add makeup imgs

README.md

@@ -36,6 +36,33 @@ If you do not wish to train the model, you can download [our pre-trained model](
 # evaluate using GPU
 python test.py
 ```
-
+
+## Face makeup using parsing maps
+[**face-makeup.PyTorch**](https://github.com/zllrunning/face-makeup.PyTorch)
+<table>
+
+<tr>
+<th>&nbsp;</th>
+<th>Hair</th>
+<th>Lip</th>
+</tr>
+
+<!-- Line 1: Original Input -->
+<tr>
+<td><em>Original Input</em></td>
+<td><img src="res/makeup/116_ori.png" height="256" width="256" alt="Original Input"></td>
+<td><img src="res/makeup/116_lip_ori.png" height="256" width="256" alt="Original Input"></td>
+</tr>
+
+<!-- Line 3: Color -->
+<tr>
+<td>Color</td>
+<td><img src="res/makeup/116_1.png" height="256" width="256" alt="Color"></td>
+<td><img src="res/makeup/116_3.png" height="256" width="256" alt="Color"></td>
+</tr>
+
+</table>
+
+
 ## References
 - [BiSeNet](https://github.com/CoinCheung/BiSeNet)

makeup.py

@@ -0,0 +1,130 @@
+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 = 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()
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+

test.py

@@ -43,6 +43,7 @@ def vis_parsing_maps(im, parsing_anno, stride, save_im=False, save_path='vis_res
 
     # Save result or not
     if save_im:
+        cv2.imwrite(save_path[:-4] +'.png', vis_parsing_anno)
         cv2.imwrite(save_path, vis_im, [int(cv2.IMWRITE_JPEG_QUALITY), 100])
 
     # return vis_im