Class ImgDataPreprocessor

mmengine/model/base_model/data_preprocessor.py:154–308

Image pre-processor for normalization and bgr to rgb conversion. Accepts the data sampled by the dataloader, and preprocesses it into the format of the model input. ``ImgDataPreprocessor`` provides the basic data pre-processing as follows - Collates and moves data to the target dev

@MODELS.register_module()
class ImgDataPreprocessor(BaseDataPreprocessor):
    """Image pre-processor for normalization and bgr to rgb conversion.

    Accepts the data sampled by the dataloader, and preprocesses it into the
    format of the model input. ``ImgDataPreprocessor`` provides the
    basic data pre-processing as follows

    - Collates and moves data to the target device.
    - Converts inputs from bgr to rgb if the shape of input is (3, H, W).
    - Normalizes image with defined std and mean.
    - Pads inputs to the maximum size of current batch with defined
      ``pad_value``. The padding size can be divisible by a defined
      ``pad_size_divisor``
    - Stack inputs to batch_inputs.

    For ``ImgDataPreprocessor``, the dimension of the single inputs must be
    (3, H, W).

    Note:
        ``ImgDataPreprocessor`` and its subclass is built in the
        constructor of :class:`BaseDataset`.

    Args:
        mean (Sequence[float or int], optional): The pixel mean of image
            channels. If ``bgr_to_rgb=True`` it means the mean value of R,
            G, B channels. If the length of `mean` is 1, it means all
            channels have the same mean value, or the input is a gray image.
            If it is not specified, images will not be normalized. Defaults
            None.
        std (Sequence[float or int], optional): The pixel standard deviation of
            image channels. If ``bgr_to_rgb=True`` it means the standard
            deviation of R, G, B channels. If the length of `std` is 1,
            it means all channels have the same standard deviation, or the
            input is a gray image.  If it is not specified, images will
            not be normalized. Defaults None.
        pad_size_divisor (int): The size of padded image should be
            divisible by ``pad_size_divisor``. Defaults to 1.
        pad_value (float or int): The padded pixel value. Defaults to 0.
        bgr_to_rgb (bool): whether to convert image from BGR to RGB.
            Defaults to False.
        rgb_to_bgr (bool): whether to convert image from RGB to RGB.
            Defaults to False.
        non_blocking (bool): Whether block current process
            when transferring data to device.
            New in version v0.3.0.

    Note:
        if images do not need to be normalized, `std` and `mean` should be
        both set to None, otherwise both of them should be set to a tuple of
        corresponding values.
    """

    def __init__(self,
                 mean: Optional[Sequence[Union[float, int]]] = None,
                 std: Optional[Sequence[Union[float, int]]] = None,
                 pad_size_divisor: int = 1,
                 pad_value: Union[float, int] = 0,
                 bgr_to_rgb: bool = False,