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