Function extract_save_all_maps

deeplabcut/compat.py:1747–1869

Extracts the scoremap, location refinement field and part affinity field prediction of the model. The maps will be rescaled to the size of the input image and stored in the corresponding model folder in /evaluation-results. ---------- config : string Full path of the config

(
    config,
    shuffle: int = 1,
    trainingsetindex: int = 0,
    comparison_bodyparts: str | list[str] = "all",
    extract_paf: bool = True,
    all_paf_in_one: bool = True,
    gputouse: int | None = None,
    device: str | None = None,
    rescale: bool = False,
    Indices: list[int] | None = None,
    modelprefix: str = "",
    dest_folder: str = None,
    snapshot_index: int | str | None = None,
    detector_snapshot_index: int | str | None = None,
    engine: Engine | None = None,
)

@renamed_parameter(old="comparisonbodyparts", new="comparison_bodyparts", since="3.0.0")
def extract_save_all_maps(
    config,
    shuffle: int = 1,
    trainingsetindex: int = 0,
    comparison_bodyparts: str | list[str] = "all",
    extract_paf: bool = True,
    all_paf_in_one: bool = True,
    gputouse: int | None = None,
    device: str | None = None,
    rescale: bool = False,
    Indices: list[int] | None = None,
    modelprefix: str = "",
    dest_folder: str = None,
    snapshot_index: int | str | None = None,
    detector_snapshot_index: int | str | None = None,
    engine: Engine | None = None,
):
    """
    Extracts the scoremap, location refinement field and part affinity field prediction of the model. The maps
    will be rescaled to the size of the input image and stored in the corresponding model folder in /evaluation-results.

    ----------
    config : string
        Full path of the config.yaml file as a string.

    shuffle: integer
        integers specifying shuffle index of the training dataset. The default is 1.

    trainingsetindex: int, optional
        Integer specifying which TrainingsetFraction to use.
        By default the first (note that TrainingFraction is a list in config.yaml).
        This variable can also be set to "all".

    comparison_bodyparts: list of bodyparts, Default is "all".
        The average error will be computed for those body parts only (Has to be a subset of the body parts).

    extract_paf : bool
        Extract part affinity fields by default.
        Note that turning it off will make the function much faster.

    all_paf_in_one : bool
        By default, all part affinity fields are displayed on a single frame.
        If false, individual fields are shown on separate frames.

    gputouse: int or None, optional, default=None
        For the TensorFlow engine (for the PyTorch engine see ``device``). Specifies
        the GPU to use (see number in ``nvidia-smi``). If you do not have a GPU put
        ``None``. See: https://nvidia.custhelp.com/app/answers/detail/a_id/3751/~/useful-nvidia-smi-queries

    device: str or None, optional, default=None
        The CUDA device to use for training. If None, the device will be taken from the
        ``pytorch_config.yaml`` file. Examples: {"cpu", "cuda", "cuda:0", "cuda:1"}. See
        https://pytorch.org/docs/stable/notes/cuda.html for more information.

    Indices: default None
        For which images shall the scmap/locref and paf be computed? Give a list of images

    nplots_per_row: int, optional (default=None)