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import dlib
class LandmarksDetector:
def __init__(self, predictor_model_path):
"""
:param predictor_model_path: path to shape_predictor_68_face_landmarks.dat file
"""
self.detector = dlib.get_frontal_face_detector() # cnn_face_detection_model_v1 also can be used
self.shape_predictor = dlib.shape_predictor(predictor_model_path)
def get_landmarks(self, image):
img = dlib.load_rgb_image(image)
dets = self.detector(img, 1)
for detection in dets:
try:
face_landmarks = [(item.x, item.y) for item in self.shape_predictor(img, detection).parts()]
yield face_landmarks
except:
print("Exception in get_landmarks()!")
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