def dataset_to_policy_features()

in lerobot/common/datasets/utils.py [0:0]

• 24 lines of code
• 11 McCabe index (conditional complexity)

def dataset_to_policy_features(features: dict[str, dict]) -> dict[str, PolicyFeature]:
    # TODO(aliberts): Implement "type" in dataset features and simplify this
    policy_features = {}
    for key, ft in features.items():
        shape = ft["shape"]
        if ft["dtype"] in ["image", "video"]:
            type = FeatureType.VISUAL
            if len(shape) != 3:
                raise ValueError(f"Number of dimensions of {key} != 3 (shape={shape})")

            names = ft["names"]
            # Backward compatibility for "channel" which is an error introduced in LeRobotDataset v2.0 for ported datasets.
            if names[2] in ["channel", "channels"]:  # (h, w, c) -> (c, h, w)
                shape = (shape[2], shape[0], shape[1])
        elif key == "observation.environment_state":
            type = FeatureType.ENV
        elif key.startswith("observation"):
            type = FeatureType.STATE
        elif key.startswith("action"):
            type = FeatureType.ACTION
        else:
            continue

        policy_features[key] = PolicyFeature(
            type=type,
            shape=shape,
        )

    return policy_features