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name: "data-preparation" description: "Prepare raw videos and annotations for the 3D-ResNets-PyTorch dataset loaders." disable-model-invocation: true metadata: disco-role: operating license: MIT

Data preparation

Use this sub-skill when a user needs raw videos converted into the directory and JSON formats consumed by 3D-ResNets-PyTorch. For downstream training, validation, or inference flags after data is prepared, route to training-and-inference; for top-level routing, return to the root skill.

Fast routing

User needs	Open/use
Extract RGB JPEG frames from Kinetics, ActivityNet, UCF101, HMDB51, or Moments in Time videos	scripts/extract_video_frames.py, then workflows
Convert raw RGB videos to HDF5 files	scripts/extract_video_hdf5.py, then workflows
Build Kinetics/UCF101/HMDB51/MIT annotation JSON files	scripts/build_annotation_json.py, then data formats
Add missing ActivityNet fps fields	build_annotation_json.py activitynet-add-fps, then ActivityNet workflow
Diagnose missing videos, empty loaders, flow/jpg assertions, or long HDF5 names	troubleshooting

Core rules to preserve

• Prepared JPEG layout is normally <video_root>/<label>/<video_id>/image_00001.jpg; ActivityNet raw extraction is flat and produces <video_root>/v_<id>/image_00001.jpg.
• Prepared RGB HDF5 layout is normally <video_root>/<label>/<video_id>.hdf5 with a variable-length byte dataset named video. The bundled HDF5 extractor does not create optical-flow datasets.
• --file_type jpg must be paired with --input_type rgb. The repository asserts that flow is supported only when --file_type hdf5, and flow HDF5 must contain video_u and video_v datasets prepared elsewhere.
• For frame-directory annotations, segments are one-based half-open ranges such as [1, n_frames + 1]. For RGB HDF5 annotations, use zero-based half-open ranges [0, n_frames].
• ActivityNet JSON must have per-video fps values before the ActivityNet loader can convert time segments to frame indices.

Bundled scripts

Run scripts from this sub-skill directory or call them by path:

python scripts/extract_video_frames.py -h
python scripts/extract_video_hdf5.py -h
python scripts/build_annotation_json.py -h
python scripts/build_annotation_json.py kinetics -h
python scripts/build_annotation_json.py activitynet-add-fps -h

The scripts are self-contained adaptations of the repository utilities; they do not import from or link to the source checkout.