DeepParkour

Training a humanoid agent to efficiently apply parkour skills to an obstacle environment.

Dependencies

requirements.txt includes all the dependecies required to run this project.

Trained Agent:

You can watch a few of our agents in this video

Installation

Clone the repo and cd into it:

git clone https://github.com/aagrawal20/DeepParkour.git
cd DeepParkour

If have access to a CUDA-compatible gpu then install tensorflow gpu.
```
pip install tensorflow-gpu 
```
Refer to TensorFlow installation guide for more details.
Install DeepParkour package.
```
pip install -e .
```

Training Agent

You can train an agent using the train_agent.py file.
You can add specific flags to the argument parser.
```
python src/main/train_agent.py
```

Rendering an Agent

You can render an agent using the render_agent.py file.
You can add specific flags to the argument parser.
```
python src/main/render_agent.py
```
Note: PyBullet only supports CPU rendering. Turn off render flag or manually turn off gpu.

Visualizing Agent training

You can visualize different stastics for eg: loss vs timesteps or reward vs timesteps.
```
jupyter notebook
```
After loading the local host navigate to the visualization.ipynb in src/util.