Run the following steps to implement human pose estimation with the pretrained Caffe model:
- This MPI dataset has 15 keypoints corresponding to different parts of the human body—let's define them first. You will also need to define pose pairs for the limbs that connect the keypoints. The limbs are predicted using the pose affinity maps:
n_points = 15body_parts = {"Head": 0, "Neck": 1, "RShoulder": 2, "RElbow": 3, "RWrist": 4, "LShoulder": 5, "LElbow": 6, "LWrist": 7, "RHip": 8, "RKnee": 9, "RAnkle": 10, "LHip": 11, "LKnee": 12, "LAnkle": 13, "Chest": 14, "Background": 15}pose_pairs = [ ["Head", "Neck"], ["Neck", "RShoulder"], ["RShoulder", "RElbow"], ["RElbow", "RWrist"], ["Neck", "LShoulder"], ["LShoulder", "LElbow"], ["LElbow", ...