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removing trailing spaces

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iperov 2019-03-19 23:53:27 +04:00
parent fa4e579b95
commit a3df04999c
61 changed files with 2110 additions and 2103 deletions
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52
facelib/LandmarksExtractor.py
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@ -10,38 +10,38 @@ class LandmarksExtractor(object):
def __init__ (self, keras):
self.keras = keras
K = self.keras.backend
def __enter__(self):
def __enter__(self):
keras_model_path = Path(__file__).parent / "2DFAN-4.h5"
if not keras_model_path.exists():
return None
self.keras_model = self.keras.models.load_model (str(keras_model_path))
self.keras_model = self.keras.models.load_model (str(keras_model_path))
return self
def __exit__(self, exc_type=None, exc_value=None, traceback=None):
del self.keras_model
return False #pass exception between __enter__ and __exit__ to outter level
def extract_from_bgr (self, input_image, rects, second_pass_extractor=None):
input_image = input_image[:,:,::-1].copy()
(h, w, ch) = input_image.shape
landmarks = []
for (left, top, right, bottom) in rects:
try:
center = np.array( [ (left + right) / 2.0, (top + bottom) / 2.0] )
#center[1] -= (bottom - top) * 0.12
scale = (right - left + bottom - top) / 195.0
image = self.crop(input_image, center, scale).astype(np.float32)
image = np.expand_dims(image, 0)
predicted = self.keras_model.predict (image).transpose (0,3,1,2)
pts_img = self.get_pts_from_predict ( predicted[-1], center, scale)
pts_img = [ ( int(pt[0]), int(pt[1]) ) for pt in pts_img ]
pts_img = [ ( int(pt[0]), int(pt[1]) ) for pt in pts_img ]
landmarks.append ( ( (left, top, right, bottom),pts_img ) )
except Exception as e:
landmarks.append ( ( (left, top, right, bottom), None ) )
@ -52,26 +52,26 @@ class LandmarksExtractor(object):
rect, lmrks = landmarks[i]
if lmrks is None:
continue
image_to_face_mat = LandmarksProcessor.get_transform_mat (lmrks, 256, FaceType.FULL)
face_image = cv2.warpAffine(input_image, image_to_face_mat, (256, 256), cv2.INTER_CUBIC)
rects2 = second_pass_extractor.extract_from_bgr(face_image)
if len(rects2) != 1: #dont do second pass if more than 1 or zero faces detected in cropped image
continue
rect2 = rects2[0]
lmrks2 = self.extract_from_bgr (face_image, [rect2] )[0][1]
source_lmrks2 = LandmarksProcessor.transform_points (lmrks2, image_to_face_mat, True)
source_lmrks2 = LandmarksProcessor.transform_points (lmrks2, image_to_face_mat, True)
landmarks[i] = (rect, source_lmrks2)
except:
continue
return landmarks
def transform(self, point, center, scale, resolution):
pt = np.array ( [point[0], point[1], 1.0] )
pt = np.array ( [point[0], point[1], 1.0] )
h = 200.0 * scale
m = np.eye(3)
m[0,0] = resolution / h
@ -80,11 +80,11 @@ class LandmarksExtractor(object):
m[1,2] = resolution * ( -center[1] / h + 0.5 )
m = np.linalg.inv(m)
return np.matmul (m, pt)[0:2]
def crop(self, image, center, scale, resolution=256.0):
ul = self.transform([1, 1], center, scale, resolution).astype( np.int )
br = self.transform([resolution, resolution], center, scale, resolution).astype( np.int )
if image.ndim > 2:
newDim = np.array([br[1] - ul[1], br[0] - ul[0], image.shape[2]], dtype=np.int32)
newImg = np.zeros(newDim, dtype=np.uint8)
@ -98,14 +98,14 @@ class LandmarksExtractor(object):
oldX = np.array([max(1, ul[0] + 1), min(br[0], wd)], dtype=np.int32)
oldY = np.array([max(1, ul[1] + 1), min(br[1], ht)], dtype=np.int32)
newImg[newY[0] - 1:newY[1], newX[0] - 1:newX[1] ] = image[oldY[0] - 1:oldY[1], oldX[0] - 1:oldX[1], :]
newImg = cv2.resize(newImg, dsize=(int(resolution), int(resolution)), interpolation=cv2.INTER_LINEAR)
return newImg
def get_pts_from_predict(self, a, center, scale):
b = a.reshape ( (a.shape[0], a.shape[1]*a.shape[2]) )
b = a.reshape ( (a.shape[0], a.shape[1]*a.shape[2]) )
c = b.argmax(1).reshape ( (a.shape[0], 1) ).repeat(2, axis=1).astype(np.float)
c[:,0] %= a.shape[2]
c[:,0] %= a.shape[2]
c[:,1] = np.apply_along_axis ( lambda x: np.floor(x / a.shape[2]), 0, c[:,1] )
for i in range(a.shape[0]):
@ -113,6 +113,6 @@ class LandmarksExtractor(object):
if pX > 0 and pX < 63 and pY > 0 and pY < 63:
diff = np.array ( [a[i,pY,pX+1]-a[i,pY,pX-1], a[i,pY+1,pX]-a[i,pY-1,pX]] )
c[i] += np.sign(diff)*0.25
c += 0.5
return [ self.transform (c[i], center, scale, a.shape[2]) for i in range(a.shape[0]) ]
return [ self.transform (c[i], center, scale, a.shape[2]) for i in range(a.shape[0]) ]