Human Action Recognition
This code is implemented based on Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition.
And this code only supports the Florence 3D action dataset.
Please download from here at ./dataset/
Environments
- python 3.6
- pytorch 1.0
Run
python main.pyFile Details
| File Name | Description |
|---|---|
preprocess.py |
Preprocess the Florence 3D action dataset. Each frame is unified into 32 frames, separated by train / valid / test and dropped into a file. |
config.py |
Hyperparameter and data path setting |
main.py |
Execution File. Loads data and models, and performs training and testing. |
model.py |
Defines the General Graph Convolutional Network (GGCN) class. Construct an adjacency matrix with three consecutive graphs, and call several layers. |
layer.py |
Defines the graph convolution, standard convolution and classifier layer. |
metric.py |
Defines the accuracy function |