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README.md
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# Video-Progress Benchmark Release
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Video-Progress Benchmark is a benchmark for long-horizon robot manipulation
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## Contents
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bash scripts/extract_vlac2_release_raw_archives.sh
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```
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This extracts `data/train_videos.tar` and `data/test_videos.tar` into `data/`.
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To extract the raw videos elsewhere, pass a target directory:
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python scripts/extract_vlac2_release_frames.py --data-root data
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```
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By default, extracted frames are written to `_extracted_frames/` under the release directory.
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If the raw videos were extracted elsewhere:
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### 3. Use the benchmark splits
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The benchmark JSON files are
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Frame paths in the JSON files use the prefix:
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__VLAC2_FRAMES_ROOT__/
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```
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Replace `__VLAC2_FRAMES_ROOT__` with the absolute path to the extracted-frame directory.
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For example, if frames are extracted to:
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* `test_nonexpert_seen`
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* `test_nonexpert_unseen`
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The test splits are intended for evaluation only.
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## Dependencies
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A video decoder backend is required for frame extraction. Install one of:
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```bash
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pip install opencv-python
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## Notes
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* This repository
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* The full raw-data release is distributed separately.
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* The benchmark JSON files are
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* The raw-video archives and extracted-frame cache are separated so that users can regenerate frames under their own storage layout.
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# Video-Progress Benchmark Release
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Video-Progress Benchmark is a benchmark for evaluating progress prediction in long-horizon robot manipulation. This release provides the benchmark split files, the minimal subset of raw videos required by the benchmark protocol, and a frame-extraction workflow for reproducible evaluation.
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## Contents
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bash scripts/extract_vlac2_release_raw_archives.sh
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```
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This command extracts `data/train_videos.tar` and `data/test_videos.tar` into `data/`, while preserving the relative directory structure expected by the benchmark release.
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To extract the raw videos elsewhere, pass a target directory:
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python scripts/extract_vlac2_release_frames.py --data-root data
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```
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By default, extracted frames are written to `_extracted_frames/` under the release directory. The extractor materializes only the benchmark-designated main camera stream.
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If the raw videos were extracted elsewhere:
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### 3. Use the benchmark splits
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The benchmark JSON files are pre-generated and can be used directly. No benchmark reconstruction is required.
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Frame paths in the JSON files use the prefix:
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__VLAC2_FRAMES_ROOT__/
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```
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Replace `__VLAC2_FRAMES_ROOT__` with the absolute path to the extracted-frame directory produced by the frame-extraction step.
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For example, if frames are extracted to:
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* `test_nonexpert_seen`
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* `test_nonexpert_unseen`
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The four test splits are intended for evaluation only.
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## Dependencies
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A video decoder backend is required for frame extraction. Install one of the following:
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```bash
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pip install opencv-python
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## Notes
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* This repository contains only the raw videos required by the released benchmark splits.
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* The full raw-data release is distributed separately.
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* The benchmark JSON files are canonical release artifacts and do not need to be rebuilt.
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* The raw-video archives and the extracted-frame cache are intentionally separated so that users can regenerate frames under their own storage layout.
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