context_encoder.py 文件源码

def mask_randomly(self, imgs):
        y1 = np.random.randint(0, self.img_rows - self.mask_height, imgs.shape[0])
        y2 = y1 + self.mask_height
        x1 = np.random.randint(0, self.img_rows - self.mask_width, imgs.shape[0])
        x2 = x1 + self.mask_width

        masked_imgs = np.empty_like(imgs)
        missing_parts = np.empty((imgs.shape[0], self.mask_height, self.mask_width, self.channels))
        for i, img in enumerate(imgs):
            masked_img = img.copy()
            _y1, _y2, _x1, _x2 = y1[i], y2[i], x1[i], x2[i]
            missing_parts[i] = masked_img[_y1:_y2, _x1:_x2, :].copy()
            masked_img[_y1:_y2, _x1:_x2, :] = 0
            masked_imgs[i] = masked_img

        return masked_imgs, missing_parts, (y1, y2, x1, x2)