|
| 1 | +""" |
| 2 | + Implemented an algorithm using opencv to tone an image with sepia technic |
| 3 | +""" |
| 4 | + |
| 5 | +from cv2 import imread, imshow, waitKey, destroyAllWindows |
| 6 | + |
| 7 | + |
| 8 | +def make_sepia(img, factor: int): |
| 9 | + pixel_h, pixel_v = img.shape[0], img.shape[1] |
| 10 | + |
| 11 | + def to_grayscale(blue, green, red): |
| 12 | + """ |
| 13 | + Helper function to create pixel's greyscale representation |
| 14 | + Src: https://pl.wikipedia.org/wiki/YUV |
| 15 | + """ |
| 16 | + return 0.2126 * red + 0.587 * green + 0.114 * blue |
| 17 | + |
| 18 | + def normalize(value): |
| 19 | + """ Helper function to normalize R/G/B value -> return 255 if value > 255""" |
| 20 | + return value if value <= 255 else 255 |
| 21 | + |
| 22 | + for i in range(pixel_h): |
| 23 | + for j in range(pixel_v): |
| 24 | + greyscale = int(to_grayscale(*img[i][j])) |
| 25 | + img[i][j] = [ |
| 26 | + normalize(greyscale), |
| 27 | + normalize(greyscale + factor), |
| 28 | + normalize(greyscale + 2 * factor), |
| 29 | + ] |
| 30 | + |
| 31 | + return img |
| 32 | + |
| 33 | + |
| 34 | +if __name__ == "__main__": |
| 35 | + # read original image |
| 36 | + img = imread("image_data/lena.jpg", 1) |
| 37 | + img1 = imread("image_data/lena.jpg", 1) |
| 38 | + img2 = imread("image_data/lena.jpg", 1) |
| 39 | + img3 = imread("image_data/lena.jpg", 1) |
| 40 | + |
| 41 | + # convert with sepia with different factor's value |
| 42 | + sepia_10 = make_sepia(img, 10) |
| 43 | + sepia_20 = make_sepia(img1, 20) |
| 44 | + sepia_30 = make_sepia(img2, 30) |
| 45 | + sepia_40 = make_sepia(img3, 40) |
| 46 | + |
| 47 | + # show result images |
| 48 | + imshow("Original image with sepia (factor: 10)", img) |
| 49 | + imshow("Original image with sepia (factor: 20)", img1) |
| 50 | + imshow("Original image with sepia (factor: 30)", img2) |
| 51 | + imshow("Original image with sepia (factor: 40)", img3) |
| 52 | + waitKey(0) |
| 53 | + destroyAllWindows() |
0 commit comments