希望你给我一些建议，将 h36m 关键点转换为 coco 格式。
这是我在 h36m 中的姿势。我想将其转换为 coco coco 关键点。
我发现代码相反但没有设法改变它。
def coco_h36m(keypoints):
temporal = keypoints.shape[0]
keypoints_h36m = np.zeros_like(keypoints, dtype=np.float32)
htps_keypoints = np.zeros((temporal, 4, 2), dtype=np.float32)
# htps_keypoints: head, thorax, pelvis, spine
htps_keypoints[:, 0, 0] = np.mean(keypoints[:, 1:5, 0], axis=1, dtype=np.float32)
htps_keypoints[:, 0, 1] = np.sum(keypoints[:, 1:3, 1], axis=1, dtype=np.float32) - keypoints[:, 0, 1]
htps_keypoints[:, 1, :] = np.mean(keypoints[:, 5:7, :], axis=1, dtype=np.float32)
htps_keypoints[:, 1, :] += (keypoints[:, 0, :] - htps_keypoints[:, 1, :]) / 3
htps_keypoints[:, 2, :] = np.mean(keypoints[:, 11:13, :], axis=1, dtype=np.float32)
htps_keypoints[:, 3, :] = np.mean(keypoints[:, [5, 6, 11, 12], :], axis=1, dtype=np.float32)
keypoints_h36m[:, spple_keypoints, :] = htps_keypoints
keypoints_h36m[:, h36m_coco_order, :] = keypoints[:, coco_order, :]
keypoints_h36m[:, 9, :] -= (keypoints_h36m[:, 9, :] - np.mean(keypoints[:, 5:7, :], axis=1, dtype=np.float32)) / 4
keypoints_h36m[:, 7, 0] += 2*(keypoints_h36m[:, 7, 0] - np.mean(keypoints_h36m[:, [0, 8], 0], axis=1, dtype=np.float32))
keypoints_h36m[:, 8, 1] -= (np.mean(keypoints[:, 1:3, 1], axis=1, dtype=np.float32) - keypoints[:, 0, 1])*2/3
# half body: the joint of ankle and knee equal to hip
# keypoints_h36m[:, [2, 3]] = keypoints_h36m[:, [1, 1]]
# keypoints_h36m[:, [5, 6]] = keypoints_h36m[:, [4, 4]]
valid_frames = np.where(np.sum(keypoints_h36m.reshape(-1, 34), axis=1) != 0)[0]
return keypoints_h36m, valid_frames