def alignment_112x112(img,bb,landmark,image_size):
M = None
if landmark is not None:
src = np.array([
[30.2946, 51.6963],
[65.5318, 51.5014],
[48.0252, 71.7366],
[33.5493, 92.3655],
[62.7299, 92.2041] ], dtype=np.float32 )
if image_size[1]==112:
src[:,0] += 8.0
dst = landmark.astype(np.float32)
tform = trans.SimilarityTransform()
tform.estimate(dst, src)
M = tform.params[0:2,:]
if M is None:
ret = img[bb[1]:bb[3],bb[0]:bb[2],:]
if len(image_size)>0:
ret = cv2.resize(ret, (image_size[1], image_size[0]), interpolation=cv2.INTER_CUBIC)
return ret
else:
warped = cv2.warpAffine(img,M,(image_size[1],image_size[0]), borderValue = 0.0)
return warped
richardminh
commented
5 years ago
alignment:112x112
def alignment_112x112(img,bb,landmark,image_size): M = None if landmark is not None: src = np.array([ [30.2946, 51.6963], [65.5318, 51.5014], [48.0252, 71.7366], [33.5493, 92.3655], [62.7299, 92.2041] ], dtype=np.float32 ) if image_size[1]==112: src[:,0] += 8.0 dst = landmark.astype(np.float32)