datasets.py 文件源码

def transform(self, images):
        if self._aug_flag:
            transformed_images =\
                np.zeros([images.shape[0], self._imsize, self._imsize, 3])
            ori_size = images.shape[1]
            for i in range(images.shape[0]):
                h1 = np.floor((ori_size - self._imsize) * np.random.random())
                w1 = np.floor((ori_size - self._imsize) * np.random.random())
                cropped_image =\
                    images[i][w1: w1 + self._imsize, h1: h1 + self._imsize, :]
                if random.random() > 0.5:
                    transformed_images[i] = np.fliplr(cropped_image)
                else:
                    transformed_images[i] = cropped_image
            return transformed_images
        else:
            return images