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