步态提取-使用卷积神经网络从视频中提取行人步态-附项目源码-优质项目实战.zip

# Training and analysis For training our models you need to install `requirements.txt` from the main directory ```bash pip install -r requirements.txt ``` Data used for training is available [here](https://simtk.org/frs/?group_id=1918) (doi:10.18735/j0rz-0k12) Use the following scripts for training and analyzing models. Files are listed in the order in which they should be run. | File | Description | |:------------- |:-------------| | process_annotations.ipynb* | Processes OpenPose json files | | process_frames.ipynb* | Normalize pozes in frames | | combine_video_csvs.ipynb | Combines time series of poses with labels | | split_ids.ipynb | Training, validation, testing split | | compute_SEMLS_residuals.ipynb | Builds simple models for SEMLS to control for demographics | | process_raw_videos.ipynb* | Additional processing of trajectories (missing data, smoothing, orientation) | | cnn_predict_doublesided_var.ipynb* | Models for variables that depend on the side (GDI, knee flexion at max extension) | | cnn_predict_singlesided_var.ipynb* | Models for variables that don't depend on the side (cadence, speed) | | select_optimal_epoch.ipynb | Choose the best model based on validation error | | calculate_corr_rmse.ipynb | Get performance metrics for classification and regression tasks | | calculate_SEMLS_ROC.ipynb | Get performance metrics for the binary prediction task (SEMLS) | | statistical_analysis.ipynb | Analyze results from models | For predicting on new video data you need to run files with *.