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Rename functions to use snake case

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This commit is contained in:
Tianyi Zheng 2023-01-07 01:18:18 -08:00
parent d0ca630533
commit b0debde359
1 changed files with 11 additions and 11 deletions
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22
digital_image_processing/morphological_operations/erosion_operation.py
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@ -2,32 +2,32 @@ import numpy as np
from PIL import Image
def rgb2gray(rgb: np.ndarray) -> np.ndarray:
def rgb_to_gray(rgb: np.ndarray) -> np.ndarray:
"""
Return gray image from rgb image
>>> rgb2gray(np.array([[[127, 255, 0]]]))
>>> rgb_to_gray(np.array([[[127, 255, 0]]]))
array([[187.6453]])
>>> rgb2gray(np.array([[[0, 0, 0]]]))
>>> rgb_to_gray(np.array([[[0, 0, 0]]]))
array([[0.]])
>>> rgb2gray(np.array([[[2, 4, 1]]]))
>>> rgb_to_gray(np.array([[[2, 4, 1]]]))
array([[3.0598]])
>>> rgb2gray(np.array([[[26, 255, 14], [5, 147, 20], [1, 200, 0]]]))
>>> rgb_to_gray(np.array([[[26, 255, 14], [5, 147, 20], [1, 200, 0]]]))
array([[159.0524, 90.0635, 117.6989]])
"""
r, g, b = rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2]
return 0.2989 * r + 0.5870 * g + 0.1140 * b
def gray2binary(gray: np.ndarray) -> np.ndarray:
def gray_to_binary(gray: np.ndarray) -> np.ndarray:
"""
Return binary image from gray image
>>> gray2binary(np.array([[127, 255, 0]]))
>>> gray_to_binary(np.array([[127, 255, 0]]))
array([[False, True, False]])
>>> gray2binary(np.array([[0]]))
>>> gray_to_binary(np.array([[0]]))
array([[False]])
>>> gray2binary(np.array([[26.2409, 4.9315, 1.4729]]))
>>> gray_to_binary(np.array([[26.2409, 4.9315, 1.4729]]))
array([[False, False, False]])
>>> gray2binary(np.array([[26, 255, 14], [5, 147, 20], [1, 200, 0]]))
>>> gray_to_binary(np.array([[26, 255, 14], [5, 147, 20], [1, 200, 0]]))
array([[False, True, False],
[False, True, False],
[False, True, False]])
@ -67,7 +67,7 @@ if __name__ == "__main__":
# kernel to be applied
structuring_element = np.array([[0, 1, 0], [1, 1, 1], [0, 1, 0]])
# Apply erosion operation to a binary image
output = erosion(gray2binary(rgb2gray(lena)), structuring_element)
output = erosion(gray_to_binary(rgb_to_gray(lena)), structuring_element)
# Save the output image
pil_img = Image.fromarray(output).convert("RGB")
pil_img.save("result_erosion.png")