mirror of
https://github.com/TheAlgorithms/Python.git
synced 2024-11-24 05:21:09 +00:00
5933cd4d83
* Add sepia tone * Add unit test * technic --> technique * Update digital_image_processing/sepia.py Co-Authored-By: Christian Clauss <cclauss@me.com> * Update digital_image_processing/sepia.py Co-Authored-By: Christian Clauss <cclauss@me.com> * Fixed errors after commit changes * Fixed errors Co-authored-by: Christian Clauss <cclauss@me.com>
49 lines
1.4 KiB
Python
49 lines
1.4 KiB
Python
"""
|
|
Implemented an algorithm using opencv to tone an image with sepia technique
|
|
"""
|
|
|
|
from cv2 import imread, imshow, waitKey, destroyAllWindows
|
|
|
|
|
|
def make_sepia(img, factor: int):
|
|
""" Function create sepia tone. Source: https://en.wikipedia.org/wiki/Sepia_(color) """
|
|
pixel_h, pixel_v = img.shape[0], img.shape[1]
|
|
|
|
def to_grayscale(blue, green, red):
|
|
"""
|
|
Helper function to create pixel's greyscale representation
|
|
Src: https://pl.wikipedia.org/wiki/YUV
|
|
"""
|
|
return 0.2126 * red + 0.587 * green + 0.114 * blue
|
|
|
|
def normalize(value):
|
|
""" Helper function to normalize R/G/B value -> return 255 if value > 255"""
|
|
return min(value, 255)
|
|
|
|
for i in range(pixel_h):
|
|
for j in range(pixel_v):
|
|
greyscale = int(to_grayscale(*img[i][j]))
|
|
img[i][j] = [
|
|
normalize(greyscale),
|
|
normalize(greyscale + factor),
|
|
normalize(greyscale + 2 * factor),
|
|
]
|
|
|
|
return img
|
|
|
|
|
|
if __name__ == "__main__":
|
|
# read original image
|
|
images = {
|
|
percentage: imread("image_data/lena.jpg", 1) for percentage in (10, 20, 30, 40)
|
|
}
|
|
|
|
for percentage, img in images.items():
|
|
make_sepia(img, percentage)
|
|
|
|
for percentage, img in images.items():
|
|
imshow(f"Original image with sepia (factor: {percentage})", img)
|
|
|
|
waitKey(0)
|
|
destroyAllWindows()
|