def __call__()

in src/chug/image/transforms_torch.py [0:0]

• 8 lines of code
• 3 McCabe index (conditional complexity)

    def __call__(self, img):
        kernel_size = self.get_params(self.scale)
        if isinstance(img, torch.Tensor):
            padding = kernel_size // 2
            img = torch.nn.functional.max_pool2d(img, kernel_size=kernel_size, stride=1, padding=padding)
        elif isinstance(img, Image.Image):
            img = img.filter(ImageFilter.MaxFilter(kernel_size))
        return img