Module `facetorch.analyzer.detector.pre`

Classes

class BaseDetPreProcessor (transform: torchvision.transforms.transforms.Compose, device: torch.device, optimize_transform: bool)

Base class for detector pre processors.

All detector pre processors should subclass it. All subclass should overwrite:

Methods:run, used for running the processing

Args

device : torch.device: Torch device cpu or cuda.
transform : transforms.Compose: Transform compose object to be applied to the image.
optimize_transform : bool: Whether to optimize the transform.

Expand source code

class BaseDetPreProcessor(BaseProcessor):
    @Timer(
        "BaseDetPreProcessor.__init__",
        "{name}: {milliseconds:.2f} ms",
        logger=logger.debug,
    )
    def __init__(
        self,
        transform: transforms.Compose,
        device: torch.device,
        optimize_transform: bool,
    ):
        """Base class for detector pre processors.

        All detector pre processors should subclass it.
        All subclass should overwrite:

        - Methods:``run``, used for running the processing

        Args:
            device (torch.device): Torch device cpu or cuda.
            transform (transforms.Compose): Transform compose object to be applied to the image.
            optimize_transform (bool): Whether to optimize the transform.

        """
        super().__init__(transform, device, optimize_transform)

    @abstractmethod
    def run(self, data: ImageData) -> ImageData:
        """Abstract method that runs the detector pre processing functionality.
        Returns a batch of preprocessed face tensors.

        Args:
            data (ImageData): ImageData object containing the image tensor.

        Returns:
            ImageData: ImageData object containing the image tensor preprocessed for the detector.

        """

Ancestors

BaseProcessor

Subclasses

DetectorPreProcessor

Methods

def run(self, data: ImageData) ‑> ImageData

Abstract method that runs the detector pre processing functionality. Returns a batch of preprocessed face tensors.

Args

data : ImageData: ImageData object containing the image tensor.

Returns

ImageData: ImageData object containing the image tensor preprocessed for the detector.

Inherited members

BaseProcessor:
- optimize

class DetectorPreProcessor (transform: torchvision.transforms.transforms.Compose, device: torch.device, optimize_transform: bool, reverse_colors: bool)

Initialize the detector preprocessor.

Args

transform : Compose: Composed Torch transform object.
device : torch.device: Torch device cpu or cuda.
optimize_transform : bool: Whether to optimize the transform.
reverse_colors : bool: Whether to reverse the colors of the image tensor from RGB to BGR or vice versa. If False, the colors remain unchanged.

Expand source code

class DetectorPreProcessor(BaseDetPreProcessor):
    @Timer(
        "DetectorPreProcessor.__init__",
        "{name}: {milliseconds:.2f} ms",
        logger=logger.debug,
    )
    def __init__(
        self,
        transform: transforms.Compose,
        device: torch.device,
        optimize_transform: bool,
        reverse_colors: bool,
    ):
        """Initialize the detector preprocessor.

        Args:
            transform (Compose): Composed Torch transform object.
            device (torch.device): Torch device cpu or cuda.
            optimize_transform (bool): Whether to optimize the transform.
            reverse_colors (bool): Whether to reverse the colors of the image tensor from RGB to BGR or vice versa. If False, the colors remain unchanged.

        """
        super().__init__(transform, device, optimize_transform)
        self.reverse_colors = reverse_colors

    @Timer(
        "DetectorPreProcessor.run", "{name}: {milliseconds:.2f} ms", logger=logger.debug
    )
    def run(self, data: ImageData) -> ImageData:
        """Run the detector preprocessor on the image tensor in BGR format and return the transformed image tensor.

        Args:
            data (ImageData): ImageData object containing the image tensor.

        Returns:
            ImageData: ImageData object containing the preprocessed image tensor.
        """
        if data.tensor.device != self.device:
            data.tensor = data.tensor.to(self.device)

        data.tensor = self.transform(data.tensor)

        if self.reverse_colors:
            data.tensor = rgb2bgr(data.tensor)

        return data

Ancestors

Methods

def run(self, data: ImageData) ‑> ImageData

Run the detector preprocessor on the image tensor in BGR format and return the transformed image tensor.

Args

data : ImageData: ImageData object containing the image tensor.

Returns

ImageData: ImageData object containing the preprocessed image tensor.

Inherited members

BaseDetPreProcessor:
- optimize