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490e645ed3
* updating DIRECTORY.md
* types(maths): Fix pylance issues in maths
* reset(vsc): Reset settings changes
* Update maths/jaccard_similarity.py
Co-authored-by: Tianyi Zheng <tianyizheng02@gmail.com>
* revert(erosion_operation): Revert erosion_operation
* test(jaccard_similarity): Add doctest to test alternative_union
* types(newton_raphson): Add typehints to func bodies
---------
Co-authored-by: github-actions <${GITHUB_ACTOR}@users.noreply.github.com>
Co-authored-by: Tianyi Zheng <tianyizheng02@gmail.com>
76 lines
2.5 KiB
Python
76 lines
2.5 KiB
Python
import numpy as np
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from PIL import Image
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def rgb2gray(rgb: np.array) -> np.array:
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"""
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Return gray image from rgb image
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>>> rgb2gray(np.array([[[127, 255, 0]]]))
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array([[187.6453]])
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>>> rgb2gray(np.array([[[0, 0, 0]]]))
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array([[0.]])
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>>> rgb2gray(np.array([[[2, 4, 1]]]))
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array([[3.0598]])
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>>> rgb2gray(np.array([[[26, 255, 14], [5, 147, 20], [1, 200, 0]]]))
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array([[159.0524, 90.0635, 117.6989]])
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"""
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r, g, b = rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2]
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return 0.2989 * r + 0.5870 * g + 0.1140 * b
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def gray2binary(gray: np.array) -> np.array:
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"""
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Return binary image from gray image
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>>> gray2binary(np.array([[127, 255, 0]]))
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array([[False, True, False]])
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>>> gray2binary(np.array([[0]]))
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array([[False]])
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>>> gray2binary(np.array([[26.2409, 4.9315, 1.4729]]))
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array([[False, False, False]])
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>>> gray2binary(np.array([[26, 255, 14], [5, 147, 20], [1, 200, 0]]))
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array([[False, True, False],
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[False, True, False],
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[False, True, False]])
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"""
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return (gray > 127) & (gray <= 255)
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def erosion(image: np.array, kernel: np.array) -> np.array:
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"""
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Return eroded image
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>>> erosion(np.array([[True, True, False]]), np.array([[0, 1, 0]]))
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array([[False, False, False]])
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>>> erosion(np.array([[True, False, False]]), np.array([[1, 1, 0]]))
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array([[False, False, False]])
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"""
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output = np.zeros_like(image)
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image_padded = np.zeros(
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(image.shape[0] + kernel.shape[0] - 1, image.shape[1] + kernel.shape[1] - 1)
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)
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# Copy image to padded image
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image_padded[kernel.shape[0] - 2 : -1 :, kernel.shape[1] - 2 : -1 :] = image
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# Iterate over image & apply kernel
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for x in range(image.shape[1]):
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for y in range(image.shape[0]):
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summation = (
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kernel * image_padded[y : y + kernel.shape[0], x : x + kernel.shape[1]]
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).sum()
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output[y, x] = int(summation == 5)
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return output
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# kernel to be applied
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structuring_element = np.array([[0, 1, 0], [1, 1, 1], [0, 1, 0]])
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if __name__ == "__main__":
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# read original image
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image = np.array(Image.open(r"..\image_data\lena.jpg"))
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# Apply erosion operation to a binary image
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output = erosion(gray2binary(rgb2gray(image)), structuring_element)
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# Save the output image
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pil_img = Image.fromarray(output).convert("RGB")
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pil_img.save("result_erosion.png")
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