transform.py 文件源码

def __call__(self, img):
        img_flip = img.transpose(Image.FLIP_LEFT_RIGHT)
        center_crop = transforms.CenterCrop(self.size)
        img_list = []
        w, h = img.size
        for image in [img, img_flip]:
            img_list.append(center_crop(image))
            img_list.append(image.crop((0, 0, self.size, self.size)))
            img_list.append(image.crop((w-self.size, 0, w, self.size)))
            img_list.append(image.crop((0, h - self.size, self.size, h)))
            img_list.append(image.crop((w-self.size, h-self.size, w, h)))
        imgs = None
        to_tensor = transforms.ToTensor()
        for image in img_list:
            if imgs is None:
                temp_img = to_tensor(image)
                imgs = self.normalize(temp_img)
            else:
                temp_img = to_tensor(image)
                temp_img = self.normalize(temp_img)
                imgs = torch.cat((imgs, temp_img))
        return imgs


# ---------------------------------------------------------------------------------------------
# from: https://github.com/eladhoffer/convNet.pytorch/blob/master/preprocess.py