removed last fix

This commit is contained in:
Colombo 2019-10-14 20:31:11 +04:00
parent e18b07549b
commit 5a2eefaa5b

View file

@ -39,7 +39,6 @@ class FANExtractor(object):
input_image = input_image[:,:,::-1]
is_bgr = False
(h, w, ch) = input_image.shape
landmarks = []
@ -64,12 +63,10 @@ class FANExtractor(object):
images += [ self.crop(input_image, c, scale) ]
images = np.stack (images)
predicted = self.model.predict (images.astype(np.float32) / 255.0).transpose (0,3,1,2)
for i, pred in enumerate(predicted):
ptss += [ self.get_pts_from_predict ( pred, centers[i], scale) ]
pts_img = np.mean ( np.array(ptss), 0 )
landmarks.append (pts_img)
@ -77,10 +74,7 @@ class FANExtractor(object):
landmarks.append (None)
if second_pass_extractor is not None:
new_landmarks = []
for lmrks in landmarks:
new_landmarks += [None]
for i, lmrks in enumerate(landmarks):
try:
if lmrks is not None:
image_to_face_mat = LandmarksProcessor.get_transform_mat (lmrks, 256, FaceType.FULL)
@ -89,26 +83,10 @@ class FANExtractor(object):
rects2 = second_pass_extractor.extract(face_image, is_bgr=is_bgr)
if len(rects2) == 1: #dont do second pass if faces != 1 detected in cropped image
lmrks2 = self.extract (face_image, [ rects2[0] ], is_bgr=is_bgr, multi_sample=True)[0]
new_landmarks[-1] = LandmarksProcessor.transform_points (lmrks2, image_to_face_mat, True)
landmarks[i] = LandmarksProcessor.transform_points (lmrks2, image_to_face_mat, True)
except:
pass
for i, new_lmrks in enumerate(new_landmarks):
mat = LandmarksProcessor.get_transform_mat (new_lmrks, 256, FaceType.FULL)
center, p1,p2 = LandmarksProcessor.transform_points ([ [127,127], [0,0], [0,255] ], mat, True)
p_dist = npla.norm(p2-p1)
for j, other_lmrks in enumerate(landmarks):
if i != j:
other_mat = LandmarksProcessor.get_transform_mat (new_lmrks, 256, FaceType.FULL)
other_center = LandmarksProcessor.transform_points ([ [127,127] ], other_mat, True)
dist = npla.norm (other_center - center)
if dist < p_dist*0.25:
break
else:
landmarks[i] = new_lmrks
return landmarks
def transform(self, point, center, scale, resolution):