| import tempfile |
|
|
| import cv2 |
| import numpy as np |
| import pytest |
| from PIL import Image |
|
|
| INPUT_HEIGHT, INPUT_WIDTH = 600, 500 |
|
|
|
|
| @pytest.mark.parametrize('dtype,extension,dim', [ |
| (np.uint8, '.png', 1), |
| (np.uint8, '.jpg', 3), |
| (np.uint8, '.png', 1), |
| (np.uint16, '.png', 1), |
| (np.uint16, '.jpg', 1), |
| (np.float32, '.tiff', 1), |
| (np.uint8, '.tiff', 3), |
| ] |
| ) |
| def test_image_reader(dtype, extension, dim): |
| tf = tempfile.NamedTemporaryFile(suffix=extension) |
|
|
| if dtype in [np.uint8, np.uint16]: |
| image_w = np.random.randint(0, 225, (225, 225, dim)).astype(dtype) |
| else: |
| image_w = np.random.rand(225, 225, dim).astype(dtype) |
|
|
| if dim == 1: |
| image_w = np.squeeze(image_w) |
| cv2.imwrite(tf.name, image_w) |
|
|
| image_r = np.array(Image.open(tf.name)) |
| image_r = cv2.normalize( |
| image_r, None, 0, 255, cv2.NORM_MINMAX, dtype=cv2.CV_8U) |
| image_r = cv2.resize( |
| image_r, (INPUT_WIDTH, INPUT_HEIGHT), interpolation=cv2.INTER_LINEAR) |
|
|
| assert image_r.dtype == np.uint8 |
| assert image_r.shape[:2] == (INPUT_HEIGHT, INPUT_WIDTH) |
| assert np.min(image_r) >= 0 and np.max(image_r) <= 255 |
|
|
