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| import numpy as np | |
| import cv2 | |
| from PIL import Image | |
| def read_file(source_image, target_image): | |
| s = cv2.cvtColor(source_image, cv2.COLOR_RGB2LAB) | |
| t = cv2.cvtColor(np.array(target_image), cv2.COLOR_RGB2LAB) | |
| return s, t | |
| def get_mean_and_std(x): | |
| x_mean, x_std = cv2.meanStdDev(x) | |
| x_mean = np.hstack(np.around(x_mean,2)) | |
| x_std = np.hstack(np.around(x_std,2)) | |
| return x_mean, x_std | |
| def color_transfer(source, target_image): | |
| """ | |
| The primary goal of this algorithm is to adjust the colors of the source image | |
| such that its color distribution looks like the distribution of the target image. | |
| """ | |
| s, t = read_file(source, target_image) | |
| s_mean, s_std = get_mean_and_std(s) | |
| t_mean, t_std = get_mean_and_std(t) | |
| height, width, channel = s.shape | |
| for i in range(0,height): | |
| for j in range(0,width): | |
| for k in range(0,channel): | |
| x = s[i,j,k] | |
| x = ((x-s_mean[k])*(t_std[k]/s_std[k]))+t_mean[k] | |
| # round or +0.5 | |
| x = round(x) | |
| # boundary check | |
| x = 0 if x<0 else x | |
| x = 255 if x>255 else x | |
| s[i,j,k] = x | |
| s = cv2.cvtColor(s,cv2.COLOR_LAB2BGR) | |
| cv2.imwrite('result.jpg',s) | |
| def rgb_to_hex(rgb): | |
| return '#{:02x}{:02x}{:02x}'.format(rgb[0], rgb[1], rgb[2]) | |
| def hex_to_rgb(hex): | |
| hex = hex.lstrip('#') | |
| return tuple(int(hex[i:i+2], 16) for i in (0, 2, 4)) | |
| def create_color_palette(colors, palette_width=800, palette_height=200): | |
| """ | |
| Receives a list of colors in hex format and creates a palette image | |
| """ | |
| pixels = [] | |
| n_colors = len(colors) | |
| for i in range(n_colors): | |
| color = hex_to_rgb(colors[i]) | |
| for j in range(palette_width//n_colors * palette_height): | |
| pixels.append(color) | |
| img = Image.new('RGB', (palette_height, palette_width)) | |
| img.putdata(pixels) | |
| # img.show() | |
| return img | |
| # colors = ['#d54b18', '#555015', '#98680e', '#1f3919', '#da8007', '#a50637', '#b50406', '#d52350', '#e2090f', '#f8545c'] | |
| # img = create_color_palette(colors) | |
| # color_transfer('s2', img) | |
| def recolor(source, colors): | |
| palette_img = create_color_palette(colors) | |
| palette_bgr = cv2.cvtColor(np.array(palette_img), cv2.COLOR_RGB2BGR) | |
| source_bgr = cv2.cvtColor(source, cv2.COLOR_RGB2BGR) | |
| recolored = color_transfer(source_bgr, palette_bgr) | |
| return recolored |