Module facetorch.analyzer.utilizer.save

Classes

class ImageSaver (transform: torchvision.transforms.transforms.Compose,
device: torch.device,
optimize_transform: bool)
Expand source code 
class ImageSaver(BaseUtilizer):
    def __init__(
        self,
        transform: transforms.Compose,
        device: torch.device,
        optimize_transform: bool,
    ):
        """Initializes the ImageSaver class. This class is used to save the image tensor to an image file.

        Args:
            transform (Compose): Composed Torch transform object.
            device (torch.device): Torch device cpu or cuda object.
            optimize_transform (bool): Whether to optimize the transform.

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

    @Timer("ImageSaver.run", "{name}: {milliseconds:.2f} ms", logger=logger.debug)
    def run(self, data: ImageData) -> ImageData:
        """Saves the image tensor to an image file, if the path_output attribute of ImageData is not None.

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

        Returns:
            ImageData: ImageData object containing the same data as the input.
        """
        if data.path_output is not None:
            os.makedirs(os.path.dirname(data.path_output), exist_ok=True)
            pil_image = torchvision.transforms.functional.to_pil_image(data.img)
            pil_image.save(data.path_output)

        return data

Initializes the ImageSaver class. This class is used to save the image tensor to an image file.

Args

transform : Compose
Composed Torch transform object.
device : torch.device
Torch device cpu or cuda object.
optimize_transform : bool
Whether to optimize the transform.

Ancestors

Methods

def run(self,
data: ImageData) ‑> ImageData
Expand source code 
@Timer("ImageSaver.run", "{name}: {milliseconds:.2f} ms", logger=logger.debug)
def run(self, data: ImageData) -> ImageData:
    """Saves the image tensor to an image file, if the path_output attribute of ImageData is not None.

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

    Returns:
        ImageData: ImageData object containing the same data as the input.
    """
    if data.path_output is not None:
        os.makedirs(os.path.dirname(data.path_output), exist_ok=True)
        pil_image = torchvision.transforms.functional.to_pil_image(data.img)
        pil_image.save(data.path_output)

    return data

Saves the image tensor to an image file, if the path_output attribute of ImageData is not None.

Args

data : ImageData
ImageData object containing the img tensor.

Returns

ImageData
ImageData object containing the same data as the input.

Inherited members