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Python
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# python | |
def beauty_face(img): | |
''' | |
Dest =(Src * (100 - Opacity) + (Src + 2 * GuassBlur(EPFFilter(Src) - Src + 128) - 256) * Opacity) /100 ; | |
https://my.oschina.net/wujux/blog/1563461 | |
''' | |
dst = np.zeros_like(img) | |
#int value1 = 3, value2 = 1; 磨皮程度与细节程度的确定 | |
v1 = 3 | |
v2 = 1 | |
dx = v1 * 5 # 双边滤波参数之一 | |
fc = v1 * 12.5 # 双边滤波参数之一 | |
p = 0.1 | |
temp4 = np.zeros_like(img) | |
temp1 = cv2.bilateralFilter(img,dx,fc,fc) | |
temp2 = cv2.subtract(temp1,img) | |
temp2 = cv2.add(temp2,(10,10,10,128)) | |
temp3 = cv2.GaussianBlur(temp2,(2*v2 - 1,2*v2-1),0) | |
temp4 = cv2.add(img,temp3) | |
dst = cv2.addWeighted(img,p,temp4,1-p,0.0) | |
dst = cv2.add(dst,(10, 10, 10,255)) | |
return dst |
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