Duplicate from HBOrtiz/eval3_track3_vl_pairs

Co-authored-by: Hans Baumann-Ortiz <HBOrtiz@users.noreply.huggingface.co>

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+*tfevents* filter=lfs diff=lfs merge=lfs -text
+# Audio files - uncompressed
+*.pcm filter=lfs diff=lfs merge=lfs -text
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+# Audio files - compressed
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README.md

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+# eval3_track3_vl_pairs (v3 — image↔label mispairing fixed)
+
+ObjectVLA-style vision-language co-training data for the **Track 3 TOY** 3-celeb Eval 3 task. v3 fixes a critical bug where ~98% of rows had `image_path` pointing to a frame extracted from a different episode than the row's labels described.
+
+Companion to [`HBOrtiz/so101_eval3_track3_v3_baseline`](https://huggingface.co/datasets/HBOrtiz/so101_eval3_track3_v3_baseline).
+
+## What changed vs prior pushes
+
+**Bug fix** (v3): Earlier builders keyed video lookups by enumeration index in their own filtered ep_metadata list, but `ep_to_videos` was keyed by the merged-dataset's `episode_index` (a different index space — assigned by `merge_track3_custom.discover() = sorted(base) + sorted(aug)`). The builder filter selected 151 base teleops vs the merger's 178, shifting every subsequent index. Result: ~98% of rows mispaired.
+
+v3 replicates `merge_track3_custom.discover()` exactly to produce the canonical episode-name list (length 9394 = merger's `episode_index` order), then joins per-episode metadata by NAME. Result: every JPEG is now extracted from the episode whose labels the row carries.
+
+The 27 base teleops without `portrait_corners.json` caches are skipped (no usable bbox geometry available for them).
+
+## Contents
+
+- **`manifest.parquet`** — 56 202 VL pair rows (9 367 episodes × 3 portraits × 2 caption types).
+- **`data.tar.zst`** — `images/chunk-*/<episode>__f0000.jpg` + `references/<episode>__ref.jpg`. Extract with `tar --zstd -xf data.tar.zst`.
+- **`_stats.json`** — counts + refit success rate.
+
+## Schema
+
+| column | type | meaning |
+|---|---|---|
+| `image_path` | str | wrist-cam frame 0 JPEG (480 × 640) for the named episode |
+| `reference_image_path` | str | reference photo (480 × 480) for the episode |
+| `prompt` | str | input prompt (uses 8-number flat quad for grounded type) |
+| `target` | str | expected completion |
+| `quad_corners_norm` | list[4][2] | 4 (x, y) corners of the printed paper, normalized [0,1]. Preserves rotation. Always 4 distinct corners (sub-pixel refined when available, coarse minAreaRect fallback otherwise) |
+| `bbox_refit_ok` | bool | True iff `refine_paper_quad_to_edges` produced valid sub-pixel corners; False = coarse fallback |
+| `celeb_name` | str | "Yann LeCun" / "Barack Obama" / "Taylor Swift" |
+| `celeb_slug` | str | slug form |
+| `caption_type` | str | `"location_explicit"` or `"qa_grounded"` |
+| `episode` | str | episode name (matches the merged-dataset episode for that index) |
+| `episode_index` | int | merger's episode_index (consistent across `HBOrtiz/so101_eval3_track3_v3_baseline`) |
+| `frame_idx` | int | always `0` |
+| `pid` | int | portrait id (0, 1, 2) |
+
+## Caption types
+
+**`location_explicit`** — prompt=`"What is in this image?"`, target=`"The printed photo of <name> is at [x1,y1,x2,y2,x3,y3,x4,y4]."`
+**`qa_grounded`** — prompt=`"Who is in the printed photo at [x1,y1,x2,y2,x3,y3,x4,y4]?"`, target=`"<name>"`
+
+The 8 numbers in the prompts/targets are the flat list of the 4 quad corners (preserves rotation, unlike axis-aligned xyxy).
+
+## Stats
+
+- 3 unique celebs: Yann LeCun, Barack Obama, Taylor Swift
+- 9 367 episodes (178 base + 9 216 aug − 27 cacheless base)
+- 56 202 VL pairs
+- 78.9 % `bbox_refit_ok=True` (sub-pixel refined corners)
+- 21.1 % `bbox_refit_ok=False` (coarse minAreaRect fallback — still 4 distinct corners)
+
+## Loading
+
+```python
+import subprocess
+from huggingface_hub import hf_hub_download
+import pyarrow.parquet as pq
+
+tar = hf_hub_download("HBOrtiz/eval3_track3_vl_pairs", "data.tar.zst", repo_type="dataset")
+subprocess.run(["tar", "--zstd", "-xf", tar])
+
+manifest = pq.read_table(hf_hub_download(
+    "HBOrtiz/eval3_track3_vl_pairs", "manifest.parquet", repo_type="dataset"
+)).to_pandas()
+```

_stats.json

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+{
+  "n_records": 56202,
+  "n_unique_celebs": 3,
+  "n_unique_episodes": 9367,
+  "n_unique_images": 9367,
+  "n_refit_ok": 44330,
+  "pct_refit_ok": 78.9,
+  "n_canonical_skipped_no_meta": 27,
+  "n_canonical_skipped_no_video": 0,
+  "wall_seconds": 270.2,
+  "bug_fix": "v3 \u2014 image\u2194label mispairing fixed via NAME-keyed video lookup"
+}

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manifest.parquet

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