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recognition

recognition

This skill provides ST-GCN skeleton action-recognition model, graph, configuration, checkpoint, and CLI guidance while routing data and pose concerns to their owning skills.

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Skill documentation

GitHub

name: recognition description: "This skill provides ST-GCN skeleton action-recognition model, graph, configuration, checkpoint, and CLI guidance while routing data and pose concerns to their owning skills." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Recognition

Use this sub-skill when a user needs the repository's ST_GCN_18 model, graph layout/strategy selection, recognition train/test configuration construction, pretrained-checkpoint alias selection, mmskl argument binding, or model input/output shape guidance.

  • Read API reference for constructor contracts, graph layouts, adjacency strategies, and tensor shapes.
  • Read CLI and configuration reference for recognition train/test patterns, flags, batch/GPU behavior, and config-path handling.
  • Read model zoo reference for checkpoint aliases and the no-download boundary.
  • Run the tiny ST-GCN smoke for a bounded, download-free import/graph/forward check. It asserts finite output and the requested (N, num_class) shape; it is not training or evaluation.
  • Use troubleshooting for CUDA/compiler, graph/class-count, data/checkpoint, CLI, and native-NMS gates.

Scope and routing

This sub-skill covers the recognition model and its application wiring. Route JSON schema, annotation validation, loader/transforms, and axis conversion to the data-preparation skill. Route video input, MMDetection, HRNet, and pose extraction to the pose-estimation skill; successful ST-GCN construction does not establish detector or video readiness.

The smoke deliberately creates synthetic input and never downloads data or a checkpoint. Do not claim a complete training/evaluation run or downloaded checkpoint verification from this sub-skill.

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