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1922e5b 7677e5f 1922e5b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 | # RoboSteer Level3 preprocessing assets
English | [中文说明](README.zh-CN.md)
This folder releases three Level3 assets as portable tables and a reconstruction tool. It is independent of the sibling `level1/` assets. The original server paths and video symlinks are not distributed.
## Assets
| Folder | Contents | Reconstructed layout |
|---|---|---|
| `text_audio_instructions/` | 17,575 UTF-8 instructions across 7,764 tasks, including original audio/text modality and order | `<task_id>/<item_id>__text.txt` or `__audio.txt` |
| `video_symlinks/` | 8,475 video references with paths relative to a user-provided public-data root, byte sizes and SHA-256 | `<item_id>.mp4` |
| `interleaved_input_list_for_GEM/` | 26,050 ordered items: 17,575 text items and 8,475 video references | `<task_id>/order_NNN.txt` or `.mp4` |
No raw audio transcripts, audio files, image assets or video bytes are included. The audio-origin instructions are processed motion instructions, not raw Whisper transcripts. The original GEM preparation skipped 7,764 image items. Original order numbers are preserved, including gaps left by skipped images.
`release_manifest.json` records the comparison between the grouped text and the actual GEM text. If differences exist, `text_overrides.parquet` preserves them for exact reconstruction; the grouped instruction table remains unchanged.
## Download
```bash
pip install huggingface_hub pyarrow
hf download PhoebeCC/RoboSteer-Preprocessing \
--repo-type dataset --include 'level3/*' --local-dir ./RoboSteer-Preprocessing
```
For reproducibility, add `--revision <commit-id>` using the commit of the Level3 release.
## External video dependency
Prepare the matching RoboSteer public data locally:
```text
<public-root>/
└── Data_Processed/Level3/Video_Slices/
└── <original segment filename>.mp4
```
The release identifies every required video using `source_relpath`, `source_size` and `source_sha256`. A matching folder layout alone is insufficient: each video must also match its recorded bytes. This release does not download or regenerate the original media.
## Reconstruct the three original assets
```bash
python RoboSteer-Preprocessing/level3/scripts/materialize_level3.py \
--public-root /data/public \
--output-root ./restored_level3 \
--video-mode symlink
```
The result is:
```text
restored_level3/
├── text_audio_instructions/
├── video_symlinks/
└── interleaved_input_list_for_GEM/
```
This reproduces the selected assets directly under the output root. To match the organized project layout, pass `--output-root /path/to/cxt/level3/inputs` instead. Use a new output directory for initial validation.
The tool verifies release checksums and all source videos before writing. It writes exact UTF-8 text bytes, including existing newlines. It does not overwrite conflicting files. Existing matching files are accepted. Missing or different source videos produce a JSON error report on stdout and exit code 2. Conflicting or missing reconstructed outputs in verification mode produce exit code 3. Original input videos remain untouched.
Use `--video-mode copy` if symlinks are unavailable. This copies video bytes into both video layouts and therefore uses additional disk space. Default symlinks point to the supplied local public-data root; moving that root later requires rebuilding them.
Verify the restored assets:
```bash
python RoboSteer-Preprocessing/level3/scripts/materialize_level3.py \
--public-root /data/public \
--output-root ./restored_level3 \
--verify-only
```
Verification checks all expected entries; it does not remove or reject unrelated extra files. It does not run GEM or evaluate video decoding or instruction quality.
## Read the tables directly
```python
import pyarrow.parquet as pq
instructions = pq.read_table(
"RoboSteer-Preprocessing/level3/text_audio_instructions/data.parquet"
).to_pylist()
```
- Instructions: `item_id`, `task_id`, `order`, `source_modality`, `file_name`, `text`, `sha256`.
- Videos: `item_id`, `task_id`, `order`, `file_name`, `source_relpath`, `source_size`, `source_sha256`.
- GEM items: `task_id`, `item_id`, `order`, `file_name`, `kind`, `sha256`, `source_relpath` (null for text). Text is joined by `item_id`; optional overrides take precedence only for GEM reconstruction.
`file_name` is relative to its reconstructed asset directory. Media paths are relative to `--public-root`, never to the HF cache. The video table contains references, not embedded `Video` objects; viewing it on Hugging Face does not make external videos playable.
## Validation and provenance
The text was exported from the existing Level3 preprocessing outputs. Video references were taken from the original symlink targets, and the task/order layout from the actual GEM input directories. Text and video integrity are recorded as SHA-256; no historical processing `status` values were reused as quality labels.
See `release_manifest.json`, `validation.json` and `SHA256SUMS`. The reconstruction utility requires Python 3.9+ and pyarrow. The release does not include Qwen/Whisper/GEM models, logs, server credentials, or raw absolute server paths. Dataset terms and upstream media conditions should be consulted at the repository and source-data level.
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