "Spain",
44
+ "continent": "Europe",
45
+ "mode": "walking",
46
+ "prompt": "A first-person POV walking through Gaudi's Sagrada Familia basilica with its tall organic spires rising above the surrounding Barcelona street grid.",
47
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
48
+ },
49
+ {
50
+ "id": "colosseum___roman_forum",
51
+ "place": "Colosseum & Roman Forum",
52
+ "city": "Rome",
53
+ "country": "Italy",
54
+ "continent": "Europe",
55
+ "mode": "walking",
56
+ "prompt": "A first-person POV walking through the ancient Colosseum's tiered stone arches beside the ruined columns of the Roman Forum.",
57
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
58
+ },
59
+ {
60
+ "id": "red_square___st__basil_s_cathedral",
61
+ "place": "Red Square & St. Basil's Cathedral",
62
+ "city": "Moscow",
63
+ "country": "Russia",
64
+ "continent": "Europe",
65
+ "mode": "walking",
66
+ "prompt": "A first-person POV walking through the vast cobblestone expanse of Red Square with St. Basil's Cathedral's colorful onion domes and the red Kremlin walls.",
67
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
68
+ },
69
+ {
70
+ "id": "brandenburg_gate",
71
+ "place": "Brandenburg Gate",
72
+ "city": "Berlin",
73
+ "country": "Germany",
74
+ "continent": "Europe",
75
+ "mode": "walking",
76
+ "prompt": "A first-person POV walking through the neoclassical columns and quadriga statue of the Brandenburg Gate at the end of the wide Unter den Linden boulevard.",
77
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
78
+ },
79
+ {
80
+ "id": "amsterdam_canal_ring",
81
+ "place": "Amsterdam Canal Ring",
82
+ "city": "Amsterdam",
83
+ "country": "Netherlands",
84
+ "continent": "Europe",
85
+ "mode": "walking",
86
+ "prompt": "A first-person POV walking through narrow tilted brick canal houses lining a tree-shaded Amsterdam canal, with bicycles parked along the water and arched stone bridges.",
87
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
88
+ },
89
+ {
90
+ "id": "santorini_caldera_villages",
91
+ "place": "Santorini Caldera Villages",
92
+ "city": "Oia",
93
+ "country": "Greece",
94
+ "continent": "Europe",
95
+ "mode": "walking",
96
+ "prompt": "A first-person POV walking through whitewashed cave houses and blue-domed churches perched along the cliffside of the Santorini caldera overlooking the deep blue Aegean Sea.",
97
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
98
+ },
99
+ {
100
+ "id": "charles_bridge",
101
+ "place": "Charles Bridge",
102
+ "city": "Prague",
103
+ "country": "Czech Republic",
104
+ "continent": "Europe",
105
+ "mode": "walking",
106
+ "prompt": "A first-person POV walking through the Gothic stone arches and baroque statues lining Charles Bridge over the Vltava River with Prague Castle on the hill beyond.",
107
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
108
+ },
109
+ {
110
+ "id": "neuschwanstein_castle_road",
111
+ "place": "Neuschwanstein Castle Road",
112
+ "city": "Schwangau",
113
+ "country": "Germany",
114
+ "continent": "Europe",
115
+ "mode": "driving",
116
+ "prompt": "A dashcam POV driving through a forested mountain road winding up toward the fairy-tale white towers of Neuschwanstein Castle.",
117
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
118
+ },
119
+ {
120
+ "id": "trolltunga_cliff_trail",
121
+ "place": "Trolltunga Cliff Trail",
122
+ "city": "Odda",
123
+ "country": "Norway",
124
+ "continent": "Europe",
125
+ "mode": "walking",
126
+ "prompt": "A first-person POV walking through a rocky hiking trail along a Norwegian fjord leading to the flat Trolltunga cliff jutting out high above the blue water.",
127
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
128
+ },
129
+ {
130
+ "id": "piazza_san_marco",
131
+ "place": "Piazza San Marco",
132
+ "city": "Venice",
133
+ "country": "Italy",
134
+ "continent": "Europe",
135
+ "mode": "walking",
136
+ "prompt": "A first-person POV walking through the open expanse of Piazza San Marco with the Byzantine domes of St Mark's Basilica and its tall bell tower, pigeons scattered across the paving.",
137
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
138
+ },
139
+ {
140
+ "id": "acropolis___parthenon",
141
+ "place": "Acropolis & Parthenon",
142
+ "city": "Athens",
143
+ "country": "Greece",
144
+ "continent": "Europe",
145
+ "mode": "walking",
146
+ "prompt": "A first-person POV walking through the marble columns of the Parthenon atop the rocky Acropolis hill overlooking the sprawling white city of Athens.",
147
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
148
+ },
149
+ {
150
+ "id": "ring_road__golden_circle",
151
+ "place": "Ring Road (Golden Circle)",
152
+ "city": "Thingvellir",
153
+ "country": "Iceland",
154
+ "continent": "Europe",
155
+ "mode": "driving",
156
+ "prompt": "A dashcam POV driving through a lone highway crossing a stark volcanic Icelandic landscape of moss-covered lava fields, distant glaciers, and steaming geothermal vents.",
157
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
158
+ },
159
+ {
160
+ "id": "cliffs_of_moher_coastal_path",
161
+ "place": "Cliffs of Moher Coastal Path",
162
+ "city": "County Clare",
163
+ "country": "Ireland",
164
+ "continent": "Europe",
165
+ "mode": "walking",
166
+ "prompt": "A first-person POV walking through a grassy clifftop trail along the towering Cliffs of Moher with the Atlantic Ocean crashing far below.",
167
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
168
+ },
169
+ {
170
+ "id": "nyhavn_waterfront",
171
+ "place": "Nyhavn Waterfront",
172
+ "city": "Copenhagen",
173
+ "country": "Denmark",
174
+ "continent": "Europe",
175
+ "mode": "walking",
176
+ "prompt": "A first-person POV walking through the brightly colored 17th-century townhouses lining the Nyhavn canal, with wooden sailboats moored along the quay.",
177
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
178
+ },
179
+ {
180
+ "id": "bergen_s_bryggen_wharf",
181
+ "place": "Bergen's Bryggen Wharf",
182
+ "city": "Bergen",
183
+ "country": "Norway",
184
+ "continent": "Europe",
185
+ "mode": "walking",
186
+ "prompt": "A first-person POV walking through the tilted, colorful wooden Hanseatic buildings of Bryggen wharf lining Bergen's harbor beneath green mountains.",
187
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
188
+ },
189
+ {
190
+ "id": "plaza_mayor",
191
+ "place": "Plaza Mayor",
192
+ "city": "Madrid",
193
+ "country": "Spain",
194
+ "continent": "Europe",
195
+ "mode": "walking",
196
+ "prompt": "A first-person POV walking through the arcaded red facades and central equestrian statue of Madrid's grand Plaza Mayor.",
197
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
198
+ },
199
+ {
200
+ "id": "chain_bridge___buda_castle",
201
+ "place": "Chain Bridge & Buda Castle",
202
+ "city": "Budapest",
203
+ "country": "Hungary",
204
+ "continent": "Europe",
205
+ "mode": "walking",
206
+ "prompt": "A first-person POV walking through the Chain Bridge's stone lion statues and iron cables spanning the Danube, with Buda Castle's domed silhouette on the hill above.",
207
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
208
+ },
209
+ {
210
+ "id": "old_town_market_square",
211
+ "place": "Old Town Market Square",
212
+ "city": "Krakow",
213
+ "country": "Poland",
214
+ "continent": "Europe",
215
+ "mode": "walking",
216
+ "prompt": "A first-person POV walking through the Gothic spires of St. Mary's Basilica and the long Renaissance Cloth Hall lining Krakow's medieval market square.",
217
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
218
+ },
219
+ {
220
+ "id": "dubrovnik_city_walls",
221
+ "place": "Dubrovnik City Walls",
222
+ "city": "Dubrovnik",
223
+ "country": "Croatia",
224
+ "continent": "Europe",
225
+ "mode": "walking",
226
+ "prompt": "A first-person POV walking through the orange-tiled rooftops of Dubrovnik's old town seen from the top of its massive stone city walls, with the Adriatic Sea beyond.",
227
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
228
+ },
229
+ {
230
+ "id": "lucerne_s_chapel_bridge",
231
+ "place": "Lucerne's Chapel Bridge",
232
+ "city": "Lucerne",
233
+ "country": "Switzerland",
234
+ "continent": "Europe",
235
+ "mode": "walking",
236
+ "prompt": "A first-person POV walking through the medieval wooden Chapel Bridge with its stone water tower crossing the Reuss River, snow-capped Alps visible in the distance.",
237
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
238
+ },
239
+ {
240
+ "id": "ringstrasse___schonbrunn_palace",
241
+ "place": "Ringstrasse & Schonbrunn Palace",
242
+ "city": "Vienna",
243
+ "country": "Austria",
244
+ "continent": "Europe",
245
+ "mode": "driving",
246
+ "prompt": "A dashcam POV driving through the grand yellow facade and manicured gardens of Schonbrunn Palace along Vienna's Ringstrasse boulevard.",
247
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
248
+ },
249
+ {
250
+ "id": "belem_tower___tagus_riverfront",
251
+ "place": "Belem Tower & Tagus Riverfront",
252
+ "city": "Lisbon",
253
+ "country": "Portugal",
254
+ "continent": "Europe",
255
+ "mode": "walking",
256
+ "prompt": "A first-person POV walking through the fortified stone turrets of Belem Tower on the banks of the Tagus River, with Lisbon's pastel-colored hillside buildings behind it.",
257
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
258
+ },
259
+ {
260
+ "id": "grand_place",
261
+ "place": "Grand Place",
262
+ "city": "Brussels",
263
+ "country": "Belgium",
264
+ "continent": "Europe",
265
+ "mode": "walking",
266
+ "prompt": "A first-person POV walking through the ornate gilded guild-house facades and Gothic town hall spire surrounding Brussels' Grand Place.",
267
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
268
+ },
269
+ {
270
+ "id": "gamla_stan_old_town",
271
+ "place": "Gamla Stan Old Town",
272
+ "city": "Stockholm",
273
+ "country": "Sweden",
274
+ "continent": "Europe",
275
+ "mode": "walking",
276
+ "prompt": "A first-person POV walking through the narrow cobblestone lanes and colorful medieval buildings of Stockholm's Gamla Stan island, water visible at the street ends.",
277
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
278
+ },
279
+ {
280
+ "id": "senate_square",
281
+ "place": "Senate Square",
282
+ "city": "Helsinki",
283
+ "country": "Finland",
284
+ "continent": "Europe",
285
+ "mode": "walking",
286
+ "prompt": "A first-person POV walking through the white neoclassical Helsinki Cathedral atop its broad staircase overlooking the granite-paved Senate Square.",
287
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
288
+ },
289
+ {
290
+ "id": "lake_bled_island_road",
291
+ "place": "Lake Bled Island Road",
292
+ "city": "Bled",
293
+ "country": "Slovenia",
294
+ "continent": "Europe",
295
+ "mode": "driving",
296
+ "prompt": "A dashcam POV driving through a lakeside road circling turquoise Lake Bled with its tiny island church and a cliffside castle rising above the far shore.",
297
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
298
+ },
299
+ {
300
+ "id": "transfagarasan_highway",
301
+ "place": "Transfagarasan Highway",
302
+ "city": "Fagaras Mountains",
303
+ "country": "Romania",
304
+ "continent": "Europe",
305
+ "mode": "driving",
306
+ "prompt": "A dashcam POV driving through a dramatic switchback mountain highway climbing through the Fagaras range with hairpin turns and jagged Carpathian peaks.",
307
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
308
+ },
309
+ {
310
+ "id": "rila_monastery_grounds",
311
+ "place": "Rila Monastery Grounds",
312
+ "city": "Rila",
313
+ "country": "Bulgaria",
314
+ "continent": "Europe",
315
+ "mode": "walking",
316
+ "prompt": "A first-person POV walking through the striped red-and-black arcades and colorful frescoed courtyard of Rila Monastery, forested mountains rising behind it.",
317
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
318
+ },
319
+ {
320
+ "id": "tbilisi_old_town",
321
+ "place": "Tbilisi Old Town",
322
+ "city": "Tbilisi",
323
+ "country": "Georgia",
324
+ "continent": "Europe",
325
+ "mode": "walking",
326
+ "prompt": "A first-person POV walking through the leaning wooden-balconied houses and sulfur bathhouse domes of Tbilisi's old town beneath a hilltop fortress.",
327
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
328
+ },
329
+ {
330
+ "id": "royal_mile",
331
+ "place": "Royal Mile",
332
+ "city": "Edinburgh",
333
+ "country": "United Kingdom",
334
+ "continent": "Europe",
335
+ "mode": "walking",
336
+ "prompt": "A first-person POV walking through the cobbled Royal Mile climbing between tall stone tenements toward the ramparts of Edinburgh Castle on its volcanic crag.",
337
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
338
+ },
339
+ {
340
+ "id": "valletta_grand_harbour",
341
+ "place": "Valletta Grand Harbour",
342
+ "city": "Valletta",
343
+ "country": "Malta",
344
+ "continent": "Europe",
345
+ "mode": "walking",
346
+ "prompt": "A first-person POV walking through the honey-colored limestone bastions and baroque church domes of Valletta overlooking the deep blue Grand Harbour.",
347
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
348
+ },
349
+ {
350
+ "id": "monte_carlo_harbour",
351
+ "place": "Monte Carlo Harbour",
352
+ "city": "Monaco",
353
+ "country": "Monaco",
354
+ "continent": "Europe",
355
+ "mode": "driving",
356
+ "prompt": "A dashcam POV driving through luxury yachts lining Monte Carlo's harbour beneath the Rock of Monaco's palace and dense white high-rises climbing the hillside.",
357
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
358
+ },
359
+ {
360
+ "id": "luxembourg_old_town_bridges",
361
+ "place": "Luxembourg Old Town Bridges",
362
+ "city": "Luxembourg City",
363
+ "country": "Luxembourg",
364
+ "continent": "Europe",
365
+ "mode": "walking",
366
+ "prompt": "A first-person POV walking through tall stone viaducts and fortress ramparts spanning the deep green Petrusse valley below Luxembourg City's old town.",
367
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
368
+ },
369
+ {
370
+ "id": "shibuya_crossing",
371
+ "place": "Shibuya Crossing",
372
+ "city": "Tokyo",
373
+ "country": "Japan",
374
+ "continent": "Asia",
375
+ "mode": "walking",
376
+ "prompt": "A first-person POV walking through the famous scramble crossing at Shibuya with dense crowds of pedestrians and giant illuminated video billboards overhead.",
377
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
378
+ },
379
+ {
380
+ "id": "great_wall_at_mutianyu",
381
+ "place": "Great Wall at Mutianyu",
382
+ "city": "Beijing",
383
+ "country": "China",
384
+ "continent": "Asia",
385
+ "mode": "walking",
386
+ "prompt": "A first-person POV walking through the Great Wall's stone ramparts and watchtowers snaking along a forested mountain ridge.",
387
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
388
+ },
389
+ {
390
+ "id": "marina_bay_skyline",
391
+ "place": "Marina Bay Skyline",
392
+ "city": "Singapore",
393
+ "country": "Singapore",
394
+ "continent": "Asia",
395
+ "mode": "driving",
396
+ "prompt": "A dashcam POV driving through the three connected towers of Marina Bay Sands with its rooftop skypark overlooking Singapore's futuristic waterfront skyline.",
397
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
398
+ },
399
+ {
400
+ "id": "grand_bazaar_alleys",
401
+ "place": "Grand Bazaar Alleys",
402
+ "city": "Istanbul",
403
+ "country": "Turkey",
404
+ "continent": "Asia",
405
+ "mode": "walking",
406
+ "prompt": "A first-person POV walking through the vaulted, lantern-lit stone corridors of Istanbul's Grand Bazaar lined with carpet, spice, and lantern stalls.",
407
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
408
+ },
409
+ {
410
+ "id": "burj_khalifa___downtown_dubai",
411
+ "place": "Burj Khalifa & Downtown Dubai",
412
+ "city": "Dubai",
413
+ "country": "United Arab Emirates",
414
+ "continent": "Asia",
415
+ "mode": "driving",
416
+ "prompt": "A dashcam POV driving through the needle-thin Burj Khalifa towering over Dubai's glass skyscrapers and wide multi-lane highways.",
417
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
418
+ },
419
+ {
420
+ "id": "taj_mahal___reflecting_pool",
421
+ "place": "Taj Mahal & Reflecting Pool",
422
+ "city": "Agra",
423
+ "country": "India",
424
+ "continent": "Asia",
425
+ "mode": "walking",
426
+ "prompt": "A first-person POV walking through the white marble domes and minarets of the Taj Mahal mirrored in its long reflecting pool with manicured gardens.",
427
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
428
+ },
429
+ {
430
+ "id": "ha_long_bay_waterway",
431
+ "place": "Ha Long Bay Waterway",
432
+ "city": "Ha Long",
433
+ "country": "Vietnam",
434
+ "continent": "Asia",
435
+ "mode": "driving",
436
+ "prompt": "A dashcam POV driving through limestone karst islands rising out of the emerald waters of Ha Long Bay with traditional wooden junk boats.",
437
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
438
+ },
439
+ {
440
+ "id": "grand_palace_complex",
441
+ "place": "Grand Palace Complex",
442
+ "city": "Bangkok",
443
+ "country": "Thailand",
444
+ "continent": "Asia",
445
+ "mode": "walking",
446
+ "prompt": "A first-person POV walking through the ornate gold-tiled spires and mosaic-covered walls of Bangkok's Grand Palace complex.",
447
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
448
+ },
449
+ {
450
+ "id": "gangnam_boulevard",
451
+ "place": "Gangnam Boulevard",
452
+ "city": "Seoul",
453
+ "country": "South Korea",
454
+ "continent": "Asia",
455
+ "mode": "driving",
456
+ "prompt": "A dashcam POV driving through a wide multi-lane Gangnam boulevard lined with glass skyscrapers, neon signage, and dense traffic.",
457
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
458
+ },
459
+ {
460
+ "id": "fushimi_inari_torii_path",
461
+ "place": "Fushimi Inari Torii Path",
462
+ "city": "Kyoto",
463
+ "country": "Japan",
464
+ "continent": "Asia",
465
+ "mode": "walking",
466
+ "prompt": "A first-person POV walking through thousands of vermilion torii gates forming a tunnel-like path winding up the forested slope of Mount Inari.",
467
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
468
+ },
469
+ {
470
+ "id": "petra_s_siq_canyon",
471
+ "place": "Petra's Siq Canyon",
472
+ "city": "Petra",
473
+ "country": "Jordan",
474
+ "continent": "Asia",
475
+ "mode": "walking",
476
+ "prompt": "A first-person POV walking through a narrow sandstone canyon with towering pink-orange rock walls leading to the carved facade of the Petra Treasury.",
477
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
478
+ },
479
+ {
480
+ "id": "nathan_road",
481
+ "place": "Nathan Road",
482
+ "city": "Hong Kong",
483
+ "country": "China",
484
+ "continent": "Asia",
485
+ "mode": "driving",
486
+ "prompt": "A dashcam POV driving through the dense neon signage and double-decker buses of Hong Kong's Nathan Road beneath a wall of high-rise apartment towers.",
487
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
488
+ },
489
+ {
490
+ "id": "angkor_wat_causeway",
491
+ "place": "Angkor Wat Causeway",
492
+ "city": "Siem Reap",
493
+ "country": "Cambodia",
494
+ "continent": "Asia",
495
+ "mode": "walking",
496
+ "prompt": "A first-person POV walking through the long stone causeway leading to Angkor Wat's five lotus-bud towers reflected in the surrounding moat.",
497
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
498
+ },
499
+ {
500
+ "id": "jerusalem_s_old_city_walls",
501
+ "place": "Jerusalem's Old City Walls",
502
+ "city": "Jerusalem",
503
+ "country": "Israel",
504
+ "continent": "Asia",
505
+ "mode": "walking",
506
+ "prompt": "A first-person POV walking through the golden Dome of the Rock and ancient limestone walls of Jerusalem's Old City, narrow stone alleys threading between them.",
507
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
508
+ },
509
+ {
510
+ "id": "borobudur_temple_terraces",
511
+ "place": "Borobudur Temple Terraces",
512
+ "city": "Magelang",
513
+ "country": "Indonesia",
514
+ "continent": "Asia",
515
+ "mode": "walking",
516
+ "prompt": "A first-person POV walking through the tiered stone stupas and carved relief terraces of Borobudur temple rising against a backdrop of volcanic mountains.",
517
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
518
+ },
519
+ {
520
+ "id": "petronas_towers_plaza",
521
+ "place": "Petronas Towers Plaza",
522
+ "city": "Kuala Lumpur",
523
+ "country": "Malaysia",
524
+ "continent": "Asia",
525
+ "mode": "driving",
526
+ "prompt": "A dashcam POV driving through the twin stainless-steel spires of the Petronas Towers linked by a skybridge, rising above KLCC park and the city skyline.",
527
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
528
+ },
529
+ {
530
+ "id": "jeepney_streets_of_manila",
531
+ "place": "Jeepney Streets of Manila",
532
+ "city": "Manila",
533
+ "country": "Philippines",
534
+ "continent": "Asia",
535
+ "mode": "driving",
536
+ "prompt": "A dashcam POV driving through brightly decorated jeepneys weaving through Manila's crowded streets past colonial-era buildings and vendor stalls.",
537
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
538
+ },
539
+ {
540
+ "id": "pudong_skyline___the_bund",
541
+ "place": "Pudong Skyline & the Bund",
542
+ "city": "Shanghai",
543
+ "country": "China",
544
+ "continent": "Asia",
545
+ "mode": "walking",
546
+ "prompt": "A first-person POV walking through the futuristic Oriental Pearl Tower and glass skyscrapers of Pudong seen across the Huangpu River from the Bund's colonial waterfront.",
547
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
548
+ },
549
+ {
550
+ "id": "registan_square",
551
+ "place": "Registan Square",
552
+ "city": "Samarkand",
553
+ "country": "Uzbekistan",
554
+ "continent": "Asia",
555
+ "mode": "walking",
556
+ "prompt": "A first-person POV walking through the three turquoise-tiled madrasas with towering arched portals framing Samarkand's Registan square.",
557
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
558
+ },
559
+ {
560
+ "id": "karakoram_highway",
561
+ "place": "Karakoram Highway",
562
+ "city": "Hunza Valley",
563
+ "country": "Pakistan",
564
+ "continent": "Asia",
565
+ "mode": "driving",
566
+ "prompt": "A dashcam POV driving through a high mountain highway winding through the Hunza Valley with terraced fields and jagged snow-capped Karakoram peaks.",
567
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
568
+ },
569
+ {
570
+ "id": "kathmandu_durbar_square",
571
+ "place": "Kathmandu Durbar Square",
572
+ "city": "Kathmandu",
573
+ "country": "Nepal",
574
+ "continent": "Asia",
575
+ "mode": "walking",
576
+ "prompt": "A first-person POV walking through the pagoda-roofed temples and carved wooden palace facades of Kathmandu's Durbar Square, Himalayan peaks faint on the horizon.",
577
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
578
+ },
579
+ {
580
+ "id": "sigiriya_rock_fortress",
581
+ "place": "Sigiriya Rock Fortress",
582
+ "city": "Sigiriya",
583
+ "country": "Sri Lanka",
584
+ "continent": "Asia",
585
+ "mode": "walking",
586
+ "prompt": "A first-person POV walking through the sheer red rock column of Sigiriya rising out of flat jungle, ancient frescoes and a stone stairway spiraling up its face.",
587
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
588
+ },
589
+ {
590
+ "id": "paro_taktsang__tiger_s_nest",
591
+ "place": "Paro Taktsang (Tiger's Nest)",
592
+ "city": "Paro",
593
+ "country": "Bhutan",
594
+ "continent": "Asia",
595
+ "mode": "walking",
596
+ "prompt": "A first-person POV walking through the white monastery of Paro Taktsang clinging to a sheer cliff face high above a pine-forested Himalayan gorge.",
597
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
598
+ },
599
+ {
600
+ "id": "bagan_temple_plain",
601
+ "place": "Bagan Temple Plain",
602
+ "city": "Bagan",
603
+ "country": "Myanmar",
604
+ "continent": "Asia",
605
+ "mode": "walking",
606
+ "prompt": "A first-person POV walking through thousands of ancient brick temples and stupas scattered across the flat Bagan plain in the early morning haze.",
607
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
608
+ },
609
+ {
610
+ "id": "luang_prabang_night_market_street",
611
+ "place": "Luang Prabang Night Market Street",
612
+ "city": "Luang Prabang",
613
+ "country": "Laos",
614
+ "continent": "Asia",
615
+ "mode": "walking",
616
+ "prompt": "A first-person POV walking through saffron-robed monk statues and gilded temple roofs along Luang Prabang's lantern-lit street between the Mekong and Nam Khan rivers.",
617
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
618
+ },
619
+ {
620
+ "id": "taipei_101___xinyi_district",
621
+ "place": "Taipei 101 & Xinyi District",
622
+ "city": "Taipei",
623
+ "country": "Taiwan",
624
+ "continent": "Asia",
625
+ "mode": "driving",
626
+ "prompt": "A dashcam POV driving through the tiered, bamboo-inspired Taipei 101 skyscraper rising above the glass towers and dense traffic of the Xinyi district.",
627
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
628
+ },
629
+ {
630
+ "id": "gobi_desert_steppe_road",
631
+ "place": "Gobi Desert Steppe Road",
632
+ "city": "Gobi Desert",
633
+ "country": "Mongolia",
634
+ "continent": "Asia",
635
+ "mode": "driving",
636
+ "prompt": "A dashcam POV driving through a faint dirt track crossing the vast, empty Gobi Desert steppe, distant rocky outcrops breaking an otherwise flat golden horizon.",
637
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
638
+ },
639
+ {
640
+ "id": "charyn_canyon_road",
641
+ "place": "Charyn Canyon Road",
642
+ "city": "Almaty Region",
643
+ "country": "Kazakhstan",
644
+ "continent": "Asia",
645
+ "mode": "driving",
646
+ "prompt": "A dashcam POV driving through a dirt road winding between the red sandstone spires of Charyn Canyon's 'Valley of Castles' formations.",
647
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
648
+ },
649
+ {
650
+ "id": "doha_corniche",
651
+ "place": "Doha Corniche",
652
+ "city": "Doha",
653
+ "country": "Qatar",
654
+ "continent": "Asia",
655
+ "mode": "walking",
656
+ "prompt": "A first-person POV walking through a curving waterfront promenade along Doha's Corniche with the futuristic skyline of West Bay towers rising across the bay.",
657
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
658
+ },
659
+ {
660
+ "id": "naqsh_e_jahan_square",
661
+ "place": "Naqsh-e Jahan Square",
662
+ "city": "Isfahan",
663
+ "country": "Iran",
664
+ "continent": "Asia",
665
+ "mode": "walking",
666
+ "prompt": "A first-person POV walking through the vast tiled expanse of Naqsh-e Jahan Square framed by turquoise-domed mosques and a grand arched bazaar entrance.",
667
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
668
+ },
669
+ {
670
+ "id": "baku_old_city___flame_towers",
671
+ "place": "Baku Old City & Flame Towers",
672
+ "city": "Baku",
673
+ "country": "Azerbaijan",
674
+ "continent": "Asia",
675
+ "mode": "walking",
676
+ "prompt": "A first-person POV walking through the medieval stone walls of Baku's Old City with the curved glass Flame Towers glowing above the modern skyline behind them.",
677
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
678
+ },
679
+ {
680
+ "id": "times_square",
681
+ "place": "Times Square",
682
+ "city": "New York City",
683
+ "country": "United States",
684
+ "continent": "North America",
685
+ "mode": "walking",
686
+ "prompt": "A first-person POV walking through the towering illuminated billboards and dense crowds of Times Square surrounded by New York's yellow taxis and skyscrapers.",
687
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
688
+ },
689
+ {
690
+ "id": "golden_gate_bridge",
691
+ "place": "Golden Gate Bridge",
692
+ "city": "San Francisco",
693
+ "country": "United States",
694
+ "continent": "North America",
695
+ "mode": "driving",
696
+ "prompt": "A dashcam POV driving through the Golden Gate Bridge's rust-orange suspension towers spanning the bay with San Francisco's hills and fog in the background.",
697
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
698
+ },
699
+ {
700
+ "id": "grand_canyon_south_rim_road",
701
+ "place": "Grand Canyon South Rim Road",
702
+ "city": "Grand Canyon",
703
+ "country": "United States",
704
+ "continent": "North America",
705
+ "mode": "driving",
706
+ "prompt": "A dashcam POV driving through a winding road along the Grand Canyon's South Rim with layered red-orange rock walls dropping away into the vast canyon.",
707
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
708
+ },
709
+ {
710
+ "id": "hollywood_boulevard",
711
+ "place": "Hollywood Boulevard",
712
+ "city": "Los Angeles",
713
+ "country": "United States",
714
+ "continent": "North America",
715
+ "mode": "walking",
716
+ "prompt": "A first-person POV walking through Hollywood Boulevard's Walk of Fame stars embedded in the sidewalk beneath palm trees and neon theater marquees.",
717
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
718
+ },
719
+ {
720
+ "id": "cn_tower___downtown_toronto",
721
+ "place": "CN Tower & Downtown Toronto",
722
+ "city": "Toronto",
723
+ "country": "Canada",
724
+ "continent": "North America",
725
+ "mode": "driving",
726
+ "prompt": "A dashcam POV driving through the slender CN Tower rising above Toronto's glass downtown skyline near the shore of Lake Ontario.",
727
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
728
+ },
729
+ {
730
+ "id": "zocalo___metropolitan_cathedral",
731
+ "place": "Zocalo & Metropolitan Cathedral",
732
+ "city": "Mexico City",
733
+ "country": "Mexico",
734
+ "continent": "North America",
735
+ "mode": "walking",
736
+ "prompt": "A first-person POV walking through the vast paved Zocalo plaza with the twin bell towers of the Metropolitan Cathedral and the Mexican flag at its center.",
737
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
738
+ },
739
+ {
740
+ "id": "bow_valley_parkway",
741
+ "place": "Bow Valley Parkway",
742
+ "city": "Banff",
743
+ "country": "Canada",
744
+ "continent": "North America",
745
+ "mode": "driving",
746
+ "prompt": "A dashcam POV driving through a two-lane mountain road winding through pine forest with snow-capped Canadian Rockies peaks rising on either side.",
747
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
748
+ },
749
+ {
750
+ "id": "french_quarter_streets",
751
+ "place": "French Quarter Streets",
752
+ "city": "New Orleans",
753
+ "country": "United States",
754
+ "continent": "North America",
755
+ "mode": "walking",
756
+ "prompt": "A first-person POV walking through wrought-iron balconies and pastel Creole townhouses lining a narrow French Quarter street with jazz music drifting from open doorways.",
757
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
758
+ },
759
+ {
760
+ "id": "route_66_desert_highway",
761
+ "place": "Route 66 Desert Highway",
762
+ "city": "Arizona",
763
+ "country": "United States",
764
+ "continent": "North America",
765
+ "mode": "driving",
766
+ "prompt": "A dashcam POV driving through a straight two-lane Route 66 highway crossing a red-rock desert landscape with distant mesas on the horizon.",
767
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
768
+ },
769
+ {
770
+ "id": "chichen_itza_pyramid_grounds",
771
+ "place": "Chichen Itza Pyramid Grounds",
772
+ "city": "Yucatan",
773
+ "country": "Mexico",
774
+ "continent": "North America",
775
+ "mode": "walking",
776
+ "prompt": "A first-person POV walking through the stepped stone pyramid of Kukulkan rising from the grassy grounds of Chichen Itza, jungle ringing the site.",
777
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
778
+ },
779
+ {
780
+ "id": "millennium_park___the_bean",
781
+ "place": "Millennium Park & the Bean",
782
+ "city": "Chicago",
783
+ "country": "United States",
784
+ "continent": "North America",
785
+ "mode": "walking",
786
+ "prompt": "A first-person POV walking through the reflective silver curves of Cloud Gate ('the Bean') in Millennium Park with Chicago's skyscraper skyline behind it.",
787
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
788
+ },
789
+ {
790
+ "id": "icefields_parkway",
791
+ "place": "Icefields Parkway",
792
+ "city": "Jasper",
793
+ "country": "Canada",
794
+ "continent": "North America",
795
+ "mode": "driving",
796
+ "prompt": "A dashcam POV driving through a remote highway threading between glaciers and turquoise lakes along the Icefields Parkway in the Canadian Rockies.",
797
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
798
+ },
799
+ {
800
+ "id": "havana_s_malecon",
801
+ "place": "Havana's Malecon",
802
+ "city": "Havana",
803
+ "country": "Cuba",
804
+ "continent": "North America",
805
+ "mode": "driving",
806
+ "prompt": "A dashcam POV driving through vintage pastel-colored American cars parked along Havana's seaside Malecon promenade with crumbling colonial facades behind.",
807
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
808
+ },
809
+ {
810
+ "id": "antigua_s_cobblestone_streets",
811
+ "place": "Antigua's Cobblestone Streets",
812
+ "city": "Antigua",
813
+ "country": "Guatemala",
814
+ "continent": "North America",
815
+ "mode": "walking",
816
+ "prompt": "A first-person POV walking through colorful colonial facades and cobblestone streets in Antigua with the Volcan de Agua looming in the background.",
817
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
818
+ },
819
+ {
820
+ "id": "old_san_juan_streets",
821
+ "place": "Old San Juan Streets",
822
+ "city": "San Juan",
823
+ "country": "Puerto Rico",
824
+ "continent": "North America",
825
+ "mode": "walking",
826
+ "prompt": "A first-person POV walking through blue cobblestone streets lined with brightly painted colonial buildings inside the fortified walls of Old San Juan.",
827
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
828
+ },
829
+ {
830
+ "id": "las_vegas_strip",
831
+ "place": "Las Vegas Strip",
832
+ "city": "Las Vegas",
833
+ "country": "United States",
834
+ "continent": "North America",
835
+ "mode": "driving",
836
+ "prompt": "A dashcam POV driving through the neon-lit casino resorts and towering signage lining the Las Vegas Strip against the night desert sky.",
837
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
838
+ },
839
+ {
840
+ "id": "niagara_falls_overlook",
841
+ "place": "Niagara Falls Overlook",
842
+ "city": "Niagara Falls",
843
+ "country": "Canada",
844
+ "continent": "North America",
845
+ "mode": "walking",
846
+ "prompt": "A first-person POV walking through the massive curved curtain of Niagara Falls's Horseshoe Falls with mist rising and a viewing promenade along the gorge edge.",
847
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
848
+ },
849
+ {
850
+ "id": "yellowstone_grand_loop_road",
851
+ "place": "Yellowstone Grand Loop Road",
852
+ "city": "Yellowstone",
853
+ "country": "United States",
854
+ "continent": "North America",
855
+ "mode": "driving",
856
+ "prompt": "A dashcam POV driving through a two-lane park road passing steaming geyser basins and bison herds against a backdrop of pine forest and distant mountains.",
857
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
858
+ },
859
+ {
860
+ "id": "ocean_drive___south_beach",
861
+ "place": "Ocean Drive & South Beach",
862
+ "city": "Miami",
863
+ "country": "United States",
864
+ "continent": "North America",
865
+ "mode": "driving",
866
+ "prompt": "A dashcam POV driving through pastel Art Deco hotel facades and palm trees lining Miami's Ocean Drive with the beach and turquoise water beyond.",
867
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
868
+ },
869
+ {
870
+ "id": "stanley_park_seawall",
871
+ "place": "Stanley Park Seawall",
872
+ "city": "Vancouver",
873
+ "country": "Canada",
874
+ "continent": "North America",
875
+ "mode": "walking",
876
+ "prompt": "A first-person POV walking through a waterfront path along Stanley Park's seawall with tall evergreen forest on one side and Vancouver's glass skyline across the harbor.",
877
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
878
+ },
879
+ {
880
+ "id": "arenal_volcano_road",
881
+ "place": "Arenal Volcano Road",
882
+ "city": "La Fortuna",
883
+ "country": "Costa Rica",
884
+ "continent": "North America",
885
+ "mode": "driving",
886
+ "prompt": "A dashcam POV driving through a jungle-lined road through Costa Rican rainforest with the near-perfect cone of Arenal Volcano rising ahead.",
887
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
888
+ },
889
+ {
890
+ "id": "casco_viejo_streets",
891
+ "place": "Casco Viejo Streets",
892
+ "city": "Panama City",
893
+ "country": "Panama",
894
+ "continent": "North America",
895
+ "mode": "walking",
896
+ "prompt": "A first-person POV walking through crumbling colonial facades and wrought-iron balconies in Panama City's Casco Viejo, with the modern skyline visible across the bay.",
897
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
898
+ },
899
+ {
900
+ "id": "dunn_s_river_falls",
901
+ "place": "Dunn's River Falls",
902
+ "city": "Ocho Rios",
903
+ "country": "Jamaica",
904
+ "continent": "North America",
905
+ "mode": "walking",
906
+ "prompt": "A first-person POV walking through terraced limestone cascades of Dunn's River Falls tumbling through lush jungle down to the Caribbean shoreline.",
907
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
908
+ },
909
+ {
910
+ "id": "zona_colonial",
911
+ "place": "Zona Colonial",
912
+ "city": "Santo Domingo",
913
+ "country": "Dominican Republic",
914
+ "continent": "North America",
915
+ "mode": "walking",
916
+ "prompt": "A first-person POV walking through the oldest cobblestone streets in the Americas lined with colonial stone cathedrals and balconied townhouses in Santo Domingo's Zona Colonial.",
917
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
918
+ },
919
+ {
920
+ "id": "quebec_city_old_town",
921
+ "place": "Quebec City Old Town",
922
+ "city": "Quebec City",
923
+ "country": "Canada",
924
+ "continent": "North America",
925
+ "mode": "walking",
926
+ "prompt": "A first-person POV walking through the steep cobbled streets and turreted Chateau Frontenac of Quebec City's walled old town overlooking the St. Lawrence River.",
927
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
928
+ },
929
+ {
930
+ "id": "christ_the_redeemer___rio_skyline",
931
+ "place": "Christ the Redeemer & Rio Skyline",
932
+ "city": "Rio de Janeiro",
933
+ "country": "Brazil",
934
+ "continent": "South America",
935
+ "mode": "driving",
936
+ "prompt": "A dashcam POV driving through the Christ the Redeemer statue atop Corcovado mountain overlooking Rio de Janeiro's beaches, favelas, and Sugarloaf Mountain.",
937
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
938
+ },
939
+ {
940
+ "id": "machu_picchu_terraces",
941
+ "place": "Machu Picchu Terraces",
942
+ "city": "Machu Picchu",
943
+ "country": "Peru",
944
+ "continent": "South America",
945
+ "mode": "walking",
946
+ "prompt": "A first-person POV walking through the stone terraces and ruins of Machu Picchu perched on a green mountain ridge with steep Andean peaks and mist in the background.",
947
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
948
+ },
949
+ {
950
+ "id": "caminito_street",
951
+ "place": "Caminito Street",
952
+ "city": "Buenos Aires",
953
+ "country": "Argentina",
954
+ "continent": "South America",
955
+ "mode": "walking",
956
+ "prompt": "A first-person POV walking through the brightly painted corrugated-metal houses lining Caminito street in La Boca, with tango dancers and market stalls.",
957
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
958
+ },
959
+ {
960
+ "id": "salar_de_uyuni_salt_flat_road",
961
+ "place": "Salar de Uyuni Salt Flat Road",
962
+ "city": "Uyuni",
963
+ "country": "Bolivia",
964
+ "continent": "South America",
965
+ "mode": "driving",
966
+ "prompt": "A dashcam POV driving through a dirt track crossing the blinding white expanse of the Uyuni salt flat stretching to the horizon under a huge open sky.",
967
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
968
+ },
969
+ {
970
+ "id": "cartagena_s_walled_old_town",
971
+ "place": "Cartagena's Walled Old Town",
972
+ "city": "Cartagena",
973
+ "country": "Colombia",
974
+ "continent": "South America",
975
+ "mode": "walking",
976
+ "prompt": "A first-person POV walking through brightly colored colonial balconies and bougainvillea draped over the narrow streets inside Cartagena's old walled city.",
977
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
978
+ },
979
+ {
980
+ "id": "torres_del_paine_road",
981
+ "place": "Torres del Paine Road",
982
+ "city": "Patagonia",
983
+ "country": "Chile",
984
+ "continent": "South America",
985
+ "mode": "driving",
986
+ "prompt": "A dashcam POV driving through a gravel road crossing windswept Patagonian steppe with the granite spires of Torres del Paine rising ahead.",
987
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
988
+ },
989
+ {
990
+ "id": "iguazu_falls_walkways",
991
+ "place": "Iguazu Falls Walkways",
992
+ "city": "Iguazu",
993
+ "country": "Argentina",
994
+ "continent": "South America",
995
+ "mode": "walking",
996
+ "prompt": "A first-person POV walking through metal walkways threading along the edge of the thundering, mist-shrouded cascades of Iguazu Falls through the rainforest.",
997
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
998
+ },
999
+ {
1000
+ "id": "quito_s_old_town_plazas",
1001
+ "place": "Quito's Old Town Plazas",
1002
+ "city": "Quito",
1003
+ "country": "Ecuador",
1004
+ "continent": "South America",
1005
+ "mode": "walking",
1006
+ "prompt": "A first-person POV walking through the whitewashed colonial churches and cobblestone plazas of Quito's old town set against Andean volcanoes.",
1007
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1008
+ },
1009
+ {
1010
+ "id": "angel_falls_overlook_trail",
1011
+ "place": "Angel Falls Overlook Trail",
1012
+ "city": "Canaima",
1013
+ "country": "Venezuela",
1014
+ "continent": "South America",
1015
+ "mode": "walking",
1016
+ "prompt": "A first-person POV walking through a jungle trail leading to a viewpoint of Angel Falls, the world's tallest waterfall, plunging off a sheer tepui cliff into the rainforest.",
1017
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1018
+ },
1019
+ {
1020
+ "id": "colonia_del_sacramento_streets",
1021
+ "place": "Colonia del Sacramento Streets",
1022
+ "city": "Colonia del Sacramento",
1023
+ "country": "Uruguay",
1024
+ "continent": "South America",
1025
+ "mode": "walking",
1026
+ "prompt": "A first-person POV walking through cobblestone streets lined with faded colonial Portuguese buildings and a lighthouse in Colonia del Sacramento's old quarter.",
1027
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1028
+ },
1029
+ {
1030
+ "id": "jesuit_missions_of_trinidad",
1031
+ "place": "Jesuit Missions of Trinidad",
1032
+ "city": "Trinidad",
1033
+ "country": "Paraguay",
1034
+ "continent": "South America",
1035
+ "mode": "walking",
1036
+ "prompt": "A first-person POV walking through the red sandstone ruins of the Jesuit mission of Trinidad, carved arches and columns standing amid open grassland.",
1037
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1038
+ },
1039
+ {
1040
+ "id": "amazon_river_at_manaus",
1041
+ "place": "Amazon River at Manaus",
1042
+ "city": "Manaus",
1043
+ "country": "Brazil",
1044
+ "continent": "South America",
1045
+ "mode": "driving",
1046
+ "prompt": "A dashcam POV driving through a wide brown stretch of the Amazon River with dense rainforest canopy along the banks and wooden riverboats passing by.",
1047
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1048
+ },
1049
+ {
1050
+ "id": "rainbow_mountain_trail",
1051
+ "place": "Rainbow Mountain Trail",
1052
+ "city": "Vinicunca",
1053
+ "country": "Peru",
1054
+ "continent": "South America",
1055
+ "mode": "walking",
1056
+ "prompt": "A first-person POV walking through a high-altitude trail climbing toward Vinicunca's striped mineral slopes in bands of red, gold, and turquoise.",
1057
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1058
+ },
1059
+ {
1060
+ "id": "rapa_nui_moai_coastline",
1061
+ "place": "Rapa Nui Moai Coastline",
1062
+ "city": "Easter Island",
1063
+ "country": "Chile",
1064
+ "continent": "South America",
1065
+ "mode": "walking",
1066
+ "prompt": "A first-person POV walking through a row of massive stone Moai statues standing along the grassy volcanic coastline of Easter Island, the Pacific Ocean behind them.",
1067
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1068
+ },
1069
+ {
1070
+ "id": "cocora_valley_wax_palms",
1071
+ "place": "Cocora Valley Wax Palms",
1072
+ "city": "Salento",
1073
+ "country": "Colombia",
1074
+ "continent": "South America",
1075
+ "mode": "walking",
1076
+ "prompt": "A first-person POV walking through towering, impossibly slender wax palm trees rising out of the misty green Cocora Valley with Andean ridgelines behind.",
1077
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1078
+ },
1079
+ {
1080
+ "id": "otavalo_market_streets",
1081
+ "place": "Otavalo Market Streets",
1082
+ "city": "Otavalo",
1083
+ "country": "Ecuador",
1084
+ "continent": "South America",
1085
+ "mode": "walking",
1086
+ "prompt": "A first-person POV walking through rows of colorful woven textiles and market stalls filling the streets of Otavalo beneath a backdrop of Andean volcanoes.",
1087
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1088
+ },
1089
+ {
1090
+ "id": "pyramids_of_giza",
1091
+ "place": "Pyramids of Giza",
1092
+ "city": "Giza",
1093
+ "country": "Egypt",
1094
+ "continent": "Africa",
1095
+ "mode": "walking",
1096
+ "prompt": "A first-person POV walking through the Great Pyramids of Giza and the Sphinx rising from the desert sand at the edge of the city.",
1097
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1098
+ },
1099
+ {
1100
+ "id": "table_mountain_road",
1101
+ "place": "Table Mountain Road",
1102
+ "city": "Cape Town",
1103
+ "country": "South Africa",
1104
+ "continent": "Africa",
1105
+ "mode": "driving",
1106
+ "prompt": "A dashcam POV driving through a coastal road curving along the base of Table Mountain's flat-topped cliff face with the Atlantic Ocean beside it.",
1107
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1108
+ },
1109
+ {
1110
+ "id": "marrakech_medina_souks",
1111
+ "place": "Marrakech Medina Souks",
1112
+ "city": "Marrakech",
1113
+ "country": "Morocco",
1114
+ "continent": "Africa",
1115
+ "mode": "walking",
1116
+ "prompt": "A first-person POV walking through the narrow, arch-covered alleys of the Marrakech medina lined with dyed textiles, lanterns, and spice stalls.",
1117
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1118
+ },
1119
+ {
1120
+ "id": "serengeti_safari_track",
1121
+ "place": "Serengeti Safari Track",
1122
+ "city": "Serengeti",
1123
+ "country": "Tanzania",
1124
+ "continent": "Africa",
1125
+ "mode": "driving",
1126
+ "prompt": "A dashcam POV driving through a dirt safari track crossing the golden grassland of the Serengeti with acacia trees and distant herds on the horizon.",
1127
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1128
+ },
1129
+ {
1130
+ "id": "victoria_falls_rainforest_path",
1131
+ "place": "Victoria Falls Rainforest Path",
1132
+ "city": "Livingstone",
1133
+ "country": "Zambia",
1134
+ "continent": "Africa",
1135
+ "mode": "walking",
1136
+ "prompt": "A first-person POV walking through a mist-soaked rainforest trail facing the massive curtain of Victoria Falls plunging into the gorge below.",
1137
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1138
+ },
1139
+ {
1140
+ "id": "sahara_dunes_track",
1141
+ "place": "Sahara Dunes Track",
1142
+ "city": "Merzouga",
1143
+ "country": "Morocco",
1144
+ "continent": "Africa",
1145
+ "mode": "driving",
1146
+ "prompt": "A dashcam POV driving through a faint tire track winding between towering orange sand dunes of the Sahara desert, camel caravans in the distance.",
1147
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1148
+ },
1149
+ {
1150
+ "id": "lalibela_s_rock_hewn_churches",
1151
+ "place": "Lalibela's Rock-Hewn Churches",
1152
+ "city": "Lalibela",
1153
+ "country": "Ethiopia",
1154
+ "continent": "Africa",
1155
+ "mode": "walking",
1156
+ "prompt": "A first-person POV walking through the monolithic rock-hewn churches of Lalibela carved directly into the reddish volcanic ground, narrow trenches connecting them.",
1157
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1158
+ },
1159
+ {
1160
+ "id": "stone_town_alleys",
1161
+ "place": "Stone Town Alleys",
1162
+ "city": "Zanzibar City",
1163
+ "country": "Tanzania",
1164
+ "continent": "Africa",
1165
+ "mode": "walking",
1166
+ "prompt": "A first-person POV walking through the narrow winding alleys of Stone Town lined with carved wooden doors and coral-stone buildings.",
1167
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1168
+ },
1169
+ {
1170
+ "id": "garden_route_coastal_highway",
1171
+ "place": "Garden Route Coastal Highway",
1172
+ "city": "Western Cape",
1173
+ "country": "South Africa",
1174
+ "continent": "Africa",
1175
+ "mode": "driving",
1176
+ "prompt": "A dashcam POV driving through a cliffside coastal highway along South Africa's Garden Route with dense green forest on one side and ocean cliffs on the other.",
1177
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1178
+ },
1179
+ {
1180
+ "id": "sossusvlei_dune_road",
1181
+ "place": "Sossusvlei Dune Road",
1182
+ "city": "Sossusvlei",
1183
+ "country": "Namibia",
1184
+ "continent": "Africa",
1185
+ "mode": "driving",
1186
+ "prompt": "A dashcam POV driving through a red dirt road crossing the Namib desert toward the towering orange sand dunes of Sossusvlei and the white clay pan of Deadvlei.",
1187
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1188
+ },
1189
+ {
1190
+ "id": "okavango_delta_waterways",
1191
+ "place": "Okavango Delta Waterways",
1192
+ "city": "Okavango Delta",
1193
+ "country": "Botswana",
1194
+ "continent": "Africa",
1195
+ "mode": "driving",
1196
+ "prompt": "A dashcam POV driving through a maze of reed-lined channels through the flooded Okavango Delta, papyrus grass and distant elephants along the waterway.",
1197
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1198
+ },
1199
+ {
1200
+ "id": "maasai_mara_savanna_track",
1201
+ "place": "Maasai Mara Savanna Track",
1202
+ "city": "Maasai Mara",
1203
+ "country": "Kenya",
1204
+ "continent": "Africa",
1205
+ "mode": "driving",
1206
+ "prompt": "A dashcam POV driving through a dirt safari track crossing the open Maasai Mara savanna, acacia trees dotting the grassland and wildebeest herds in the distance.",
1207
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1208
+ },
1209
+ {
1210
+ "id": "volcanoes_national_park_trail",
1211
+ "place": "Volcanoes National Park Trail",
1212
+ "city": "Musanze",
1213
+ "country": "Rwanda",
1214
+ "continent": "Africa",
1215
+ "mode": "walking",
1216
+ "prompt": "A first-person POV walking through a misty forest trail climbing the slopes of Rwanda's Virunga volcanoes through dense bamboo and rainforest.",
1217
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1218
+ },
1219
+ {
1220
+ "id": "avenue_of_the_baobabs",
1221
+ "place": "Avenue of the Baobabs",
1222
+ "city": "Morondava",
1223
+ "country": "Madagascar",
1224
+ "continent": "Africa",
1225
+ "mode": "driving",
1226
+ "prompt": "A dashcam POV driving through a dirt road lined with towering, bottle-shaped baobab trees silhouetted against the sky in western Madagascar.",
1227
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1228
+ },
1229
+ {
1230
+ "id": "sidi_bou_said_streets",
1231
+ "place": "Sidi Bou Said Streets",
1232
+ "city": "Sidi Bou Said",
1233
+ "country": "Tunisia",
1234
+ "continent": "Africa",
1235
+ "mode": "walking",
1236
+ "prompt": "A first-person POV walking through whitewashed houses with bright blue doors and shutters lining the steep cobbled streets of Sidi Bou Said above the Mediterranean.",
1237
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1238
+ },
1239
+ {
1240
+ "id": "goree_island_streets",
1241
+ "place": "Goree Island Streets",
1242
+ "city": "Goree Island",
1243
+ "country": "Senegal",
1244
+ "continent": "Africa",
1245
+ "mode": "walking",
1246
+ "prompt": "A first-person POV walking through narrow sandy lanes between weathered ochre and pink colonial buildings on Goree Island, the Atlantic Ocean visible at the street's end.",
1247
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1248
+ },
1249
+ {
1250
+ "id": "cape_coast_castle_grounds",
1251
+ "place": "Cape Coast Castle Grounds",
1252
+ "city": "Cape Coast",
1253
+ "country": "Ghana",
1254
+ "continent": "Africa",
1255
+ "mode": "walking",
1256
+ "prompt": "A first-person POV walking through the whitewashed ramparts and courtyards of Cape Coast Castle overlooking fishing boats and the Gulf of Guinea.",
1257
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1258
+ },
1259
+ {
1260
+ "id": "third_mainland_bridge",
1261
+ "place": "Third Mainland Bridge",
1262
+ "city": "Lagos",
1263
+ "country": "Nigeria",
1264
+ "continent": "Africa",
1265
+ "mode": "driving",
1266
+ "prompt": "A dashcam POV driving through a long causeway bridge crossing Lagos Lagoon with the dense high-rise skyline of Lagos Island visible ahead.",
1267
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1268
+ },
1269
+ {
1270
+ "id": "tassili_n_ajjer_plateau_track",
1271
+ "place": "Tassili n'Ajjer Plateau Track",
1272
+ "city": "Djanet",
1273
+ "country": "Algeria",
1274
+ "continent": "Africa",
1275
+ "mode": "driving",
1276
+ "prompt": "A dashcam POV driving through a faint desert track winding among the eroded sandstone rock forests of the Tassili n'Ajjer plateau in the Sahara.",
1277
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1278
+ },
1279
+ {
1280
+ "id": "sydney_opera_house___harbour",
1281
+ "place": "Sydney Opera House & Harbour",
1282
+ "city": "Sydney",
1283
+ "country": "Australia",
1284
+ "continent": "Oceania",
1285
+ "mode": "walking",
1286
+ "prompt": "A first-person POV walking through the white sail-shaped shells of the Sydney Opera House on the harbour with the steel arch of the Sydney Harbour Bridge behind it.",
1287
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1288
+ },
1289
+ {
1290
+ "id": "great_ocean_road",
1291
+ "place": "Great Ocean Road",
1292
+ "city": "Victoria",
1293
+ "country": "Australia",
1294
+ "continent": "Oceania",
1295
+ "mode": "driving",
1296
+ "prompt": "A dashcam POV driving through a coastal cliffside highway along Australia's Great Ocean Road with the limestone Twelve Apostles sea stacks visible offshore.",
1297
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1298
+ },
1299
+ {
1300
+ "id": "queenstown_lakefront",
1301
+ "place": "Queenstown Lakefront",
1302
+ "city": "Queenstown",
1303
+ "country": "New Zealand",
1304
+ "continent": "Oceania",
1305
+ "mode": "walking",
1306
+ "prompt": "A first-person POV walking through a lakefront promenade in Queenstown with turquoise water and the jagged snow-dusted Remarkables mountain range behind it.",
1307
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1308
+ },
1309
+ {
1310
+ "id": "uluru_base_walk",
1311
+ "place": "Uluru Base Walk",
1312
+ "city": "Uluru",
1313
+ "country": "Australia",
1314
+ "continent": "Oceania",
1315
+ "mode": "walking",
1316
+ "prompt": "A first-person POV walking through a red dirt trail circling the base of the massive sandstone monolith Uluru, its rust-colored surface glowing against the desert.",
1317
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1318
+ },
1319
+ {
1320
+ "id": "milford_sound_fjord_road",
1321
+ "place": "Milford Sound Fjord Road",
1322
+ "city": "Fiordland",
1323
+ "country": "New Zealand",
1324
+ "continent": "Oceania",
1325
+ "mode": "driving",
1326
+ "prompt": "A dashcam POV driving through a narrow road threading through steep rainforested cliffs toward Milford Sound's dark fjord waters and waterfalls.",
1327
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1328
+ },
1329
+ {
1330
+ "id": "coral_coast_highway",
1331
+ "place": "Coral Coast Highway",
1332
+ "city": "Coral Coast",
1333
+ "country": "Fiji",
1334
+ "continent": "Oceania",
1335
+ "mode": "driving",
1336
+ "prompt": "A dashcam POV driving through a palm-lined coastal highway along Fiji's Coral Coast with turquoise lagoon waters visible through gaps in the trees.",
1337
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1338
+ },
1339
+ {
1340
+ "id": "bora_bora_overwater_bungalow_path",
1341
+ "place": "Bora Bora Overwater Bungalow Path",
1342
+ "city": "Bora Bora",
1343
+ "country": "French Polynesia",
1344
+ "continent": "Oceania",
1345
+ "mode": "walking",
1346
+ "prompt": "A first-person POV walking through a wooden overwater walkway connecting thatched-roof bungalows above the turquoise lagoon of Bora Bora, a green volcanic peak rising behind.",
1347
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1348
+ },
1349
+ {
1350
+ "id": "bondi_beach_coastal_walk",
1351
+ "place": "Bondi Beach Coastal Walk",
1352
+ "city": "Sydney",
1353
+ "country": "Australia",
1354
+ "continent": "Oceania",
1355
+ "mode": "walking",
1356
+ "prompt": "A first-person POV walking through a clifftop coastal footpath above Bondi Beach's golden sand and surf, sandstone cliffs and the open Pacific stretching to the horizon.",
1357
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1358
+ },
1359
+ {
1360
+ "id": "three_sisters_lookout_trail",
1361
+ "place": "Three Sisters Lookout Trail",
1362
+ "city": "Blue Mountains",
1363
+ "country": "Australia",
1364
+ "continent": "Oceania",
1365
+ "mode": "walking",
1366
+ "prompt": "A first-person POV walking through a forested clifftop trail in the Blue Mountains facing the three sandstone Three Sisters rock formations wrapped in blue-tinged haze.",
1367
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1368
+ },
1369
+ {
1370
+ "id": "hobbiton_movie_set_path",
1371
+ "place": "Hobbiton Movie Set Path",
1372
+ "city": "Matamata",
1373
+ "country": "New Zealand",
1374
+ "continent": "Oceania",
1375
+ "mode": "walking",
1376
+ "prompt": "A first-person POV walking through a grassy path winding past round hobbit-hole doors set into rolling green hillsides at the Hobbiton film set.",
1377
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1378
+ },
1379
+ {
1380
+ "id": "franz_josef_glacier_road",
1381
+ "place": "Franz Josef Glacier Road",
1382
+ "city": "Franz Josef",
1383
+ "country": "New Zealand",
1384
+ "continent": "Oceania",
1385
+ "mode": "driving",
1386
+ "prompt": "A dashcam POV driving through a valley road running through temperate rainforest toward the blue-white tongue of the Franz Josef Glacier descending from the Southern Alps.",
1387
+ "negative_prompt": "blurry, distorted, low quality, jittery, deformed, wrong landmark, generic unrecognizable location"
1388
+ }
1389
+ ]
1390
+ }
bench_t2v_space_comprehensive/results.jsonl ADDED
@@ -0,0 +1,137 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {"id": "eiffel_tower___champ_de_mars", "started_at": 1785266464.4780333, "status": "ok", "bytes": 14079555, "inference_s": "201.159", "wall_s": 201.2}
2
+ {"id": "tower_bridge___the_thames", "started_at": 1785266665.6622431, "status": "ok", "bytes": 7974610, "inference_s": "201.418", "wall_s": 201.4}
3
+ {"id": "sagrada_familia", "started_at": 1785266867.0987186, "status": "ok", "bytes": 10121710, "inference_s": "201.222", "wall_s": 201.2}
4
+ {"id": "colosseum___roman_forum", "started_at": 1785267081.7862575, "status": "ok", "bytes": 8804272, "inference_s": "200.783", "wall_s": 200.8}
5
+ {"id": "red_square___st__basil_s_cathedral", "started_at": 1785267282.585454, "status": "ok", "bytes": 11011496, "inference_s": "200.943", "wall_s": 201.0}
6
+ {"id": "brandenburg_gate", "started_at": 1785267483.5474632, "status": "ok", "bytes": 7664554, "inference_s": "201.195", "wall_s": 201.2}
7
+ {"id": "amsterdam_canal_ring", "started_at": 1785267684.757735, "status": "ok", "bytes": 13211634, "inference_s": "201.018", "wall_s": 201.0}
8
+ {"id": "santorini_caldera_villages", "started_at": 1785267885.7993898, "status": "ok", "bytes": 10513171, "inference_s": "201.929", "wall_s": 201.9}
9
+ {"id": "charles_bridge", "started_at": 1785268087.7476113, "status": "ok", "bytes": 8858720, "inference_s": "201.795", "wall_s": 201.8}
10
+ {"id": "neuschwanstein_castle_road", "started_at": 1785268289.5643306, "status": "ok", "bytes": 9755646, "inference_s": "201.230", "wall_s": 201.2}
11
+ {"id": "trolltunga_cliff_trail", "started_at": 1785268490.8123834, "status": "ok", "bytes": 8552914, "inference_s": "201.253", "wall_s": 201.3}
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+ {"id": "piazza_san_marco", "started_at": 1785268692.0856776, "status": "ok", "bytes": 9640326, "inference_s": "201.312", "wall_s": 201.3}
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+ {"id": "acropolis___parthenon", "started_at": 1785268893.4156938, "status": "ok", "bytes": 11118758, "inference_s": "201.217", "wall_s": 201.2}
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+ {"id": "ring_road__golden_circle", "started_at": 1785269094.6516867, "status": "ok", "bytes": 7003943, "inference_s": "201.238", "wall_s": 201.3}
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+ {"id": "cliffs_of_moher_coastal_path", "started_at": 1785269295.9031394, "status": "ok", "bytes": 7094928, "inference_s": "201.525", "wall_s": 201.5}
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+ {"id": "nyhavn_waterfront", "started_at": 1785269497.444583, "status": "ok", "bytes": 13306144, "inference_s": "201.477", "wall_s": 201.5}
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+ {"id": "bergen_s_bryggen_wharf", "started_at": 1785269698.9474125, "status": "ok", "bytes": 11701512, "inference_s": "201.512", "wall_s": 201.5}
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+ {"id": "plaza_mayor", "started_at": 1785269900.483803, "status": "ok", "bytes": 9789684, "inference_s": "201.638", "wall_s": 201.7}
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+ {"id": "chain_bridge___buda_castle", "started_at": 1785270102.1405444, "status": "ok", "bytes": 9140264, "inference_s": "201.398", "wall_s": 201.4}
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+ {"id": "dubrovnik_city_walls", "started_at": 1785270505.1580012, "status": "ok", "bytes": 10152160, "inference_s": "201.347", "wall_s": 201.4}
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+ {"id": "lucerne_s_chapel_bridge", "started_at": 1785270706.525702, "status": "ok", "bytes": 8745291, "inference_s": "201.837", "wall_s": 201.9}
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+ {"id": "ringstrasse___schonbrunn_palace", "started_at": 1785270908.3797607, "status": "ok", "bytes": 11323721, "inference_s": "201.475", "wall_s": 201.5}
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+ {"id": "belem_tower___tagus_riverfront", "started_at": 1785271109.8760467, "status": "ok", "bytes": 10434677, "inference_s": "200.601", "wall_s": 200.6}
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+ {"id": "grand_place", "started_at": 1785271310.4958615, "status": "ok", "bytes": 12663009, "inference_s": "202.049", "wall_s": 202.1}
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+ {"id": "gamla_stan_old_town", "started_at": 1785271512.5670536, "status": "ok", "bytes": 11041228, "inference_s": "201.640", "wall_s": 201.7}
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+ {"id": "senate_square", "started_at": 1785271714.2261896, "status": "ok", "bytes": 7628762, "inference_s": "200.810", "wall_s": 200.8}
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+ {"id": "lake_bled_island_road", "started_at": 1785271915.0532293, "status": "ok", "bytes": 7268499, "inference_s": "201.582", "wall_s": 201.6}
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+ {"id": "transfagarasan_highway", "started_at": 1785272116.6559188, "status": "ok", "bytes": 6805105, "inference_s": "201.599", "wall_s": 201.6}
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+ {"id": "tbilisi_old_town", "started_at": 1785272519.6085749, "status": "ok", "bytes": 10553804, "inference_s": "201.418", "wall_s": 201.4}
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+ {"id": "royal_mile", "started_at": 1785272721.0447838, "status": "ok", "bytes": 10193836, "inference_s": "201.673", "wall_s": 201.7}
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+ {"id": "valletta_grand_harbour", "started_at": 1785272922.737876, "status": "ok", "bytes": 8853699, "inference_s": "201.400", "wall_s": 201.4}
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+ {"id": "monte_carlo_harbour", "started_at": 1785273124.154314, "status": "ok", "bytes": 9179244, "inference_s": "200.809", "wall_s": 200.8}
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+ {"id": "luxembourg_old_town_bridges", "started_at": 1785273324.9810796, "status": "ok", "bytes": 12249331, "inference_s": "201.847", "wall_s": 201.9}
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+ {"id": "shibuya_crossing", "started_at": 1785273526.8510385, "status": "ok", "bytes": 10217565, "inference_s": "201.672", "wall_s": 201.7}
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+ {"id": "marina_bay_skyline", "started_at": 1785273929.426913, "status": "ok", "bytes": 9098016, "inference_s": "201.799", "wall_s": 201.8}
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+ {"id": "grand_bazaar_alleys", "started_at": 1785274131.244224, "status": "ok", "bytes": 11845126, "inference_s": "201.571", "wall_s": 201.6}
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+ {"id": "burj_khalifa___downtown_dubai", "started_at": 1785274332.8335962, "status": "ok", "bytes": 9146087, "inference_s": "201.121", "wall_s": 201.1}
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+ {"id": "taj_mahal___reflecting_pool", "started_at": 1785274533.9729545, "status": "ok", "bytes": 9470129, "inference_s": "201.556", "wall_s": 201.6}
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+ {"id": "ha_long_bay_waterway", "started_at": 1785274735.5472503, "status": "ok", "bytes": 7828218, "inference_s": "201.516", "wall_s": 201.5}
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+ {"id": "grand_palace_complex", "started_at": 1785274937.0781195, "status": "ok", "bytes": 12490861, "inference_s": "201.239", "wall_s": 201.3}
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+ {"id": "gangnam_boulevard", "started_at": 1785275138.3379502, "status": "ok", "bytes": 11754777, "inference_s": "201.167", "wall_s": 201.2}
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+ {"id": "fushimi_inari_torii_path", "started_at": 1785275339.527631, "status": "ok", "bytes": 12170120, "inference_s": "201.790", "wall_s": 201.8}
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+ {"id": "petra_s_siq_canyon", "started_at": 1785275541.336124, "status": "ok", "bytes": 6879522, "inference_s": "201.398", "wall_s": 201.4}
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+ {"id": "nathan_road", "started_at": 1785275742.7517424, "status": "ok", "bytes": 11180418, "inference_s": "200.731", "wall_s": 200.8}
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+ {"id": "angkor_wat_causeway", "started_at": 1785275943.5029607, "status": "ok", "bytes": 9173655, "inference_s": "201.665", "wall_s": 201.7}
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+ {"id": "jerusalem_s_old_city_walls", "started_at": 1785276145.1855414, "status": "ok", "bytes": 8492045, "inference_s": "201.447", "wall_s": 201.5}
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+ {"id": "borobudur_temple_terraces", "started_at": 1785276346.6505134, "status": "ok", "bytes": 8819375, "inference_s": "201.009", "wall_s": 201.0}
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+ {"id": "petronas_towers_plaza", "started_at": 1785276547.676569, "status": "ok", "bytes": 10868070, "inference_s": "201.891", "wall_s": 201.9}
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+ {"id": "pudong_skyline___the_bund", "started_at": 1785276951.327236, "status": "ok", "bytes": 10388072, "inference_s": "201.112", "wall_s": 201.1}
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+ {"id": "registan_square", "started_at": 1785277152.460113, "status": "ok", "bytes": 9324624, "inference_s": "201.472", "wall_s": 201.5}
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+ {"id": "karakoram_highway", "started_at": 1785277353.9502223, "status": "ok", "bytes": 6992006, "inference_s": "201.583", "wall_s": 201.6}
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+ {"id": "kathmandu_durbar_square", "started_at": 1785277555.5485709, "status": "ok", "bytes": 8088868, "inference_s": "201.276", "wall_s": 201.3}
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+ {"id": "sigiriya_rock_fortress", "started_at": 1785277756.8406267, "status": "ok", "bytes": 9124450, "inference_s": "200.978", "wall_s": 201.0}
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+ {"id": "paro_taktsang__tiger_s_nest", "started_at": 1785277957.836694, "status": "ok", "bytes": 8962297, "inference_s": "201.709", "wall_s": 201.7}
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+ {"id": "bagan_temple_plain", "started_at": 1785278159.5657527, "status": "ok", "bytes": 6926385, "inference_s": "201.435", "wall_s": 201.4}
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+ {"id": "luang_prabang_night_market_street", "started_at": 1785278361.0145648, "status": "ok", "bytes": 11888977, "inference_s": "200.984", "wall_s": 201.0}
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+ {"id": "taipei_101___xinyi_district", "started_at": 1785278562.0210502, "status": "ok", "bytes": 9070423, "inference_s": "201.831", "wall_s": 201.8}
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+ {"id": "gobi_desert_steppe_road", "started_at": 1785278763.8695269, "status": "ok", "bytes": 8910311, "inference_s": "201.225", "wall_s": 201.2}
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+ {"id": "charyn_canyon_road", "started_at": 1785278965.1114876, "status": "ok", "bytes": 7092160, "inference_s": "200.699", "wall_s": 200.7}
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+ {"id": "doha_corniche", "started_at": 1785279165.8226924, "status": "ok", "bytes": 9611134, "inference_s": "201.670", "wall_s": 201.7}
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+ {"id": "naqsh_e_jahan_square", "started_at": 1785279367.5086472, "status": "ok", "bytes": 14507836, "inference_s": "201.512", "wall_s": 201.5}
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+ {"id": "baku_old_city___flame_towers", "started_at": 1785279569.0453951, "status": "ok", "bytes": 7403160, "inference_s": "201.014", "wall_s": 201.0}
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+ {"id": "times_square", "started_at": 1785279770.0739574, "status": "ok", "bytes": 10757840, "inference_s": "201.701", "wall_s": 201.7}
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+ {"id": "golden_gate_bridge", "started_at": 1785279971.796226, "status": "ok", "bytes": 7327413, "inference_s": "201.728", "wall_s": 201.7}
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+ {"id": "grand_canyon_south_rim_road", "started_at": 1785280173.5370736, "status": "ok", "bytes": 7675991, "inference_s": "201.254", "wall_s": 201.3}
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+ {"id": "hollywood_boulevard", "started_at": 1785280374.8112862, "status": "ok", "bytes": 12160488, "inference_s": "201.118", "wall_s": 201.1}
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+ {"id": "cn_tower___downtown_toronto", "started_at": 1785280575.951021, "status": "ok", "bytes": 7543388, "inference_s": "201.701", "wall_s": 201.7}
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+ {"id": "zocalo___metropolitan_cathedral", "started_at": 1785280777.6703093, "status": "ok", "bytes": 6173731, "inference_s": "201.429", "wall_s": 201.4}
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+ {"id": "bow_valley_parkway", "started_at": 1785280979.1138308, "status": "ok", "bytes": 7401619, "inference_s": "200.820", "wall_s": 200.8}
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+ {"id": "french_quarter_streets", "started_at": 1785281179.9474683, "status": "ok", "bytes": 10302898, "inference_s": "201.919", "wall_s": 201.9}
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+ {"id": "route_66_desert_highway", "started_at": 1785281381.8836997, "status": "ok", "bytes": 6083682, "inference_s": "201.493", "wall_s": 201.5}
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+ {"id": "chichen_itza_pyramid_grounds", "started_at": 1785281583.3885193, "status": "ok", "bytes": 8333149, "inference_s": "200.944", "wall_s": 201.0}
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+ {"id": "millennium_park___the_bean", "started_at": 1785281784.3464377, "status": "ok", "bytes": 10020199, "inference_s": "201.760", "wall_s": 201.8}
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+ {"id": "icefields_parkway", "started_at": 1785281986.1229749, "status": "ok", "bytes": 6583915, "inference_s": "201.527", "wall_s": 201.5}
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+ {"id": "havana_s_malecon", "started_at": 1785282187.6653523, "status": "ok", "bytes": 8327769, "inference_s": "201.174", "wall_s": 201.2}
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+ {"id": "antigua_s_cobblestone_streets", "started_at": 1785282388.854531, "status": "ok", "bytes": 9263135, "inference_s": "201.392", "wall_s": 201.4}
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+ {"id": "old_san_juan_streets", "started_at": 1785282590.26303, "status": "ok", "bytes": 10091405, "inference_s": "201.617", "wall_s": 201.6}
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+ {"id": "las_vegas_strip", "started_at": 1785282791.8960772, "status": "ok", "bytes": 9558546, "inference_s": "201.268", "wall_s": 201.3}
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+ {"id": "niagara_falls_overlook", "started_at": 1785282993.1796439, "status": "ok", "bytes": 9020975, "inference_s": "200.999", "wall_s": 201.0}
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+ {"id": "yellowstone_grand_loop_road", "started_at": 1785283194.1966174, "status": "ok", "bytes": 7333128, "inference_s": "201.630", "wall_s": 201.6}
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+ {"id": "ocean_drive___south_beach", "started_at": 1785283395.8385603, "status": "ok", "bytes": 9066089, "inference_s": "201.611", "wall_s": 201.6}
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+ {"id": "stanley_park_seawall", "started_at": 1785283597.4673696, "status": "ok", "bytes": 9722421, "inference_s": "200.968", "wall_s": 201.0}
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+ {"id": "arenal_volcano_road", "started_at": 1785283798.453171, "status": "ok", "bytes": 8023953, "inference_s": "201.757", "wall_s": 201.8}
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+ {"id": "casco_viejo_streets", "started_at": 1785284000.223339, "status": "ok", "bytes": 9766096, "inference_s": "201.579", "wall_s": 201.6}
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+ {"id": "dunn_s_river_falls", "started_at": 1785284201.8207648, "status": "ok", "bytes": 10762670, "inference_s": "200.924", "wall_s": 200.9}
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+ {"id": "zona_colonial", "started_at": 1785284402.7601943, "status": "ok", "bytes": 9377655, "inference_s": "201.760", "wall_s": 201.8}
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+ {"id": "quebec_city_old_town", "started_at": 1785284604.538704, "status": "ok", "bytes": 11059286, "inference_s": "201.568", "wall_s": 201.6}
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+ {"id": "christ_the_redeemer___rio_skyline", "started_at": 1785284806.1324875, "status": "ok", "bytes": 8893808, "inference_s": "201.204", "wall_s": 201.2}
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+ {"id": "machu_picchu_terraces", "started_at": 1785285007.353173, "status": "ok", "bytes": 8781885, "inference_s": "201.285", "wall_s": 201.3}
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+ {"id": "caminito_street", "started_at": 1785285208.6527352, "status": "ok", "bytes": 8820308, "inference_s": "201.733", "wall_s": 201.7}
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+ {"id": "salar_de_uyuni_salt_flat_road", "started_at": 1785285410.3998873, "status": "ok", "bytes": 7245279, "inference_s": "201.107", "wall_s": 201.1}
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+ {"id": "cartagena_s_walled_old_town", "started_at": 1785285611.5206203, "status": "ok", "bytes": 14124294, "inference_s": "201.302", "wall_s": 201.3}
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+ {"id": "torres_del_paine_road", "started_at": 1785285812.8465245, "status": "ok", "bytes": 9525639, "inference_s": "201.560", "wall_s": 201.6}
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+ {"id": "iguazu_falls_walkways", "started_at": 1785286014.424008, "status": "ok", "bytes": 11143489, "inference_s": "201.615", "wall_s": 201.6}
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+ {"id": "quito_s_old_town_plazas", "started_at": 1785286216.0574136, "status": "ok", "bytes": 8311937, "inference_s": "200.986", "wall_s": 201.0}
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+ {"id": "angel_falls_overlook_trail", "started_at": 1785286417.056427, "status": "ok", "bytes": 9785550, "inference_s": "201.889", "wall_s": 201.9}
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+ {"id": "colonia_del_sacramento_streets", "started_at": 1785286618.9616437, "status": "ok", "bytes": 10557430, "inference_s": "201.475", "wall_s": 201.5}
102
+ {"id": "jesuit_missions_of_trinidad", "started_at": 1785286820.4542823, "status": "ok", "bytes": 8646169, "inference_s": "200.810", "wall_s": 200.8}
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+ {"id": "amazon_river_at_manaus", "started_at": 1785287021.2801187, "status": "ok", "bytes": 5100768, "inference_s": "201.633", "wall_s": 201.6}
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+ {"id": "rainbow_mountain_trail", "started_at": 1785287222.9235888, "status": "ok", "bytes": 8886115, "inference_s": "201.530", "wall_s": 201.5}
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+ {"id": "rapa_nui_moai_coastline", "started_at": 1785287424.4711592, "status": "ok", "bytes": 8336763, "inference_s": "201.176", "wall_s": 201.2}
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+ {"id": "cocora_valley_wax_palms", "started_at": 1785287625.6601799, "status": "ok", "bytes": 9466974, "inference_s": "201.555", "wall_s": 201.6}
107
+ {"id": "otavalo_market_streets", "started_at": 1785287827.2317595, "status": "ok", "bytes": 9134437, "inference_s": "201.617", "wall_s": 201.6}
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+ {"id": "pyramids_of_giza", "started_at": 1785288028.864994, "status": "ok", "bytes": 9573637, "inference_s": "201.095", "wall_s": 201.1}
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+ {"id": "table_mountain_road", "started_at": 1785288229.9759283, "status": "ok", "bytes": 6744711, "inference_s": "200.914", "wall_s": 200.9}
110
+ {"id": "marrakech_medina_souks", "started_at": 1785288430.904767, "status": "ok", "bytes": 11118935, "inference_s": "201.820", "wall_s": 201.8}
111
+ {"id": "serengeti_safari_track", "started_at": 1785288632.7459855, "status": "ok", "bytes": 9942884, "inference_s": "201.294", "wall_s": 201.3}
112
+ {"id": "victoria_falls_rainforest_path", "started_at": 1785288834.057049, "status": "ok", "bytes": 7061736, "inference_s": "200.661", "wall_s": 200.7}
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+ {"id": "sahara_dunes_track", "started_at": 1785289034.731873, "status": "ok", "bytes": 6368233, "inference_s": "201.623", "wall_s": 201.6}
114
+ {"id": "lalibela_s_rock_hewn_churches", "started_at": 1785289236.3676877, "status": "ok", "bytes": 7237230, "inference_s": "201.624", "wall_s": 201.6}
115
+ {"id": "stone_town_alleys", "started_at": 1785289438.0053017, "status": "ok", "bytes": 8678259, "inference_s": "200.914", "wall_s": 200.9}
116
+ {"id": "garden_route_coastal_highway", "started_at": 1785289638.934534, "status": "ok", "bytes": 6986461, "inference_s": "201.709", "wall_s": 201.7}
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+ {"id": "sossusvlei_dune_road", "started_at": 1785289840.662059, "status": "ok", "bytes": 9274529, "inference_s": "201.434", "wall_s": 201.4}
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+ {"id": "okavango_delta_waterways", "started_at": 1785290042.1116316, "status": "ok", "bytes": 8542112, "inference_s": "200.955", "wall_s": 201.0}
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+ {"id": "maasai_mara_savanna_track", "started_at": 1785290243.0811586, "status": "ok", "bytes": 9489985, "inference_s": "201.237", "wall_s": 201.3}
120
+ {"id": "volcanoes_national_park_trail", "started_at": 1785290444.3353128, "status": "ok", "bytes": 9186391, "inference_s": "201.537", "wall_s": 201.6}
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+ {"id": "avenue_of_the_baobabs", "started_at": 1785290645.8899007, "status": "ok", "bytes": 8447707, "inference_s": "201.363", "wall_s": 201.4}
122
+ {"id": "sidi_bou_said_streets", "started_at": 1785290847.268436, "status": "ok", "bytes": 8383087, "inference_s": "200.928", "wall_s": 200.9}
123
+ {"id": "goree_island_streets", "started_at": 1785291048.2123034, "status": "ok", "bytes": 8251655, "inference_s": "201.774", "wall_s": 201.8}
124
+ {"id": "cape_coast_castle_grounds", "started_at": 1785291250.0031052, "status": "ok", "bytes": 7188528, "inference_s": "201.488", "wall_s": 201.5}
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+ {"id": "third_mainland_bridge", "started_at": 1785291451.5032556, "status": "ok", "bytes": 7179944, "inference_s": "200.974", "wall_s": 201.0}
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+ {"id": "tassili_n_ajjer_plateau_track", "started_at": 1785291652.4886806, "status": "ok", "bytes": 9646053, "inference_s": "201.652", "wall_s": 201.7}
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+ {"id": "sydney_opera_house___harbour", "started_at": 1785291854.1582212, "status": "ok", "bytes": 8770042, "inference_s": "201.646", "wall_s": 201.7}
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+ {"id": "great_ocean_road", "started_at": 1785292055.8178806, "status": "ok", "bytes": 7513382, "inference_s": "200.891", "wall_s": 200.9}
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+ {"id": "queenstown_lakefront", "started_at": 1785292256.7215385, "status": "ok", "bytes": 7694777, "inference_s": "201.758", "wall_s": 201.8}
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+ {"id": "uluru_base_walk", "started_at": 1785292458.4942544, "status": "ok", "bytes": 7888359, "inference_s": "201.400", "wall_s": 201.4}
131
+ {"id": "milford_sound_fjord_road", "started_at": 1785292659.9071739, "status": "ok", "bytes": 12620713, "inference_s": "201.169", "wall_s": 201.2}
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+ {"id": "coral_coast_highway", "started_at": 1785292861.0961971, "status": "ok", "bytes": 11303979, "inference_s": "201.252", "wall_s": 201.3}
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+ {"id": "bora_bora_overwater_bungalow_path", "started_at": 1785293062.3670175, "status": "ok", "bytes": 8576914, "inference_s": "201.574", "wall_s": 201.6}
134
+ {"id": "bondi_beach_coastal_walk", "started_at": 1785293263.9557347, "status": "ok", "bytes": 7808905, "inference_s": "201.398", "wall_s": 201.4}
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+ {"id": "three_sisters_lookout_trail", "started_at": 1785293465.3669057, "status": "ok", "bytes": 11760406, "inference_s": "200.901", "wall_s": 200.9}
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+ {"id": "hobbiton_movie_set_path", "started_at": 1785293666.2861776, "status": "ok", "bytes": 8726882, "inference_s": "201.582", "wall_s": 201.6}
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+ {"id": "franz_josef_glacier_road", "started_at": 1785293867.8850467, "status": "ok", "bytes": 8135919, "inference_s": "201.517", "wall_s": 201.5}
bench_t2v_space_comprehensive/score_claude.py ADDED
@@ -0,0 +1,259 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # SPDX-License-Identifier: Apache-2.0
2
+ """Sole eval signal for bench_t2v_space_comprehensive: Claude Opus 5 on Amazon
3
+ Bedrock, used as a VLM-as-judge over frames sampled from each generated video.
4
+
5
+ Replaces the previous two-model setup (local Qwen3.5-27B + TIGER-Lab/VideoScore2
6
+ combined by combine.py) -- there is now exactly one judge, so there is nothing
7
+ to combine; summarize.py just aggregates this scorer's output.
8
+
9
+ The rubric is unchanged from the Qwen3.5 version: three axes, each 0-10 --
10
+ `alignment` (is this the SPECIFIC named real-world place?), `quality`,
11
+ `smoothness`.
12
+
13
+ Claude takes images, not video, so each video is reduced to K evenly-spaced
14
+ frames sent as JPEG images in one user turn. Frames are downscaled to
15
+ --max-side (default 768px long edge) to keep per-request image tokens
16
+ reasonable: Claude bills roughly (w*h)/750 tokens per image, so 8 frames at
17
+ 768x432 is ~3.5k image tokens per video.
18
+
19
+ Requirements:
20
+ pip install 'anthropic[bedrock]' # boto3 is what signs the SigV4 request
21
+ AWS credentials resolvable the usual way (env vars, ~/.aws, instance role)
22
+ AWS_REGION (or --aws-region) set to a region where the model is enabled
23
+
24
+ Usage (CPU node is fine -- no local model is loaded):
25
+ python score_claude.py # scores outputs/videos/*.mp4
26
+ python score_claude.py --limit 5 # quick partial check
27
+ python score_claude.py --concurrency 8 # more in-flight requests
28
+ Output: outputs/claude_scores.jsonl (resumable -- skips ids already present).
29
+ """
30
+ from __future__ import annotations
31
+
32
+ import argparse
33
+ import base64
34
+ import json
35
+ import re
36
+ import threading
37
+ from concurrent.futures import ThreadPoolExecutor
38
+ from pathlib import Path
39
+
40
+ import cv2
41
+ import numpy as np
42
+
43
+ HERE = Path(__file__).resolve().parent
44
+
45
+ DEFAULT_MODEL = "anthropic.claude-opus-5"
46
+ DEFAULT_REGION = "us-east-1"
47
+
48
+ K_FRAMES = 8
49
+ MAX_SIDE = 768
50
+ JPEG_QUALITY = 90
51
+ MAX_TOKENS = 4000
52
+
53
+ AXES = ("alignment", "quality", "smoothness")
54
+
55
+ JUDGE_PROMPT_TEMPLATE = """You are a STRICT, SKEPTICAL judge of an AI-generated video against the text prompt that produced it. Most generated videos have real flaws -- assume there are problems until the frames clearly prove otherwise. Do not give credit for "close enough" or "same general vibe."
56
+
57
+ Prompt: "{prompt}"
58
+
59
+ The prompt names a specific real-world place. The {k} images above are frames sampled evenly across the video's duration, in order.
60
+
61
+ Rate the video on three axes, each an integer from 0 to 10. Use the full range -- most videos should land in the 3-6 band; reserve 9-10 for videos with essentially no flaws.
62
+
63
+ alignment (does this show the SPECIFIC named place, not a generic lookalike?):
64
+ 10 = unmistakably the named place, every distinctive identifying feature (exact architecture, layout, landmarks) present and correct
65
+ 8-9 = clearly the named place, at most one minor identifying detail off
66
+ 6-7 = recognizable as the named place but missing or altering several distinctive features
67
+ 4-5 = generic scene of the right broad category (e.g. "a plaza", "a bridge") that could be anywhere -- does NOT capture what makes this place specific
68
+ 2-3 = only a loose thematic connection; a knowledgeable viewer would not identify this as the named place
69
+ 0-1 = wrong place entirely or unrecognizable
70
+
71
+ quality (sharpness, absence of warping/artifacts/melting geometry):
72
+ 10 = photoreal, no visible artifacts anywhere
73
+ 8-9 = very good, at most one small artifact on close inspection
74
+ 6-7 = noticeable but minor artifacts (soft warping, texture smearing) that don't dominate the frame
75
+ 4-5 = clear artifacts in multiple frames (melting geometry, garbled architectural detail, unstable structures)
76
+ 0-3 = pervasive artifacts, badly broken in most frames
77
+
78
+ smoothness (temporal coherence across the frames -- no flicker, no discontinuities, consistent object/architecture identity):
79
+ 10 = perfectly smooth and consistent throughout
80
+ 8-9 = very smooth, at most one minor discontinuity
81
+ 6-7 = mostly smooth but with a couple of noticeable jumps or identity drift
82
+ 4-5 = frequent flicker or objects/architecture changing shape or identity between frames
83
+ 0-3 = incoherent, frames barely relate to each other
84
+
85
+ Be honest and critical -- if you are uncertain whether a detail is correct, score it as if it is wrong, not right.
86
+
87
+ Respond with ONLY a JSON object, no other text, in exactly this form:
88
+ {{"alignment": <int 0-10>, "quality": <int 0-10>, "smoothness": <int 0-10>, "reason": "<one short sentence, naming the specific flaw if any>"}}
89
+ """
90
+
91
+
92
+ def item_meta(it: dict) -> dict:
93
+ """Manifest fields carried through onto every score record."""
94
+ return {"place": it["place"], "country": it["country"],
95
+ "continent": it["continent"], "mode": it["mode"]}
96
+
97
+
98
+ # --- generic below this line -------------------------------------------------
99
+
100
+ def make_client(mode: str, region: str, max_retries: int):
101
+ """Bedrock client. `mantle` is the Messages-API Bedrock endpoint and the
102
+ recommended path; `legacy` is the older bedrock-runtime InvokeModel path,
103
+ kept for accounts that only have that enabled (its model ids look like
104
+ `us.anthropic.claude-opus-5-v1:0` -- pass one with --model)."""
105
+ try:
106
+ from anthropic import AnthropicBedrock, AnthropicBedrockMantle
107
+ except ImportError as exc: # pragma: no cover
108
+ raise SystemExit(f"anthropic SDK not available: {exc}") from exc
109
+ cls = AnthropicBedrockMantle if mode == "mantle" else AnthropicBedrock
110
+ return cls(aws_region=region, max_retries=max_retries)
111
+
112
+
113
+ def sample_frames(video_path: Path, k: int) -> list[np.ndarray]:
114
+ """K evenly-spaced BGR frames across the whole video."""
115
+ cap = cv2.VideoCapture(str(video_path))
116
+ n = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
117
+ if n <= 0:
118
+ cap.release()
119
+ raise RuntimeError(f"no frames read from {video_path}")
120
+ frames = []
121
+ for i in np.linspace(0, n - 1, num=min(k, n), dtype=int):
122
+ cap.set(cv2.CAP_PROP_POS_FRAMES, int(i))
123
+ ok, frame = cap.read()
124
+ if ok:
125
+ frames.append(frame)
126
+ cap.release()
127
+ if not frames:
128
+ raise RuntimeError(f"no frames decoded from {video_path}")
129
+ return frames
130
+
131
+
132
+ def encode_jpeg(frame_bgr: np.ndarray, max_side: int) -> str:
133
+ h, w = frame_bgr.shape[:2]
134
+ scale = max_side / max(h, w)
135
+ if scale < 1:
136
+ frame_bgr = cv2.resize(frame_bgr, (int(w * scale), int(h * scale)),
137
+ interpolation=cv2.INTER_AREA)
138
+ ok, buf = cv2.imencode(".jpg", frame_bgr, [int(cv2.IMWRITE_JPEG_QUALITY), JPEG_QUALITY])
139
+ if not ok:
140
+ raise RuntimeError("cv2.imencode failed")
141
+ return base64.standard_b64encode(buf.tobytes()).decode("ascii")
142
+
143
+
144
+ def parse_judge_json(text: str) -> dict:
145
+ """Pull the JSON object out of the judge's reply and clamp the axes."""
146
+ m = re.search(r"\{.*\}", text, re.S)
147
+ if not m:
148
+ raise ValueError(f"no JSON object found in judge output: {text[:200]!r}")
149
+ obj = json.loads(m.group(0))
150
+ for axis in AXES:
151
+ obj[axis] = max(0.0, min(10.0, float(obj[axis])))
152
+ return obj
153
+
154
+
155
+ def judge_video(client, model: str, effort: str, prompt: str,
156
+ video_path: Path, k_frames: int, max_side: int) -> dict:
157
+ frames = sample_frames(video_path, k_frames)
158
+ content = [
159
+ {"type": "image", "source": {"type": "base64", "media_type": "image/jpeg",
160
+ "data": encode_jpeg(f, max_side)}}
161
+ for f in frames
162
+ ]
163
+ content.append({"type": "text",
164
+ "text": JUDGE_PROMPT_TEMPLATE.format(prompt=prompt, k=len(frames))})
165
+
166
+ response = client.messages.create(
167
+ model=model,
168
+ max_tokens=MAX_TOKENS,
169
+ thinking={"type": "adaptive"},
170
+ output_config={"effort": effort},
171
+ messages=[{"role": "user", "content": content}],
172
+ )
173
+ if response.stop_reason == "refusal":
174
+ category = getattr(response.stop_details, "category", None)
175
+ raise RuntimeError(f"model refused (category={category})")
176
+ text = "".join(b.text for b in response.content if b.type == "text")
177
+ if not text.strip():
178
+ raise RuntimeError(f"empty response (stop_reason={response.stop_reason})")
179
+ return parse_judge_json(text)
180
+
181
+
182
+ def parse_args() -> argparse.Namespace:
183
+ p = argparse.ArgumentParser(description="Score bench_t2v_space_comprehensive with Claude Opus 5 on Bedrock.")
184
+ p.add_argument("--manifest", default=str(HERE / "manifest.json"))
185
+ p.add_argument("--videos-dir", default=str(HERE / "outputs" / "videos"))
186
+ p.add_argument("--out-dir", default=str(HERE / "outputs"))
187
+ p.add_argument("--model", default=DEFAULT_MODEL)
188
+ p.add_argument("--aws-region", default=None,
189
+ help=f"defaults to $AWS_REGION, else {DEFAULT_REGION}")
190
+ p.add_argument("--bedrock-mode", choices=("mantle", "legacy"), default="mantle")
191
+ p.add_argument("--effort", choices=("low", "medium", "high", "xhigh", "max"), default="medium")
192
+ p.add_argument("--limit", type=int, default=None)
193
+ p.add_argument("--k-frames", type=int, default=K_FRAMES)
194
+ p.add_argument("--max-side", type=int, default=MAX_SIDE)
195
+ p.add_argument("--concurrency", type=int, default=4)
196
+ p.add_argument("--max-retries", type=int, default=5)
197
+ return p.parse_args()
198
+
199
+
200
+ def main() -> None:
201
+ import os
202
+
203
+ args = parse_args()
204
+ region = args.aws_region or os.environ.get("AWS_REGION") or DEFAULT_REGION
205
+
206
+ manifest = json.load(open(args.manifest))
207
+ items = manifest["items"]
208
+ if args.limit is not None:
209
+ items = items[: args.limit]
210
+
211
+ videos_dir = Path(args.videos_dir)
212
+ out_dir = Path(args.out_dir)
213
+ out_dir.mkdir(parents=True, exist_ok=True)
214
+ scores_path = out_dir / "claude_scores.jsonl"
215
+ already = set()
216
+ if scores_path.exists():
217
+ for line in scores_path.read_text().splitlines():
218
+ if line.strip():
219
+ already.add(json.loads(line)["id"])
220
+
221
+ todo = [it for it in items if it["id"] not in already]
222
+ print(f"{len(items)} items, {len(already)} already scored, {len(todo)} to score")
223
+ print(f"judge: {args.model} via bedrock ({args.bedrock_mode}, region={region}, effort={args.effort})")
224
+
225
+ client = make_client(args.bedrock_mode, region, args.max_retries)
226
+ write_lock = threading.Lock()
227
+ counter = {"n": 0}
228
+
229
+ def work(it: dict) -> None:
230
+ video_path = videos_dir / f"{it['id']}.mp4"
231
+ meta = {"id": it["id"], **item_meta(it)}
232
+ if not video_path.exists():
233
+ with write_lock:
234
+ counter["n"] += 1
235
+ print(f"[{counter['n']}/{len(todo)}] SKIP {it['id']}: video not found")
236
+ return
237
+ try:
238
+ judge = judge_video(client, args.model, args.effort, it["prompt"],
239
+ video_path, args.k_frames, args.max_side)
240
+ record = {**meta, **{axis: judge[axis] for axis in AXES},
241
+ "reason": judge.get("reason", "")}
242
+ line = " ".join(f"{axis.split('_')[0]}={judge[axis]:.0f}" for axis in AXES)
243
+ except Exception as exc:
244
+ record = {**meta, "error": f"{type(exc).__name__}: {exc}"[:300]}
245
+ line = f"ERROR {exc}"
246
+ with write_lock:
247
+ counter["n"] += 1
248
+ print(f"[{counter['n']}/{len(todo)}] {it['id']}: {line}", flush=True)
249
+ with open(scores_path, "a") as f:
250
+ f.write(json.dumps(record) + "\n")
251
+
252
+ with ThreadPoolExecutor(max_workers=max(1, args.concurrency)) as pool:
253
+ list(pool.map(work, todo))
254
+
255
+ print(f"done -> {scores_path}")
256
+
257
+
258
+ if __name__ == "__main__":
259
+ main()
bench_t2v_space_comprehensive/summarize.py ADDED
@@ -0,0 +1,94 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # SPDX-License-Identifier: Apache-2.0
2
+ """Aggregate score_claude.py output into a per-video score file and a summary.
3
+
4
+ Replaces the old combine.py, which merged two judges (Qwen3.5 + VideoScore2).
5
+ Claude Opus 5 is now the only judge, so there is nothing to combine -- the
6
+ score is just the mean of the three rubric axes:
7
+
8
+ score = mean(alignment, quality, smoothness) / 10
9
+ pass = alignment >= 8 and quality >= 7
10
+
11
+ Thresholds are carried over unchanged from combine.py (alignment >= 8 means a
12
+ near-perfect place match, not just "recognizable"); the VideoScore2
13
+ `min(v,t,p) >= 4` gate is gone with the model that produced it.
14
+
15
+ Usage:
16
+ python summarize.py
17
+ python summarize.py --out-dir outputs
18
+ Output: outputs/scores.jsonl (per-video) + outputs/summary.json.
19
+ """
20
+ from __future__ import annotations
21
+
22
+ import argparse
23
+ import json
24
+ from pathlib import Path
25
+
26
+ import numpy as np
27
+
28
+ HERE = Path(__file__).resolve().parent
29
+
30
+ AXES = ("alignment", "quality", "smoothness")
31
+ GROUP_KEYS = ("mode", "continent")
32
+
33
+ PASS_ALIGNMENT = 8.0
34
+ PASS_QUALITY = 7.0
35
+
36
+
37
+ def passed(r: dict) -> bool:
38
+ return r["alignment"] >= PASS_ALIGNMENT and r["quality"] >= PASS_QUALITY
39
+
40
+
41
+ # --- generic below this line -------------------------------------------------
42
+
43
+ def parse_args() -> argparse.Namespace:
44
+ p = argparse.ArgumentParser(description="Summarize Claude judge scores.")
45
+ p.add_argument("--out-dir", default=str(HERE / "outputs"))
46
+ return p.parse_args()
47
+
48
+
49
+ def load_jsonl(path: Path) -> list[dict]:
50
+ if not path.exists():
51
+ raise SystemExit(f"missing {path} -- run score_claude.py first")
52
+ return [json.loads(l) for l in path.read_text().splitlines() if l.strip()]
53
+
54
+
55
+ def main() -> None:
56
+ args = parse_args()
57
+ out_dir = Path(args.out_dir)
58
+ records = load_jsonl(out_dir / "claude_scores.jsonl")
59
+
60
+ merged = []
61
+ for r in sorted(records, key=lambda x: x["id"]):
62
+ if "error" in r:
63
+ merged.append({**{k: v for k, v in r.items() if k != "reason"}, "pass": False})
64
+ continue
65
+ score = sum(r[axis] for axis in AXES) / (10.0 * len(AXES))
66
+ merged.append({**r, "score": round(score, 4), "pass": passed(r)})
67
+
68
+ scores_path = out_dir / "scores.jsonl"
69
+ scores_path.write_text("\n".join(json.dumps(r) for r in merged) + "\n")
70
+
71
+ ok = [r for r in merged if "error" not in r]
72
+ summary = {
73
+ "judge": "claude-opus-5 (bedrock)",
74
+ "num_scored": len(merged),
75
+ "num_ok": len(ok),
76
+ "num_errors": len(merged) - len(ok),
77
+ "pass_rate": round(sum(r["pass"] for r in ok) / len(ok), 3) if ok else None,
78
+ "mean_score": round(float(np.mean([r["score"] for r in ok])), 3) if ok else None,
79
+ }
80
+ for axis in AXES:
81
+ summary[f"mean_{axis}"] = round(float(np.mean([r[axis] for r in ok])), 3) if ok else None
82
+ for key in GROUP_KEYS:
83
+ groups: dict = {}
84
+ for r in ok:
85
+ groups.setdefault(r[key], []).append(r["score"])
86
+ summary[f"mean_score_by_{key}"] = {k: round(float(np.mean(v)), 3)
87
+ for k, v in sorted(groups.items())}
88
+
89
+ (out_dir / "summary.json").write_text(json.dumps(summary, indent=2))
90
+ print(json.dumps(summary, indent=2))
91
+
92
+
93
+ if __name__ == "__main__":
94
+ main()
bench_t2v_time_comprehensive/manifest.json ADDED
The diff for this file is too large to render. See raw diff
 
bench_t2v_time_comprehensive/results.jsonl ADDED
@@ -0,0 +1,200 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {"id": "misc_14989515-hd_1920_1080_30fps__rain_starts", "variant": "rain_starts", "started_at": 1784590789.599874, "status": "ok", "bytes": 8945630, "inference_s": "203.375", "wall_s": 203.4}
2
+ {"id": "human_016__storm_approaches", "variant": "storm_approaches", "started_at": 1784590993.0048258, "status": "ok", "bytes": 10433488, "inference_s": "202.502", "wall_s": 202.5}
3
+ {"id": "common_sense_962e6081-fb20-412a-ba57-e5dd93d9dd03__thunderstorm_lightning", "variant": "thunderstorm_lightning", "started_at": 1784591195.5276568, "status": "ok", "bytes": 10553029, "inference_s": "202.291", "wall_s": 202.3}
4
+ {"id": "av_46fe9718-b496-4c30-b1b6-8b02028dd336__fog_rolls_in", "variant": "fog_rolls_in", "started_at": 1784591411.1057043, "status": "ok", "bytes": 5007011, "inference_s": "202.369", "wall_s": 202.4}
5
+ {"id": "human_266__snow_starts", "variant": "snow_starts", "started_at": 1784591613.4884238, "status": "ok", "bytes": 9264627, "inference_s": "202.470", "wall_s": 202.5}
6
+ {"id": "human_013__blizzard", "variant": "blizzard", "started_at": 1784591815.979174, "status": "ok", "bytes": 7657183, "inference_s": "202.393", "wall_s": 202.4}
7
+ {"id": "human_010__hail_starts", "variant": "hail_starts", "started_at": 1784592018.3871925, "status": "ok", "bytes": 11392524, "inference_s": "202.524", "wall_s": 202.5}
8
+ {"id": "human_102__mist_burns_off", "variant": "mist_burns_off", "started_at": 1784592220.9338763, "status": "ok", "bytes": 7291287, "inference_s": "202.375", "wall_s": 202.4}
9
+ {"id": "common_sense_7a5402d9-c502-4658-9cbc-8a1bdd161abb__day_to_night", "variant": "day_to_night", "started_at": 1784592423.3238971, "status": "ok", "bytes": 6390207, "inference_s": "202.315", "wall_s": 202.3}
10
+ {"id": "human_168__night_to_day", "variant": "night_to_day", "started_at": 1784592625.6555269, "status": "ok", "bytes": 11375506, "inference_s": "202.465", "wall_s": 202.5}
11
+ {"id": "av_69c37938-8eb3-4234-a708-03d55db9aacc__dusk_golden_hour", "variant": "dusk_golden_hour", "started_at": 1784592828.1446314, "status": "ok", "bytes": 11183466, "inference_s": "202.493", "wall_s": 202.5}
12
+ {"id": "human_137__sunrise", "variant": "sunrise", "started_at": 1784593030.659136, "status": "ok", "bytes": 7101984, "inference_s": "202.464", "wall_s": 202.5}
13
+ {"id": "av_5da7e548-93f4-4a9f-b59d-418051e7c859__sunset", "variant": "sunset", "started_at": 1784593233.1393054, "status": "ok", "bytes": 6191165, "inference_s": "202.405", "wall_s": 202.4}
14
+ {"id": "misc_2254244-uhd_3840_2160_24fps__noon_to_late_afternoon", "variant": "noon_to_late_afternoon", "started_at": 1784593435.5609128, "status": "ok", "bytes": 11929618, "inference_s": "202.611", "wall_s": 202.6}
15
+ {"id": "av_c135ea08-213e-4533-b55b-3bb776cdf345__season_to_autumn", "variant": "season_to_autumn", "started_at": 1784593638.1940017, "status": "ok", "bytes": 9168135, "inference_s": "202.512", "wall_s": 202.5}
16
+ {"id": "human_214__day_night_day", "variant": "day_night_day", "started_at": 1784593840.7254562, "status": "ok", "bytes": 8643596, "inference_s": "202.529", "wall_s": 202.5}
17
+ {"id": "common_sense_8740b595-939f-4e60-a2a0-fb9df396ba66__clear_rain_clear", "variant": "clear_rain_clear", "started_at": 1784594043.2735188, "status": "ok", "bytes": 6742668, "inference_s": "202.446", "wall_s": 202.5}
18
+ {"id": "common_sense_e0bf6d20-504c-46cc-8b48-f7dcef57762a__clouds_time_lapse", "variant": "clouds_time_lapse", "started_at": 1784594245.7349763, "status": "ok", "bytes": 10177302, "inference_s": "202.622", "wall_s": 202.6}
19
+ {"id": "common_sense_73c951a6-d5e3-4664-bd84-0598584e4a41__sun_glare_to_overcast", "variant": "sun_glare_to_overcast", "started_at": 1784594448.3771093, "status": "ok", "bytes": 4572845, "inference_s": "202.355", "wall_s": 202.4}
20
+ {"id": "av_51b45829-502e-4143-9c32-c026bd6ab191__heat_haze_shimmer", "variant": "heat_haze_shimmer", "started_at": 1784594650.7447326, "status": "ok", "bytes": 5670617, "inference_s": "202.384", "wall_s": 202.4}
21
+ {"id": "human_254__rain_starts", "variant": "rain_starts", "started_at": 1784594853.1427624, "status": "ok", "bytes": 13891799, "inference_s": "202.513", "wall_s": 202.5}
22
+ {"id": "human_018__storm_approaches", "variant": "storm_approaches", "started_at": 1784595055.6819818, "status": "ok", "bytes": 8467530, "inference_s": "202.521", "wall_s": 202.5}
23
+ {"id": "misc_13362641_3840_2160_25fps__thunderstorm_lightning", "variant": "thunderstorm_lightning", "started_at": 1784595258.221112, "status": "ok", "bytes": 6325028, "inference_s": "202.410", "wall_s": 202.4}
24
+ {"id": "common_sense_071c7452-afc7-4dd7-99af-ee9668572af7__fog_rolls_in", "variant": "fog_rolls_in", "started_at": 1784595460.6450222, "status": "ok", "bytes": 7677746, "inference_s": "202.580", "wall_s": 202.6}
25
+ {"id": "av_adc4f0ac-5a6d-4142-a914-41f032dc8672__snow_starts", "variant": "snow_starts", "started_at": 1784595663.2386963, "status": "ok", "bytes": 8404726, "inference_s": "202.506", "wall_s": 202.5}
26
+ {"id": "misc_3326930-hd_1920_1080_24fps__blizzard", "variant": "blizzard", "started_at": 1784595865.76193, "status": "ok", "bytes": 5490718, "inference_s": "202.416", "wall_s": 202.4}
27
+ {"id": "misc_2099536-hd_1920_1080_30fps__hail_starts", "variant": "hail_starts", "started_at": 1784596068.1938019, "status": "ok", "bytes": 8101558, "inference_s": "202.558", "wall_s": 202.6}
28
+ {"id": "common_sense_06fbad19-a061-48a7-b0ee-c2be28b30528__mist_burns_off", "variant": "mist_burns_off", "started_at": 1784596270.766454, "status": "ok", "bytes": 7932423, "inference_s": "202.456", "wall_s": 202.5}
29
+ {"id": "misc_18820560-uhd_3840_2160_25fps__day_to_night", "variant": "day_to_night", "started_at": 1784596473.2396207, "status": "ok", "bytes": 4672732, "inference_s": "202.417", "wall_s": 202.4}
30
+ {"id": "misc_4757483-hd_1920_1080_30fps__night_to_day", "variant": "night_to_day", "started_at": 1784596675.6692417, "status": "ok", "bytes": 6308685, "inference_s": "202.341", "wall_s": 202.4}
31
+ {"id": "av_75c13cf4-888d-4fbe-bc67-eef9e7e716b5__dusk_golden_hour", "variant": "dusk_golden_hour", "started_at": 1784596878.0227542, "status": "ok", "bytes": 8935079, "inference_s": "202.407", "wall_s": 202.4}
32
+ {"id": "common_sense_3092507f-b59a-4948-9da4-9e7541001f45__sunrise", "variant": "sunrise", "started_at": 1784597080.4466648, "status": "ok", "bytes": 5995256, "inference_s": "202.420", "wall_s": 202.4}
33
+ {"id": "av_2cdc6699-574f-40b7-9b5b-15905c540274__sunset", "variant": "sunset", "started_at": 1784597282.8799272, "status": "ok", "bytes": 5932897, "inference_s": "202.377", "wall_s": 202.4}
34
+ {"id": "human_142__noon_to_late_afternoon", "variant": "noon_to_late_afternoon", "started_at": 1784597485.269235, "status": "ok", "bytes": 7671604, "inference_s": "202.305", "wall_s": 202.3}
35
+ {"id": "misc_2812731-hd_1920_1080_30fps__season_to_autumn", "variant": "season_to_autumn", "started_at": 1784597687.5866084, "status": "ok", "bytes": 10644979, "inference_s": "201.621", "wall_s": 201.6}
36
+ {"id": "human_247__day_night_day", "variant": "day_night_day", "started_at": 1784597889.225821, "status": "ok", "bytes": 5160011, "inference_s": "202.070", "wall_s": 202.1}
37
+ {"id": "av_b690d0f9-3f65-4340-aaf6-479c9d2797c7__clear_rain_clear", "variant": "clear_rain_clear", "started_at": 1784598091.307711, "status": "ok", "bytes": 10306608, "inference_s": "202.153", "wall_s": 202.2}
38
+ {"id": "misc_13280173_3840_2160_25fps__clouds_time_lapse", "variant": "clouds_time_lapse", "started_at": 1784598293.4802647, "status": "ok", "bytes": 7219386, "inference_s": "202.324", "wall_s": 202.3}
39
+ {"id": "human_281__sun_glare_to_overcast", "variant": "sun_glare_to_overcast", "started_at": 1784598495.8173907, "status": "ok", "bytes": 11257674, "inference_s": "202.343", "wall_s": 202.4}
40
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bench_t2v_time_comprehensive/score_claude.py ADDED
@@ -0,0 +1,263 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # SPDX-License-Identifier: Apache-2.0
2
+ """Sole eval signal for bench_t2v_time_comprehensive: Claude Opus 5 on Amazon
3
+ Bedrock, used as a VLM-as-judge over frames sampled from each generated video.
4
+
5
+ Replaces the previous two-model setup this bench borrowed from `bench_i2v_time`
6
+ (a local VLM reward judge + TIGER-Lab/VideoScore2, merged by `combine_v3.py`,
7
+ which produced the old `scores_v2`/`scores_v3` files) -- there is now exactly
8
+ one judge and it lives here, so there is nothing to combine; summarize.py just
9
+ aggregates this scorer's output.
10
+
11
+ Three axes, each 0-10 -- `time_alignment` (did the described time/weather
12
+ transition actually happen, in the right direction?), `quality`, `smoothness`.
13
+
14
+ Claude takes images, not video, so each video is reduced to K evenly-spaced
15
+ frames sent as JPEG images in one user turn. Frames are downscaled to
16
+ --max-side (default 768px long edge) to keep per-request image tokens
17
+ reasonable: Claude bills roughly (w*h)/750 tokens per image, so 8 frames at
18
+ 768x432 is ~3.5k image tokens per video.
19
+
20
+ Requirements:
21
+ pip install 'anthropic[bedrock]' # boto3 is what signs the SigV4 request
22
+ AWS credentials resolvable the usual way (env vars, ~/.aws, instance role)
23
+ AWS_REGION (or --aws-region) set to a region where the model is enabled
24
+
25
+ Usage (CPU node is fine -- no local model is loaded):
26
+ python score_claude.py # scores outputs/videos/*.mp4
27
+ python score_claude.py --limit 5 # quick partial check
28
+ python score_claude.py --concurrency 8 # more in-flight requests
29
+ Output: outputs/claude_scores.jsonl (resumable -- skips ids already present).
30
+ """
31
+ from __future__ import annotations
32
+
33
+ import argparse
34
+ import base64
35
+ import json
36
+ import re
37
+ import threading
38
+ from concurrent.futures import ThreadPoolExecutor
39
+ from pathlib import Path
40
+
41
+ import cv2
42
+ import numpy as np
43
+
44
+ HERE = Path(__file__).resolve().parent
45
+
46
+ DEFAULT_MODEL = "anthropic.claude-opus-5"
47
+ DEFAULT_REGION = "us-east-1"
48
+
49
+ K_FRAMES = 8
50
+ MAX_SIDE = 768
51
+ JPEG_QUALITY = 90
52
+ MAX_TOKENS = 4000
53
+
54
+ AXES = ("time_alignment", "quality", "smoothness")
55
+
56
+ JUDGE_PROMPT_TEMPLATE = """You are a STRICT, SKEPTICAL judge of an AI-generated video against the text prompt that produced it. Most generated videos have real flaws -- assume there are problems until the frames clearly prove otherwise. Do not give credit for "close enough" or "same general vibe."
57
+
58
+ Prompt: "{prompt}"
59
+
60
+ The prompt describes a scene followed by an instructed TIME/WEATHER transition. The {k} images above are frames sampled evenly across the video's duration, in order.
61
+
62
+ Rate the video on three axes, each an integer from 0 to 10. Use the full range -- most videos should land in the 3-6 band; reserve 9-10 for videos with essentially no flaws.
63
+
64
+ time_alignment (does the described time/weather transition actually happen, in the right direction?):
65
+ 10 = the transition clearly and correctly happens exactly as described (right direction, right end state)
66
+ 8-9 = the transition happens correctly, at most one minor detail off (e.g. slightly under/overshooting the described end state)
67
+ 6-7 = a transition happens and is recognizable as the right general kind (e.g. it does get darker/wetter/snowier) but is incomplete, weak, or has some wrong details
68
+ 4-5 = little to no visible transition, or the wrong kind of change (e.g. asked for rain, got only clouds)
69
+ 2-3 = the scene changes in some way but not toward what was described, or the requested state is contradicted
70
+ 0-1 = no transition at all, or the opposite of what was described
71
+
72
+ Note: for a non-monotonic transition (e.g. day->night->day, clear->rain->clear) the
73
+ scene must reach the intermediate state AND return -- drifting one way and stopping
74
+ there is a 4-5, not a pass.
75
+
76
+ quality (sharpness, absence of warping/artifacts/melting geometry):
77
+ 10 = photoreal, no visible artifacts anywhere
78
+ 8-9 = very good, at most one small artifact on close inspection
79
+ 6-7 = noticeable but minor artifacts (soft warping, texture smearing) that don't dominate the frame
80
+ 4-5 = clear artifacts in multiple frames (melting geometry, garbled architectural detail, unstable structures)
81
+ 0-3 = pervasive artifacts, badly broken in most frames
82
+
83
+ smoothness (temporal coherence across the frames -- no flicker, no discontinuities, consistent object/architecture identity):
84
+ 10 = perfectly smooth and consistent throughout
85
+ 8-9 = very smooth, at most one minor discontinuity
86
+ 6-7 = mostly smooth but with a couple of noticeable jumps or identity drift
87
+ 4-5 = frequent flicker or objects/architecture changing shape or identity between frames
88
+ 0-3 = incoherent, frames barely relate to each other
89
+
90
+ Be honest and critical -- if you are uncertain whether a detail is correct, score it as if it is wrong, not right.
91
+
92
+ Respond with ONLY a JSON object, no other text, in exactly this form:
93
+ {{"time_alignment": <int 0-10>, "quality": <int 0-10>, "smoothness": <int 0-10>, "reason": "<one short sentence, naming the specific flaw if any>"}}
94
+ """
95
+
96
+
97
+ def item_meta(it: dict) -> dict:
98
+ """Manifest fields carried through onto every score record."""
99
+ return {"domain": it["domain"], "variant": it["variant"]}
100
+
101
+
102
+ # --- generic below this line -------------------------------------------------
103
+
104
+ def make_client(mode: str, region: str, max_retries: int):
105
+ """Bedrock client. `mantle` is the Messages-API Bedrock endpoint and the
106
+ recommended path; `legacy` is the older bedrock-runtime InvokeModel path,
107
+ kept for accounts that only have that enabled (its model ids look like
108
+ `us.anthropic.claude-opus-5-v1:0` -- pass one with --model)."""
109
+ try:
110
+ from anthropic import AnthropicBedrock, AnthropicBedrockMantle
111
+ except ImportError as exc: # pragma: no cover
112
+ raise SystemExit(f"anthropic SDK not available: {exc}") from exc
113
+ cls = AnthropicBedrockMantle if mode == "mantle" else AnthropicBedrock
114
+ return cls(aws_region=region, max_retries=max_retries)
115
+
116
+
117
+ def sample_frames(video_path: Path, k: int) -> list[np.ndarray]:
118
+ """K evenly-spaced BGR frames across the whole video."""
119
+ cap = cv2.VideoCapture(str(video_path))
120
+ n = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
121
+ if n <= 0:
122
+ cap.release()
123
+ raise RuntimeError(f"no frames read from {video_path}")
124
+ frames = []
125
+ for i in np.linspace(0, n - 1, num=min(k, n), dtype=int):
126
+ cap.set(cv2.CAP_PROP_POS_FRAMES, int(i))
127
+ ok, frame = cap.read()
128
+ if ok:
129
+ frames.append(frame)
130
+ cap.release()
131
+ if not frames:
132
+ raise RuntimeError(f"no frames decoded from {video_path}")
133
+ return frames
134
+
135
+
136
+ def encode_jpeg(frame_bgr: np.ndarray, max_side: int) -> str:
137
+ h, w = frame_bgr.shape[:2]
138
+ scale = max_side / max(h, w)
139
+ if scale < 1:
140
+ frame_bgr = cv2.resize(frame_bgr, (int(w * scale), int(h * scale)),
141
+ interpolation=cv2.INTER_AREA)
142
+ ok, buf = cv2.imencode(".jpg", frame_bgr, [int(cv2.IMWRITE_JPEG_QUALITY), JPEG_QUALITY])
143
+ if not ok:
144
+ raise RuntimeError("cv2.imencode failed")
145
+ return base64.standard_b64encode(buf.tobytes()).decode("ascii")
146
+
147
+
148
+ def parse_judge_json(text: str) -> dict:
149
+ """Pull the JSON object out of the judge's reply and clamp the axes."""
150
+ m = re.search(r"\{.*\}", text, re.S)
151
+ if not m:
152
+ raise ValueError(f"no JSON object found in judge output: {text[:200]!r}")
153
+ obj = json.loads(m.group(0))
154
+ for axis in AXES:
155
+ obj[axis] = max(0.0, min(10.0, float(obj[axis])))
156
+ return obj
157
+
158
+
159
+ def judge_video(client, model: str, effort: str, prompt: str,
160
+ video_path: Path, k_frames: int, max_side: int) -> dict:
161
+ frames = sample_frames(video_path, k_frames)
162
+ content = [
163
+ {"type": "image", "source": {"type": "base64", "media_type": "image/jpeg",
164
+ "data": encode_jpeg(f, max_side)}}
165
+ for f in frames
166
+ ]
167
+ content.append({"type": "text",
168
+ "text": JUDGE_PROMPT_TEMPLATE.format(prompt=prompt, k=len(frames))})
169
+
170
+ response = client.messages.create(
171
+ model=model,
172
+ max_tokens=MAX_TOKENS,
173
+ thinking={"type": "adaptive"},
174
+ output_config={"effort": effort},
175
+ messages=[{"role": "user", "content": content}],
176
+ )
177
+ if response.stop_reason == "refusal":
178
+ category = getattr(response.stop_details, "category", None)
179
+ raise RuntimeError(f"model refused (category={category})")
180
+ text = "".join(b.text for b in response.content if b.type == "text")
181
+ if not text.strip():
182
+ raise RuntimeError(f"empty response (stop_reason={response.stop_reason})")
183
+ return parse_judge_json(text)
184
+
185
+
186
+ def parse_args() -> argparse.Namespace:
187
+ p = argparse.ArgumentParser(description="Score bench_t2v_time_comprehensive with Claude Opus 5 on Bedrock.")
188
+ p.add_argument("--manifest", default=str(HERE / "manifest.json"))
189
+ p.add_argument("--videos-dir", default=str(HERE / "outputs" / "videos"))
190
+ p.add_argument("--out-dir", default=str(HERE / "outputs"))
191
+ p.add_argument("--model", default=DEFAULT_MODEL)
192
+ p.add_argument("--aws-region", default=None,
193
+ help=f"defaults to $AWS_REGION, else {DEFAULT_REGION}")
194
+ p.add_argument("--bedrock-mode", choices=("mantle", "legacy"), default="mantle")
195
+ p.add_argument("--effort", choices=("low", "medium", "high", "xhigh", "max"), default="medium")
196
+ p.add_argument("--limit", type=int, default=None)
197
+ p.add_argument("--k-frames", type=int, default=K_FRAMES)
198
+ p.add_argument("--max-side", type=int, default=MAX_SIDE)
199
+ p.add_argument("--concurrency", type=int, default=4)
200
+ p.add_argument("--max-retries", type=int, default=5)
201
+ return p.parse_args()
202
+
203
+
204
+ def main() -> None:
205
+ import os
206
+
207
+ args = parse_args()
208
+ region = args.aws_region or os.environ.get("AWS_REGION") or DEFAULT_REGION
209
+
210
+ manifest = json.load(open(args.manifest))
211
+ items = manifest["items"]
212
+ if args.limit is not None:
213
+ items = items[: args.limit]
214
+
215
+ videos_dir = Path(args.videos_dir)
216
+ out_dir = Path(args.out_dir)
217
+ out_dir.mkdir(parents=True, exist_ok=True)
218
+ scores_path = out_dir / "claude_scores.jsonl"
219
+ already = set()
220
+ if scores_path.exists():
221
+ for line in scores_path.read_text().splitlines():
222
+ if line.strip():
223
+ already.add(json.loads(line)["id"])
224
+
225
+ todo = [it for it in items if it["id"] not in already]
226
+ print(f"{len(items)} items, {len(already)} already scored, {len(todo)} to score")
227
+ print(f"judge: {args.model} via bedrock ({args.bedrock_mode}, region={region}, effort={args.effort})")
228
+
229
+ client = make_client(args.bedrock_mode, region, args.max_retries)
230
+ write_lock = threading.Lock()
231
+ counter = {"n": 0}
232
+
233
+ def work(it: dict) -> None:
234
+ video_path = videos_dir / f"{it['id']}.mp4"
235
+ meta = {"id": it["id"], **item_meta(it)}
236
+ if not video_path.exists():
237
+ with write_lock:
238
+ counter["n"] += 1
239
+ print(f"[{counter['n']}/{len(todo)}] SKIP {it['id']}: video not found")
240
+ return
241
+ try:
242
+ judge = judge_video(client, args.model, args.effort, it["prompt"],
243
+ video_path, args.k_frames, args.max_side)
244
+ record = {**meta, **{axis: judge[axis] for axis in AXES},
245
+ "reason": judge.get("reason", "")}
246
+ line = " ".join(f"{axis.split('_')[0]}={judge[axis]:.0f}" for axis in AXES)
247
+ except Exception as exc:
248
+ record = {**meta, "error": f"{type(exc).__name__}: {exc}"[:300]}
249
+ line = f"ERROR {exc}"
250
+ with write_lock:
251
+ counter["n"] += 1
252
+ print(f"[{counter['n']}/{len(todo)}] {it['id']}: {line}", flush=True)
253
+ with open(scores_path, "a") as f:
254
+ f.write(json.dumps(record) + "\n")
255
+
256
+ with ThreadPoolExecutor(max_workers=max(1, args.concurrency)) as pool:
257
+ list(pool.map(work, todo))
258
+
259
+ print(f"done -> {scores_path}")
260
+
261
+
262
+ if __name__ == "__main__":
263
+ main()
bench_t2v_time_comprehensive/summarize.py ADDED
@@ -0,0 +1,92 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # SPDX-License-Identifier: Apache-2.0
2
+ """Aggregate score_claude.py output into a per-video score file and a summary.
3
+
4
+ Claude Opus 5 is the only judge, so the score is just the mean of the three
5
+ rubric axes:
6
+
7
+ score = mean(time_alignment, quality, smoothness) / 10
8
+ pass = time_alignment >= 8 and quality >= 7
9
+
10
+ Thresholds match the other benches in this directory: time_alignment >= 8 means
11
+ the transition landed on the described end state, not merely drifted toward it.
12
+
13
+ Usage:
14
+ python summarize.py
15
+ python summarize.py --out-dir outputs
16
+ Output: outputs/scores.jsonl (per-video) + outputs/summary.json.
17
+ """
18
+ from __future__ import annotations
19
+
20
+ import argparse
21
+ import json
22
+ from pathlib import Path
23
+
24
+ import numpy as np
25
+
26
+ HERE = Path(__file__).resolve().parent
27
+
28
+ AXES = ("time_alignment", "quality", "smoothness")
29
+ GROUP_KEYS = ("variant", "domain")
30
+
31
+ PASS_TIME_ALIGNMENT = 8.0
32
+ PASS_QUALITY = 7.0
33
+
34
+
35
+ def passed(r: dict) -> bool:
36
+ return r["time_alignment"] >= PASS_TIME_ALIGNMENT and r["quality"] >= PASS_QUALITY
37
+
38
+
39
+ # --- generic below this line -------------------------------------------------
40
+
41
+ def parse_args() -> argparse.Namespace:
42
+ p = argparse.ArgumentParser(description="Summarize Claude judge scores.")
43
+ p.add_argument("--out-dir", default=str(HERE / "outputs"))
44
+ return p.parse_args()
45
+
46
+
47
+ def load_jsonl(path: Path) -> list[dict]:
48
+ if not path.exists():
49
+ raise SystemExit(f"missing {path} -- run score_claude.py first")
50
+ return [json.loads(l) for l in path.read_text().splitlines() if l.strip()]
51
+
52
+
53
+ def main() -> None:
54
+ args = parse_args()
55
+ out_dir = Path(args.out_dir)
56
+ records = load_jsonl(out_dir / "claude_scores.jsonl")
57
+
58
+ merged = []
59
+ for r in sorted(records, key=lambda x: x["id"]):
60
+ if "error" in r:
61
+ merged.append({**{k: v for k, v in r.items() if k != "reason"}, "pass": False})
62
+ continue
63
+ score = sum(r[axis] for axis in AXES) / (10.0 * len(AXES))
64
+ merged.append({**r, "score": round(score, 4), "pass": passed(r)})
65
+
66
+ scores_path = out_dir / "scores.jsonl"
67
+ scores_path.write_text("\n".join(json.dumps(r) for r in merged) + "\n")
68
+
69
+ ok = [r for r in merged if "error" not in r]
70
+ summary = {
71
+ "judge": "claude-opus-5 (bedrock)",
72
+ "num_scored": len(merged),
73
+ "num_ok": len(ok),
74
+ "num_errors": len(merged) - len(ok),
75
+ "pass_rate": round(sum(r["pass"] for r in ok) / len(ok), 3) if ok else None,
76
+ "mean_score": round(float(np.mean([r["score"] for r in ok])), 3) if ok else None,
77
+ }
78
+ for axis in AXES:
79
+ summary[f"mean_{axis}"] = round(float(np.mean([r[axis] for r in ok])), 3) if ok else None
80
+ for key in GROUP_KEYS:
81
+ groups: dict = {}
82
+ for r in ok:
83
+ groups.setdefault(r[key], []).append(r["score"])
84
+ summary[f"mean_score_by_{key}"] = {k: round(float(np.mean(v)), 3)
85
+ for k, v in sorted(groups.items())}
86
+
87
+ (out_dir / "summary.json").write_text(json.dumps(summary, indent=2))
88
+ print(json.dumps(summary, indent=2))
89
+
90
+
91
+ if __name__ == "__main__":
92
+ main()