Add files using upload-large-folder tool

.gitignore

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+runtime/
+__pycache__/
+*.pyc
+dist/

README.md

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+---
+pretty_name: OneSearch-Video-Bench
+language:
+- en
+task_categories:
+- visual-question-answering
+tags:
+- benchmark
+- visual-search
+- video
+size_categories:
+- n<1K
+configs:
+- config_name: default
+  data_files:
+  - split: test
+    path: test.jsonl
+---
+
+# OneSearch-Video
+
+OneSearch-Video contains 307 visual question-answer pairs over 293 silent videos.
+The distributed MP4 files play at **1 FPS**. Each playback second represents one
+ordered frame slot in the benchmark input. This is the playback rate of the
+sampled sequence, not a claim that the source footage was sampled once per second.
+
+## Files
+
+```text
+README.md
+prepare.py
+extract_frames.py
+SHA256SUMS
+test.jsonl
+media.jsonl
+frames.jsonl
+alignment.json
+media/
+  0000.mp4
+  ...
+runtime/frames/
+  0000/frame_000.png
+  ...
+```
+
+Videos are distributed in `video-00001.zip`. Original-resolution tool frames
+are distributed separately in `video-frames-*.zip`. Extract both the video
+archive and every frame archive into this directory, preserving their paths.
+Each archive is at most 10 GB (10,000,000,000 bytes). The PNGs preserve the
+annotation images exactly, including their original resolution and file bytes.
+They are not decoded from the smaller MP4s.
+
+From the distribution directory:
+
+```bash
+sha256sum -c SHA256SUMS
+unzip video-00001.zip
+for archive in video-frames-*.zip; do unzip "$archive"; done
+```
+
+`test.jsonl` has one record per question:
+
+| Field | Meaning |
+| --- | --- |
+| `id` | Stable sample ID, represented as a string |
+| `question` | Question given to the model |
+| `answer` | Reference answer for evaluation; not an actor input |
+| `video` | MP4 path relative to this dataset directory |
+| `fps` | Playback rate, always `1` |
+| `n_frames` | Number of frames in the released MP4 |
+| `structure` | Question structure |
+| `difficulty` | Difficulty label |
+| `num_hops` | Annotated reasoning hop count |
+| `knowledge_domain` | Knowledge category |
+
+Multiple questions may reference the same video. `media.jsonl` contains
+one entry per unique MP4 with its relative path, byte size, SHA-256 checksum,
+frame count, playback rate and encoded dimensions. `frames.jsonl` binds every
+video checksum to its ordered original-resolution PNGs, with relative paths,
+frame indices, byte sizes, checksums and image dimensions. `alignment.json`
+records the scope and results of the frame correspondence checks.
+
+The checks cover all 307 QA records, 565 annotated target-frame references,
+293 videos and 37,354 PNGs. Annotation frame indices match their source-frame
+mapping. Encoding the ordered reference PNGs reproduces 253 MP4s byte for byte;
+the other 40 videos pass per-frame visual correspondence checks against all
+candidate frame slots. See `alignment.json` for the comparison method and
+tolerances. All distributed PNGs are byte-identical to their reference files.
+
+## Optional MP4 frame extraction
+
+The benchmark uses the distributed original-resolution PNGs. For inspection,
+`extract_frames.py` can also decode frames from the MP4 files:
+
+```bash
+python extract_frames.py
+python extract_frames.py --video media/0000.mp4
+python extract_frames.py --output-dir ./decoded_frames --workers 4
+```
+
+These diagnostic frames go to `runtime/decoded_frames/<video_id>/` by default.
+The script preserves the MP4 frame order and encoded dimensions, which can be
+smaller than the benchmark PNG dimensions. It refuses to write to the official
+`runtime/frames/` tree. MP4-decoded images must not replace the original-resolution
+benchmark images. No API key or network access is needed for extraction.
+
+## Prepare inference inputs
+
+Requirements: Python 3.9 or newer, `ffmpeg` and `ffprobe` on `PATH`.
+The loader uses the Python standard library and makes no model or judge calls.
+
+After extracting both kinds of media archives, check all videos and PNGs:
+
+```bash
+python prepare.py --verify-only
+```
+
+Expose this entire dataset directory through an HTTP(S) media server reachable
+by the inference backend. Set `MEDIA_BASE_URL` to its URL, then run:
+
+```bash
+python prepare.py --media-base-url "$MEDIA_BASE_URL"
+```
+
+The loader checks each MP4 checksum, stream layout, playback rate and frame
+count, then verifies the existing original-resolution PNG filenames, sequence
+and checksums against `frames.jsonl`. It does not decode, resize, replace or
+regenerate the benchmark images. Missing or mismatched frame files cause an
+error instead of falling back to MP4 decoding.
+
+The generated files are:
+
+- `runtime/video.csv`: `index,question,answer` for inference and evaluation.
+- `runtime/video_manifest.jsonl`: the video and ordered frame URLs for tools.
+The media server must also expose `runtime/frames/`, populated by extracting
+the frame archives. The loader does not generate these PNGs.
+
+For every sample, `case_id` equals its `id`; `n_frames` equals the number of
+`frame_urls`; `frame_indices` is `0..n_frames-1`; `grid_fps` is `1.0`;
+`duration` is `n_frames` playback seconds. Frame slot `i` refers to the frame
+at playback time `i` seconds. A time span `[a, b)` uses slots `a` through `b-1`.
+The manifest contains no answers, annotations or source-video metadata.
+
+From the OneSearch-VL code repository, with `DATA_ROOT` pointing to this dataset:
+
+```bash
+python onesearch_vl/run_infer_video.py \
+  --model 8b --checkpoint /models/your-checkpoint \
+  --csv "$DATA_ROOT/runtime/video.csv" \
+  --manifest "$DATA_ROOT/runtime/video_manifest.jsonl" \
+  --output-dir outputs/onesearch_video
+
+bash onesearch_vl/run_eval.sh video \
+  --csv "$DATA_ROOT/runtime/video.csv" \
+  --traj_dir outputs/onesearch_video
+```
+
+Configure inference, search and evaluation credentials in the code repository
+before running those commands. Only the question and visual media are actor
+inputs. Reference answers are used by the evaluator. Audio, source timestamps,
+source URLs and video metadata are not supplied as evidence.
+
+The MP4 overview and the PNG tool inputs represent the same ordered frame
+sequence. The MP4 is scaled and compressed; the PNGs retain the annotation
+images' resolution for object crops and visual search. Frame slot `i` in the
+video maps to `frame_i` in the PNG sequence. A correspondence check does not
+establish the semantic correctness or answerability of every QA sample.
+No model evaluation results are included in this package.

SHA256SUMS

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+aa1d4882ba643f10a0cbd9ca21e8d050625d2068e8e2ba8520ae76251f06154d  README.md
+dd4db8fc64dbe61da225bca577f30d16f81f0d976319df94797d6d115428ed7b  prepare.py
+2396b530f8c0a72bb12a1418c0ceb935cfd17778e98c780fa4cf09fbdb8cc12b  extract_frames.py
+8f6e9f17e6464bfe8336e04facf69febb49d8d8c5f82eb21356bdc0c685a1d81  .gitignore
+5c2a97c7252742cada38008837e709ee91a5e3837e3688e885f6e25f925aaa42  test.jsonl
+b18ecb87f019e3a1197e40daf49a6b30ffc5aa4d825ca2d85e3f997184ad7ff9  media.jsonl
+da92ea350d45d710333c187082967f7e7ffc376316bf73d60d1847d63d241c8f  frames.jsonl
+0cc30b5e9020a3fb11d772f84d53a0e27b70eb4d18e372bd6434b83bf82f7e26  alignment.json
+b14bf8f86fc4ed442baf42aa1275705e2deb1f682ae6b9bff4aadb2b29998312  video-00001.zip
+0d4b13f8a605006b4ae850a21105a2ee53d769526b35482faf2ee76eb8999bdd  video-frames-00001.zip
+e002c2925c85c8ac5dcead5df7bf9b18a5f2f065afeacd4523e48a3d80d1f57a  video-frames-00002.zip

alignment.json

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+{
+  "status": "passed",
+  "scope": "Frame indices, visual correspondence and file integrity; QA semantic correctness is not evaluated.",
+  "samples": 307,
+  "videos": 293,
+  "frames": 37354,
+  "frame_source": "original_resolution_annotation_pngs",
+  "original_png_bytes_preserved": true,
+  "mp4_decoded_pngs_packaged": false,
+  "annotation_target_references_checked": 565,
+  "unique_annotation_target_frames": 544,
+  "evidence_chain_entries_checked": 656,
+  "annotation_source_index_mismatches": 0,
+  "ordered_pngs_reproduce_exact_mp4_bytes": 253,
+  "remaining_videos_checked_frame_by_frame": 40,
+  "remaining_frames_checked": 5006,
+  "comparison_method": {
+    "resolution": [
+      32,
+      32
+    ],
+    "distance": "RGB mean absolute error on 0..255 channels",
+    "same_slot_error_limit": 12,
+    "alternative_slot_advantage_limit": 3
+  },
+  "max_same_slot_error": 11.487629890441895,
+  "max_alternative_slot_advantage": 0.375,
+  "material_frame_displacements_detected": 0,
+  "frame_manifest_sha256": "da92ea350d45d710333c187082967f7e7ffc376316bf73d60d1847d63d241c8f",
+  "runtime_qa_and_manifest_ids_aligned": true,
+  "runtime_frame_selection_and_clip_slices_aligned": true,
+  "runtime_uses_original_pngs": true,
+  "runtime_validation_scope": "Offline loader and frame/clip indexing helpers; no model or judge calls."
+}

extract_frames.py

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+#!/usr/bin/env python3
+"""Extract every frame from the released 1 FPS videos, without media hosting."""
+
+import argparse
+import hashlib
+import json
+import shutil
+import struct
+import subprocess
+import tempfile
+from concurrent.futures import ThreadPoolExecutor
+from fractions import Fraction
+from pathlib import Path
+
+
+def sha256(path):
+    digest = hashlib.sha256()
+    with path.open("rb") as handle:
+        for block in iter(lambda: handle.read(1024 * 1024), b""):
+            digest.update(block)
+    return digest.hexdigest()
+
+
+def relative_file(root, value):
+    path = Path(value)
+    if path.is_absolute() or ".." in path.parts or "\\" in value:
+        raise ValueError(f"Expected a relative media path: {value}")
+    resolved = (root / path).resolve()
+    if not resolved.is_relative_to(root.resolve()) or not resolved.is_file():
+        raise ValueError(f"Missing media or path outside the dataset: {value}")
+    return resolved
+
+
+def validate_video(path, expected):
+    result = subprocess.run(
+        ["ffprobe", "-v", "error", "-analyzeduration", "0", "-probesize", "32768", "-show_entries",
+         "stream=codec_type,avg_frame_rate,r_frame_rate,nb_frames,duration,start_time",
+         "-of", "json", str(path)],
+        check=True, capture_output=True, text=True, timeout=120,
+    )
+    streams = json.loads(result.stdout)["streams"]
+    if len(streams) != 1 or streams[0]["codec_type"] != "video":
+        raise ValueError(f"Expected one video stream without audio: {path.name}")
+    stream = streams[0]
+    if (Fraction(stream["avg_frame_rate"]) != 1
+            or Fraction(stream["r_frame_rate"]) != 1
+            or int(stream["nb_frames"]) != expected
+            or abs(float(stream["duration"]) - expected) > 0.001
+            or abs(float(stream["start_time"])) > 0.001):
+        raise ValueError(f"Expected a zero-based 1 FPS/{expected}-frame video: {path.name}")
+
+
+def decode_video(source, dest, expected):
+    """Decode a validated video into ordered PNGs, replacing its frame cache."""
+    dest.parent.mkdir(parents=True, exist_ok=True)
+    names = [f"frame_{i:03d}.png" for i in range(expected)]
+    with tempfile.TemporaryDirectory(prefix=source.stem + "-", dir=dest.parent) as temp:
+        temp = Path(temp)
+        subprocess.run(
+            ["ffmpeg", "-nostdin", "-v", "error", "-xerror", "-threads", "1",
+             "-i", str(source), "-map", "0:v:0", "-vsync", "0",
+             "-threads", "1", "-start_number", "0", str(temp / "frame_%03d.png")],
+            check=True, capture_output=True, timeout=300,
+        )
+        actual = sorted(p.name for p in temp.glob("*.png"))
+        if actual != names or any((temp / name).stat().st_size == 0 for name in names):
+            raise ValueError(f"Decoded frame count mismatch: {source.name}")
+        if dest.exists():
+            shutil.rmtree(dest)
+        temp.rename(dest)
+    return expected
+
+
+def validate_frame_cache(root, record, video_info):
+    """Reject cached PNGs that do not belong to the registered video bytes."""
+    video = video_info["path"]
+    n = video_info["n_frames"]
+    if (record["video"] != video or record["video_sha256"] != video_info["sha256"]
+            or record["n_frames"] != n or record["fps"] != 1
+            or type(record["width"]) is not int or record["width"] <= 0
+            or type(record["height"]) is not int or record["height"] <= 0
+            or len(record["frames"]) != n):
+        raise ValueError(f"Frame manifest does not match the video: {video}")
+    directory = Path("runtime/frames") / Path(video).stem
+    expected = [f"frame_{i:03d}.png" for i in range(n)]
+    if sorted(p.name for p in (root / directory).glob("*.png")) != expected:
+        raise ValueError(f"Cached frame count or filenames are incorrect: {video}")
+    for i, frame in enumerate(record["frames"]):
+        if frame["index"] != i or frame["path"] != str(directory / expected[i]):
+            raise ValueError(f"Cached frame order is incorrect: {video}")
+        path = relative_file(root, frame["path"])
+        if path.stat().st_size != frame["bytes"] or sha256(path) != frame["sha256"]:
+            raise ValueError(f"Cached frame checksum mismatch: {frame['path']}")
+        with path.open("rb") as handle:
+            header = handle.read(24)
+        if (len(header) != 24 or header[:8] != b"\x89PNG\r\n\x1a\n"
+                or header[12:16] != b"IHDR"
+                or struct.unpack(">II", header[16:24]) != (record["width"], record["height"])):
+            raise ValueError(f"Cached PNG dimensions differ from frames.jsonl: {frame['path']}")
+
+
+def extract(root, output_dir, videos=None, workers=4):
+    """Validate and decode registered videos; no QA or remote services required."""
+    protected = (root / "runtime/frames").resolve()
+    output = output_dir.resolve()
+    if output.is_relative_to(protected) or protected.is_relative_to(output):
+        raise ValueError("Decoded MP4 frames must not overwrite the original-resolution benchmark frames")
+    records = [json.loads(line) for line in (root / "media.jsonl").read_text(encoding="utf-8").splitlines() if line.strip()]
+    inventory = {record["path"]: record for record in records}
+    if not inventory or len(inventory) != len(records):
+        raise ValueError("Media inventory must be nonempty and contain unique paths")
+    selected = list(dict.fromkeys(videos)) if videos else list(inventory)
+    unknown = set(selected) - set(inventory)
+    if unknown:
+        raise ValueError(f"Videos absent from media.jsonl: {sorted(unknown)}")
+    stems = [Path(path).stem for path in selected]
+    if len(set(stems)) != len(stems):
+        raise ValueError("Video filenames must have unique stems for frame directories")
+    # Check destinations before starting any decode or replacing any frame cache.
+    for relative in selected:
+        source = relative_file(root, relative)
+        dest = output_dir / source.stem
+        if dest.is_symlink():
+            raise ValueError(f"Frame output must not be a symlink: {dest.name}")
+        resolved = dest.resolve()
+        if root.resolve().is_relative_to(resolved) or (root / "media").resolve().is_relative_to(resolved):
+            raise ValueError("Frame output must not replace the dataset or media directory")
+
+    def process(relative):
+        source = relative_file(root, relative)
+        record = inventory[relative]
+        if record["fps"] != 1 or type(record["n_frames"]) is not int or record["n_frames"] < 1:
+            raise ValueError(f"Expected 1 FPS and a positive frame count: {relative}")
+        if source.stat().st_size != record["bytes"] or sha256(source) != record["sha256"]:
+            raise ValueError(f"Video checksum mismatch: {relative}")
+        validate_video(source, record["n_frames"])
+        return decode_video(source, output_dir / source.stem, record["n_frames"])
+
+    with ThreadPoolExecutor(max_workers=workers) as pool:
+        counts = list(pool.map(process, selected))
+    return {"videos": len(selected), "frames": sum(counts)}
+
+
+def main():
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument("--data-root", type=Path, default=Path(__file__).resolve().parent)
+    parser.add_argument("--output-dir", type=Path, help="Output directory; default: DATA_ROOT/runtime/decoded_frames")
+    parser.add_argument("--video", action="append", help="A video path from media.jsonl, e.g. media/0000.mp4; repeat to select more")
+    parser.add_argument("--workers", type=int, default=4)
+    args = parser.parse_args()
+    if args.workers < 1:
+        parser.error("--workers must be positive")
+    root = args.data_root.resolve()
+    output = args.output_dir.resolve() if args.output_dir else root / "runtime/decoded_frames"
+    print(json.dumps(extract(root, output, args.video, args.workers)))
+
+
+if __name__ == "__main__":
+    main()

media.jsonl

@@ -0,0 +1,293 @@
+{"path": "media/0000.mp4", "bytes": 1904512, "sha256": "557782540a8bcdac005da8770669a77f23317c97479ba7ab0c84b7987ce724c2", "fps": 1, "n_frames": 128, "width": 512, "height": 288}
+{"path": "media/0001.mp4", "bytes": 3805364, "sha256": "0fdd691230ec8ea7dc549c9b2180f67f80456ae2bfd0167f73910da044005abf", "fps": 1, "n_frames": 128, "width": 512, "height": 288}
+{"path": "media/0002.mp4", "bytes": 3793390, "sha256": "cacec74ec1c4736d11395b66871f0fc5ac6b777888ae4a8a09dd340666dd0e22", "fps": 1, "n_frames": 128, "width": 512, "height": 288}
+{"path": "media/0003.mp4", "bytes": 3775853, "sha256": "f9110137cf694f4b121e54e2013eb22f5c3d5ffac62bf9fc7c8c6360a108df0b", "fps": 1, "n_frames": 128, "width": 512, "height": 320}
+{"path": "media/0004.mp4", "bytes": 2369755, "sha256": "6d2c0458f5a905a08395ff90f981ff7dc72d66693a8510a3cd43cf1099caddf0", "fps": 1, "n_frames": 128, "width": 512, "height": 288}
+{"path": "media/0005.mp4", "bytes": 1957595, "sha256": "9d5b90eda2a866c5540b0ab351e1d770087e05d2e97707b9c20365ec0f3b345f", "fps": 1, "n_frames": 128, "width": 512, "height": 288}
+{"path": "media/0006.mp4", "bytes": 1130523, "sha256": "d5694ac31643945249d4882a8f77cb1eb9de417b41724831ba61f03a12a207bc", "fps": 1, "n_frames": 128, "width": 512, "height": 260}
+{"path": "media/0007.mp4", "bytes": 1803093, "sha256": "71dc4ad2c0a7fbc0f6bbc683f04af823f51e2ac5665ff0a9ad7222ad330e3eff", "fps": 1, "n_frames": 128, "width": 512, "height": 288}
+{"path": "media/0008.mp4", "bytes": 3138219, "sha256": "876f038a60990d0baf9bc4ca4e83d8356e3198ade560267f3292ca56963716b6", "fps": 1, "n_frames": 128, "width": 512, "height": 288}
+{"path": "media/0009.mp4", "bytes": 1890099, "sha256": "2ddfe14e238d646c91dc014c46df0feb7df5072ce32b96c454a4f528e476a631", "fps": 1, "n_frames": 128, "width": 512, "height": 288}
+{"path": "media/0010.mp4", "bytes": 2608275, "sha256": "849bff7804b03a81d348c5d71c9d49ae3335695ff8328345bb9d1b479e9ee450", "fps": 1, "n_frames": 128, "width": 512, "height": 288}
+{"path": "media/0011.mp4", "bytes": 4329230, "sha256": "0703057be4bfcbf64092344fb3b6ac5b194d87263185564dd033c085467cad69", "fps": 1, "n_frames": 128, "width": 512, "height": 288}
+{"path": "media/0012.mp4", "bytes": 1409006, "sha256": "aa1517ba20d368ad4b1eaf2048d66cc15db9669ee485fe9c798eb13beb23ca93", "fps": 1, "n_frames": 128, "width": 512, "height": 288}
+{"path": "media/0013.mp4", "bytes": 1737272, "sha256": "45282aded49b80f79d2f1a730426faf1e4ee8067bb292457bcb9f1d13a93b3bd", "fps": 1, "n_frames": 128, "width": 512, "height": 288}
+{"path": "media/0014.mp4", "bytes": 3689786, "sha256": "7628db9696b325f265d146e428c45b5b2cd1a45ab6d600f959e0c8ed77d14419", "fps": 1, "n_frames": 128, "width": 512, "height": 288}
+{"path": "media/0015.mp4", "bytes": 3246565, "sha256": "c2cdf3640e1125ec7f385b46764ab8feac33f1875275dfd8152b9e47bdc307d0", "fps": 1, "n_frames": 128, "width": 512, "height": 288}
+{"path": "media/0016.mp4", "bytes": 1812288, "sha256": "b72d74c4b180dcae31a08cce6c656644c5e60ab18c24a9cb928d24504c6659d6", "fps": 1, "n_frames": 128, "width": 512, "height": 288}
+{"path": "media/0017.mp4", "bytes": 2568708, "sha256": "b4867c034d4ce7bd51a16d6d1ffa8098cdf2b653dd243b753703d068f2bc9ba5", "fps": 1, "n_frames": 108, "width": 512, "height": 288}
+{"path": "media/0018.mp4", "bytes": 1243945, "sha256": "347ebf31cd45a7fb1e19f80737b7d480717bb4980be7f88357dd88d0449450f1", "fps": 1, "n_frames": 128, "width": 512, "height": 288}
+{"path": "media/0019.mp4", "bytes": 1415287, "sha256": "6c61945b20b8706b445bc77fff7c84e09854155b190226628a99767a94dc0c2c", "fps": 1, "n_frames": 128, "width": 512, "height": 288}
+{"path": "media/0020.mp4", "bytes": 3291904, "sha256": "e7d2210e3e8995fbd68bc33aa139e13a4cd8bb416bc211a3ae2d72215b314df3", "fps": 1, "n_frames": 128, "width": 512, "height": 288}
+{"path": "media/0021.mp4", "bytes": 1412284, "sha256": "4c8099152e12d28fad7ca42b87d1a52e36b4e2cb8d208b683b8b855adbba11e6", "fps": 1, "n_frames": 128, "width": 512, "height": 288}
+{"path": "media/0022.mp4", "bytes": 2051568, "sha256": "158e1e74a676f02388ab651940a1252509b47a9b5a92570dea491ce3771e2c2b", "fps": 1, "n_frames": 128, "width": 512, "height": 288}
+{"path": "media/0023.mp4", "bytes": 3103665, "sha256": "e364d791d918d1af3cf5692c893e5b7f727411d9e9c1f50a5bd74d6f57c098de", "fps": 1, "n_frames": 128, "width": 512, "height": 288}
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prepare.py

@@ -0,0 +1,100 @@
+#!/usr/bin/env python3
+"""Verify the released videos and original-resolution frames for inference."""
+
+import argparse
+import csv
+import json
+from concurrent.futures import ThreadPoolExecutor
+from pathlib import Path
+from urllib.parse import quote, urlsplit
+
+from extract_frames import relative_file, sha256, validate_frame_cache, validate_video
+
+
+def load_rows(root):
+    rows = [json.loads(line) for line in (root / "test.jsonl").read_text(encoding="utf-8").splitlines() if line.strip()]
+    if not rows or len({row["id"] for row in rows}) != len(rows):
+        raise ValueError("Sample IDs must be unique and the dataset must be nonempty")
+    for row in rows:
+        if (not isinstance(row["id"], str) or not row["id"].isdigit()
+                or str(int(row["id"])) != row["id"]):
+            raise ValueError("Sample IDs must be canonical nonnegative integer strings")
+        if any(not isinstance(row[key], str) or not row[key].strip() for key in ("question", "answer")):
+            raise ValueError("Question and answer must be nonempty strings")
+        if row["fps"] != 1 or type(row["n_frames"]) is not int or row["n_frames"] < 1:
+            raise ValueError("Expected 1 FPS and a positive integer n_frames")
+        relative_file(root, row["video"])
+    return rows
+
+
+def prepare(root, rows, base_url, workers, verify_only=False):
+    inventory = {
+        row["path"]: row
+        for row in map(json.loads, (root / "media.jsonl").read_text(encoding="utf-8").splitlines())
+    }
+    unique = {}
+    for row in rows:
+        if row["video"] in unique and unique[row["video"]]["n_frames"] != row["n_frames"]:
+            raise ValueError("Conflicting frame counts for the same video")
+        unique[row["video"]] = row
+
+    records = [json.loads(line) for line in (root / "frames.jsonl").read_text(encoding="utf-8").splitlines() if line.strip()]
+    cached_frames = {record["video"]: record for record in records}
+    if len(cached_frames) != len(records) or not set(unique).issubset(cached_frames):
+        raise ValueError("Frame manifest must contain unique entries covering all requested videos")
+
+    def process(row):
+        source = relative_file(root, row["video"])
+        info = inventory[row["video"]]
+        if sha256(source) != info["sha256"] or source.stat().st_size != info["bytes"]:
+            raise ValueError(f"Video checksum mismatch: {row['video']}")
+        if info["n_frames"] != row["n_frames"]:
+            raise ValueError("Media inventory and sample frame counts disagree")
+        validate_video(source, row["n_frames"])
+        validate_frame_cache(root, cached_frames[row["video"]], info)
+
+    with ThreadPoolExecutor(max_workers=workers) as pool:
+        list(pool.map(process, unique.values()))
+    if verify_only:
+        return {"samples": len(rows), "videos": len(unique), "frames": sum(row["n_frames"] for row in unique.values()), "verified": True}
+
+    def url(relative):
+        return base_url.rstrip("/") + "/" + quote(relative, safe="/")
+
+    runtime = root / "runtime"
+    with (runtime / "video.csv").open("w", newline="", encoding="utf-8") as handle:
+        writer = csv.DictWriter(handle, fieldnames=["index", "question", "answer"])
+        writer.writeheader()
+        writer.writerows({"index": row["id"], "question": row["question"], "answer": row["answer"]} for row in rows)
+    with (runtime / "video_manifest.jsonl").open("w", encoding="utf-8") as handle:
+        for row in rows:
+            n = row["n_frames"]
+            record = {
+                "case_id": row["id"], "ok": True, "modality": "video",
+                "video_url": url(row["video"]), "n_frames": n, "grid_fps": 1.0,
+                "duration": float(n), "frame_indices": list(range(n)),
+                "frame_urls": [url(f"runtime/frames/{Path(row['video']).stem}/frame_{i:03d}.png") for i in range(n)],
+            }
+            handle.write(json.dumps(record) + "\n")
+    return {"samples": len(rows), "videos": len(unique), "manifest": "runtime/video_manifest.jsonl"}
+
+
+def main():
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument("--data-root", type=Path, default=Path(__file__).resolve().parent)
+    parser.add_argument("--media-base-url", help="HTTP(S) base URL serving the entire dataset directory")
+    parser.add_argument("--workers", type=int, default=4)
+    parser.add_argument("--verify-only", action="store_true", help="Verify video and original-resolution PNG checksums without preparing inference inputs")
+    args = parser.parse_args()
+    if args.workers < 1:
+        parser.error("--workers must be positive")
+    if not args.verify_only:
+        parsed = urlsplit(args.media_base_url or "")
+        if parsed.scheme not in ("http", "https") or not parsed.netloc or parsed.query or parsed.fragment or parsed.username:
+            parser.error("--media-base-url must be an HTTP(S) directory URL without credentials, query or fragment")
+    root = args.data_root.resolve()
+    print(json.dumps(prepare(root, load_rows(root), args.media_base_url, args.workers, args.verify_only)))
+
+
+if __name__ == "__main__":
+    main()

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+size 841949529

video-frames-00001.zip

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video-frames-00002.zip

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+size 7697145322