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| # test | |
| import numpy as np | |
| import albumentations as A | |
| from src.utils import get_images_list, load_image, load_augmentations_config | |
| def test_get_images_list(): | |
| images_list = get_images_list("images") | |
| assert isinstance(images_list, list) | |
| assert len(images_list) > 0 | |
| assert isinstance(images_list[0], str) | |
| def test_load_image(): | |
| images_list = get_images_list("images") | |
| for image_name in images_list: | |
| image = load_image(image_name, path_to_folder="images", bgr2rgb=True) | |
| assert len(image.shape) == 3, f"error in {image_name}" | |
| assert image.shape[2] == 3, f"error in {image_name}" | |
| assert image.max() <= 255, f"error in {image_name}" | |
| assert image.min() >= 0, f"error in {image_name}" | |
| def test_load_augmentations_config(): | |
| image = np.random.randint(0, 255, (100, 100, 3)).astype(np.uint8) | |
| placeholder_params = { | |
| "image_width": image.shape[1], | |
| "image_height": image.shape[0], | |
| "image_half_width": int(image.shape[1] / 2), | |
| "image_half_height": int(image.shape[0] / 2), | |
| } | |
| augmentations = load_augmentations_config( | |
| placeholder_params, path_to_config="configs/augmentations.json" | |
| ) | |
| for transform_name in augmentations.keys(): | |
| if transform_name in [ | |
| "CenterCrop", | |
| "RandomCrop", | |
| "RandomResizedCrop", | |
| "Resize", | |
| ]: | |
| param_values = {"p": 1.0, "height": 10, "width": 10} | |
| elif transform_name in ["RandomSizedCrop"]: | |
| param_values = { | |
| "p": 1.0, | |
| "height": 10, | |
| "width": 10, | |
| "min_max_height": (50, 50), | |
| } | |
| elif transform_name in ["Crop"]: | |
| param_values = {"p": 1.0, "x_max": 10, "y_max": 10} | |
| else: | |
| param_values = {"p": 1.0} | |
| transform = getattr(A, transform_name)(**param_values) | |
| transformed_image = transform(image=image)["image"] | |
| assert len(transformed_image.shape) == 3, f"error in {str(transform)}" | |
| assert transformed_image.shape[2] == 3, f"error in {str(transform)}" | |
| assert transformed_image.max() <= 255, f"error in {str(transform)}" | |
| assert transformed_image.min() >= 0, f"error in {str(transform)}" | |