dekker.one
Group work for a Monash Research Methods course
Merge remote-tracking branch 'origin/master'
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mini_proj/_cutter.py
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mini_proj/_cutter.py
···
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dims = image.shape
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assert dims[0] >= size0
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assert dims[1] >= size1
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return np.array([image[size0 * i:size0 * (i+1), size1 * j:size1 * (j+1)] \
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return np.array([image[size0 * i:size0 * (i+1), size1 * j:size1 * (j+1), :] \
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for i in range(dims[0] // size0) for j in range(dims[1] // size1)] + \
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[image[size0 * i:size0 * (i+1), dims[1]-size1:] \
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for i in range(dims[0] // size0) if dims[1] % size1 != 0] + \
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[image[dims[0]-size0:, size1 * j:size1 * (j+1)] \
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for j in range(dims[1] // size1) if dims[0] % size0 != \
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for j in range(dims[1] // size1) if dims[0] % size0 != 0] \
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)
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if __name__ == '__main__':
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# test = np.random.rand(5,4,3)
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test = np.array([[
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k + 4*j for k in range(4)
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[k + 4*j, k + 4*j] for k in range(4)
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] for j in range(5)])
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print(test)
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print(image_cut(test, 2, 2))
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mini_proj/report/waldo.tex
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mini_proj/report/waldo.tex