体感交互——基于Mediapipe和LSTM的手姿估计.zip

# 👇体感互动——Hand Pose Estimation Based on Mediapipe And LSTM 目录： - [👇体感互动——Hand Pose Estimation Based on Mediapipe And LSTM](#体感互动hand-pose-estimation-based-on-mediapipe-and-lstm) - [🐱Introduce](#introduce) - [🐖QuickStart](#quickstart) - [Dependencies](#dependencies) - [Inference1](#inference1) - [Inference2](#inference2) - [体感互动](#体感互动) - [😔Training](#training) - [🐒Reference](#reference) - [🐕Thanks](#thanks) ## 🐱Introduce **体感互动——Hand Pose Estimation Based on Mediapipe And LSTM** 基于mediapipe提取人体姿势、人脸、手部关键点和LSTM算法实现手势识别，并进一步实现体感互动的功能，如进行隔空移动、抓取、放大、缩小等手势操作，可为商业显示提供智能交互应用，如3D模型的展示。 数据：一共采集3类手势，每一个手势30个视频，每一个视频30帧，每一帧提取的landmarks序列长度为1662（33个4维人体姿势landmarks，468个3维人脸landmarks，21个3维左手landmarks，21个3维右手landmarks，33✖4＋468✖3+21✖3+21✖3=1662）。 网络：三层lstm([lstm_net.py](https://edu.gitee.com/jhcyun/repos/jhcyun/HandPoseEstimationBasedOnMediapipeAndLstm/blob/master/lstm_net.py)) * demo1:01_predict_hand__pose_.py  * demo2：02_predict.py  * demo3：03_predict之体感互动.py  ## 🐖QuickStart ### Dependencies ``pip install -r requirements.txt `` ### Inference1 ``python 01_predict_hand_pose.py `` ### Inference2 ``python 02_predict.py `` ### 体感互动 1、 打开https://720.vrqjcs.com/t/9332870054821ffc 2、 ``python 03_predict之体感互动.py `` ## 😔Training 详见[train_my_hand_pose/hand pose detection.ipynb](https://edu.gitee.com/jhcyun/repos/jhcyun/HandPoseEstimationBasedOnMediapipeAndLstm/blob/master/train_my_hand_pose%2Fhand%20pose%20detection.ipynb) 具体开发流程见[Hand-Pose-Estimation.pdf](https://edu.gitee.com/jhcyun/repos/jhcyun/HandPoseEstimationBasedOnMediapipeAndLstm/blob/master/Hand-Pose-Estimation.pdf) 思维导图 ## 🐒Reference * [Mediapipe](https://google.github.io/mediapipe/) * [@NicholasRenotte](https://www.youtube.com/watch?v=doDUihpj6ro) * [VRMap](https://720.vrqjcs.com/t/9332870054821ffc) ## 🐕Thanks * @Studio:JHC Software Dev Studio * @Mentor:HuangRiChen * @Author:YuJunYu