| # OCR |
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| The primary artifact is `ocr.jsonl` còn `artifact_metadata.jsonl` records the input, model, prompt version, subset, and Git lineage |
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| ## `ocr.jsonl` |
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| Each line is one `OCRFragment`, a visible text region in one keyframe. |
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| Common fields: |
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| - `fragment_id`: OCR observation identifier |
| - `video_id`: source video identifier |
| - `time_span`: `[timestamp_ms, timestamp_ms]` in source video time |
| - `text`: recognized visible text |
| - `bbox`: normalized text region with `x_min`, `y_min`, `x_max`, and `y_max` |
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| There is no placeholder for frames without text and no fabricated confidence score. Join OCR with captions or detections on `video_id` and timestamp; compare normalized bounding boxes when spatial context is needed. |
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| ## Generation flow |
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| HunyuanOCR reads the canonical keyframe images, emits visible text regions, and the job validates each result as an `OCRFragment`. It publishes one flat JSONL file and removes provider work files and the retired bundled OCR representation after a successful run. |
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| Run OCR for the original keyframe set: |
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| ```bash |
| make data-ocr INPUT=/data/aic/shared/artifacts/keyframes/keyframes.jsonl OUTPUT=/data/aic/shared/artifacts/ocr SUBSET=700vid |
| ``` |
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