Spaces:
Running
on
Zero
Running
on
Zero
File size: 3,329 Bytes
ad88a0b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 |
import cv2
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 = 116
table = {
'hair': 17,
'upper_lip': 12,
'lower_lip': 13
}
image_path = '/home/zll/data/CelebAMask-HQ/test-img/{}.jpg'.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()
|