shape_predictor_81_face_landmarks-master

所属分类:人工智能/神经网络/深度学习
开发工具:Python
文件大小:17862KB
下载次数:16
上传日期:2019-11-07 15:14:58
上 传 者Winnie_Q
说明:  基于dlib库的人脸68个特征点训练模型的扩展模型,可识别出人脸81个特征点,包括额头部分。
(Based on the extended model of the face training model of 68 feature points based on Dlib database, 81 feature points can be recognized, including the forehead part.)

文件列表:
81_facial_landmarks_reference.jpg (177994, 2019-03-19)
LICENSE (1515, 2019-03-19)
full_mesh_example.png (1803500, 2019-03-19)
shape_predictor_81_face_landmarks.dat (19743860, 2019-03-19)
transformation_example.bmp (3312806, 2019-03-19)
webcam_record.py (961, 2019-03-19)

81 Facial Landmarks Shape Predictor =============== This is a custom shape predictor model trained to find 81 facial feature landmarks given any image. It's trained similar to dlib's 68 facial landmark shape predictor. In addition to the original 68 facial landmarks, I added an additional 13 landmarks to cover the forehead area. This allows for precise head detection and for image operations that require points along the top of the head, for example when [placing a hat on someone's head.](https://github.com/codeniko/shape_predictor_81_face_landmarks/raw/master/transformation_example.bmp) The additional 13 points were extract using my fork of eos by patrikhuber: https://github.com/codeniko/eos. I continued to use the Surrey Face Model and made note of 13 points that I thought were the perfect fit for my use case. I made the modifications here, then ran it on the entire ibug large database of images to overwrite each image's 68 landmark coordinates with my 81 landmark coordinates. From here, the training for the shape predictor model can proceed using http://dlib.net/train_shape_predictor.py.html Check out this live example video of 81 landmark detection in action: [https://www.youtube.com/watch?v=mDJrASIB1T0](https://www.youtube.com/watch?v=mDJrASIB1T0) 81 landmarks reference ---------------- 81 landmarks reference image

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