I built a tool that finds silent corruption in robot training datasets. Now it fixes it too.
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That audit became trajlens, an open source lint tool for LeRobot datasets. v0.1 could detect 20+ classes of these problems and give a dataset a trust score. Today I released v0.2. It doesn't just detect anymore. It repairs. What's new Three fixers, one command. pip install trajlens trajlens fix ./my_dataset --out ./my_dataset_repaired --apply timestamp_dedrift rewrites drifted timestamps back to frame_index / fps, matching the exact float32 quantization the detection check uses stats_recompute…
1Key Takeaways
- That audit became trajlens, an open source lint tool for LeRobot datasets.
- v0.1 could detect 20+ classes of these problems and give a dataset a trust score.
- What's new Three fixers, one command.
- pip install trajlens trajlens fix ./my_dataset --out ./my_dataset_repaired --apply timestamp_dedrift rewrites drifted timestamps back to frame_index / fps, matching the exact float32 quantization the detection check uses stats_recompute….
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — ML reports that that audit became trajlens, an open source lint tool for LeRobot datasets.
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