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makeup.py
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makeup.py
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import cv2
import os
import numpy as np
from skimage.filters import gaussian
def sharpen(img):
img = img * 1.0
gauss_out = gaussian(img, sigma=5, multichannel=True)
alpha = 1.5
img_out = (img - gauss_out) * alpha + img
img_out = img_out / 255.0
mask_1 = img_out < 0
mask_2 = img_out > 1
img_out = img_out * (1 - mask_1)
img_out = img_out * (1 - mask_2) + mask_2
img_out = np.clip(img_out, 0, 1)
img_out = img_out * 255
return np.array(img_out, dtype=np.uint8)
def hair(image, parsing, part=17, color=[230, 50, 20]):
b, g, r = color #[10, 50, 250] # [10, 250, 10]
tar_color = np.zeros_like(image)
tar_color[:, :, 0] = b
tar_color[:, :, 1] = g
tar_color[:, :, 2] = r
image_hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
tar_hsv = cv2.cvtColor(tar_color, cv2.COLOR_BGR2HSV)
if part == 12 or part == 13:
image_hsv[:, :, 0:2] = tar_hsv[:, :, 0:2]
else:
image_hsv[:, :, 0:1] = tar_hsv[:, :, 0:1]
changed = cv2.cvtColor(image_hsv, cv2.COLOR_HSV2BGR)
if part == 17:
changed = sharpen(changed)
changed[parsing != part] = image[parsing != part]
# changed = cv2.resize(changed, (512, 512))
return changed
#
# def lip(image, parsing, part=17, color=[230, 50, 20]):
# b, g, r = color #[10, 50, 250] # [10, 250, 10]
# tar_color = np.zeros_like(image)
# tar_color[:, :, 0] = b
# tar_color[:, :, 1] = g
# tar_color[:, :, 2] = r
#
# image_lab = cv2.cvtColor(image, cv2.COLOR_BGR2Lab)
# il, ia, ib = cv2.split(image_lab)
#
# tar_lab = cv2.cvtColor(tar_color, cv2.COLOR_BGR2Lab)
# tl, ta, tb = cv2.split(tar_lab)
#
# image_lab[:, :, 0] = np.clip(il - np.mean(il) + tl, 0, 100)
# image_lab[:, :, 1] = np.clip(ia - np.mean(ia) + ta, -127, 128)
# image_lab[:, :, 2] = np.clip(ib - np.mean(ib) + tb, -127, 128)
#
#
# changed = cv2.cvtColor(image_lab, cv2.COLOR_Lab2BGR)
#
# if part == 17:
# changed = sharpen(changed)
#
# changed[parsing != part] = image[parsing != part]
# # changed = cv2.resize(changed, (512, 512))
# return changed
if __name__ == '__main__':
# 1 face
# 10 nose
# 11 teeth
# 12 upper lip
# 13 lower lip
# 17 hair
num = 1
table = {
'hair': 17,
'upper_lip': 12,
'lower_lip': 13
}
image_path = 'C:\\Users\\USER\\Desktop\\Forms\\face-parsing.PyTorch\\TaskData\\Real\\{}.png'.format(num)
parsing_path = 'res/test_res/{}.png'.format(num)
image = cv2.imread(image_path)
ori = image.copy()
parsing = np.array(cv2.imread(parsing_path, 0))
parsing = cv2.resize(parsing, image.shape[0:2], interpolation=cv2.INTER_NEAREST)
parts = [table['hair'], table['upper_lip'], table['lower_lip']]
# colors = [[20, 20, 200], [100, 100, 230], [100, 100, 230]]
colors = [[100, 200, 100]]
for part, color in zip(parts, colors):
image = hair(image, parsing, part, color)
cv2.imwrite('res/makeup/116_ori.png', cv2.resize(ori, (512, 512)))
cv2.imwrite('res/makeup/116_2.png', cv2.resize(image, (512, 512)))
cv2.imshow('image', cv2.resize(ori, (512, 512)))
cv2.imshow('color', cv2.resize(image, (512, 512)))
# cv2.imshow('image', ori)
# cv2.imshow('color', image)
cv2.waitKey(0)
cv2.destroyAllWindows()