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TorchDriveEnv is a lightweight 2D driving reinforcement learning environment, supported by a solid simulator and smart non-playable characters

Project description

Installation

The basic installation of torchdriveenv uses an OpenCV renderer, which is slower but easy to install. PyTorch3D renderer can be faster, but it requires specific versions of CUDA and PyTorch, so it is best installed in Docker.

Opencv rendering

To install the “torchdriveenv” with opencv rendering:

pip install torchdriveenv

To run examples: Set the $IAI_API_KEY and $WANDB_API_KEY

pip install torchdriveenv[baselines]
cd examples
python rl_training.py

Pytorch3d rendering

To install the “torchdriveenv” with Pytorch3d rendering:

docker build --target torchdriveenv-first-release -t torchdriveenv-first-release:latest .

To run examples: Set the $IAI_API_KEY and $WANDB_API_KEY

cd examples
docker compose up rl-training

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