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Resize image with padding using CV2
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| import cv2 | |
| from typing import Tuple | |
| def resize_with_pad(image: np.array, | |
| new_shape: Tuple[int, int], | |
| padding_color: Tuple[int] = (255, 255, 255)) -> np.array: | |
| """Maintains aspect ratio and resizes with padding. | |
| Params: | |
| image: Image to be resized. | |
| new_shape: Expected (width, height) of new image. | |
| padding_color: Tuple in BGR of padding color | |
| Returns: | |
| image: Resized image with padding | |
| """ | |
| original_shape = (image.shape[1], image.shape[0]) | |
| ratio = float(max(new_shape))/max(original_shape) | |
| new_size = tuple([int(x*ratio) for x in original_shape]) | |
| image = cv2.resize(image, new_size) | |
| delta_w = new_shape[0] - new_size[0] | |
| delta_h = new_shape[1] - new_size[1] | |
| top, bottom = delta_h//2, delta_h-(delta_h//2) | |
| left, right = delta_w//2, delta_w-(delta_w//2) | |
| image = cv2.copyMakeBorder(image, top, bottom, left, right, cv2.BORDER_CONSTANT, value=padding_color) | |
| return image | |
| if __name__ == "__main__": | |
| image = cv2.imread("/path/to/image") | |
| image = resize_with_pad(image, (256, 256)) | |
| cv2.imshow("Padded image", image) | |
| cv2.waitKey() |
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Thank you @IdeaKing !