Pepijn 0f6e3230df fix(annotate): decode video frames with PyAV directly ...

``lerobot.datasets.video_utils.decode_video_frames`` routes
``backend="pyav"`` through ``decode_video_frames_torchvision`` →
``torchvision.io.VideoReader``, but ``VideoReader`` was removed in
torchvision >= 0.22 (the vllm/vllm-openai:latest container ships with
torchvision 0.25). That made every Module 3 frame decode raise
``AttributeError: module 'torchvision.io' has no attribute 'VideoReader'``,
which the previous catch-all silently turned into an empty image list,
which then made every Module 3 prompt skip via the
``not _has_image_block(messages)`` branch and produce zero VQA rows.

Bypass ``video_utils`` entirely. The annotation pipeline only needs
a handful of PIL frames per (episode, ts), so a direct PyAV decode is
both simpler and insulated from torchvision API churn. ``av`` is already
in the install set, no new dependency.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

2026-04-30 18:48:36 +02:00

..

lerobot

fix(annotate): decode video frames with PyAV directly

2026-04-30 18:48:36 +02:00