Module facetorch.analyzer.utilizer.save
Classes
class ImageSaver (transform: torchvision.transforms.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.
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 dataAncestors
Methods
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.
Inherited members