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63 lines
1.9 KiB
Python
63 lines
1.9 KiB
Python
"""
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PyTest's for Digital Image Processing
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"""
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import digital_image_processing.edge_detection.canny as canny
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import digital_image_processing.filters.gaussian_filter as gg
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import digital_image_processing.filters.median_filter as med
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import digital_image_processing.filters.sobel_filter as sob
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import digital_image_processing.filters.convolve as conv
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import digital_image_processing.change_contrast as cc
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from cv2 import imread, cvtColor, COLOR_BGR2GRAY
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from numpy import array, uint8
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from PIL import Image
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img = imread(r"digital_image_processing/image_data/lena_small.jpg")
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gray = cvtColor(img, COLOR_BGR2GRAY)
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# Test: change_contrast()
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def test_change_contrast():
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with Image.open("digital_image_processing/image_data/lena_small.jpg") as img:
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# Work around assertion for response
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assert str(cc.change_contrast(img, 110)).startswith(
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"<PIL.Image.Image image mode=RGB size=100x100 at"
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)
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# canny.gen_gaussian_kernel()
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def test_gen_gaussian_kernel():
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resp = canny.gen_gaussian_kernel(9, sigma=1.4)
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# Assert ambiguous array
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assert resp.all()
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# canny.py
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def test_canny():
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canny_img = imread("digital_image_processing/image_data/lena_small.jpg", 0)
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# assert ambiguos array for all == True
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assert canny_img.all()
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canny_array = canny.canny(canny_img)
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# assert canny array for at least one True
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assert canny_array.any()
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# filters/gaussian_filter.py
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def test_gen_gaussian_kernel_filter():
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assert gg.gaussian_filter(gray, 5, sigma=0.9).all()
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def test_convolve_filter():
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# laplace diagonals
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Laplace = array([[0.25, 0.5, 0.25], [0.5, -3, 0.5], [0.25, 0.5, 0.25]])
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res = conv.img_convolve(gray, Laplace).astype(uint8)
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assert res.any()
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def test_median_filter():
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assert med.median_filter(gray, 3).any()
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def test_sobel_filter():
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grad, theta = sob.sobel_filter(gray)
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assert grad.any() and theta.any()
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