Skip to content

Latest commit

 

History

History
107 lines (79 loc) · 2.87 KB

README.md

File metadata and controls

107 lines (79 loc) · 2.87 KB

Using UniAD as driving agent.

Overview

Changelog

[2024-09-04] We simplified the UniAD input by removing the gt tag input and using fastapi to receive input from World Dreamer and pass the output to TrafficManager.

Installation

a. Env: Create a conda virtual environment and activate it.

conda create -n uniad python=3.8 -y
conda activate uniad

b. Torch: Install PyTorch and torchvision following the official instructions.

conda install cudatoolkit=11.1.1 -c conda-forge
# We use cuda-11.1 by default
pip install torch==1.9.1+cu111 torchvision==0.10.1+cu111 torchaudio==0.9.1 -f https://download.pytorch.org/whl/torch_stable.html
# Recommended torch>=1.9

c. GCC: Make sure gcc>=5 in conda env.

# If gcc is not installed:
# conda install -c omgarcia gcc-6 # gcc-6.2

export PATH=YOUR_GCC_PATH/bin:$PATH
# Eg: export PATH=/mnt/gcc-5.4/bin:$PATH

d. CUDA: Before installing MMCV family, you need to set up the CUDA_HOME (for compiling some operators on the gpu).

export CUDA_HOME=YOUR_CUDA_PATH/
# Eg: export CUDA_HOME=/mnt/cuda-11.1/

e. Install mmcv.

pip install mmcv-full==1.4.0
# If it's not working, try:
# pip install mmcv-full==1.4.0 -f https://download.openmmlab.com/mmcv/dist/cu111/torch1.9.0/index.html

f. Install requirements.

# Install Dependencies
cd UniAD
pip install -r requirements.txt

g. Install mmdet3d from source code.

cd ~
git clone https://github.com/open-mmlab/mmdetection3d.git
cd mmdetection3d
git checkout v0.17.1
pip install -v -e .

h. Install CAMixerSR from source code.

cd UniAD
git clone https://github.com/icandle/CAMixerSR.git
# 1. Comment out the  "_arch_modules = [importlib.import_module(f'archs.{file_name}') for file_name in arch_filenames]" in "CAMixerSR/codes/basicsr/archs/__init__.py" 
# 2. Comment out the  "_model_modules = [importlib.import_module(f'models.{file_name}') for file_name in model_filenames]" in "CAMixerSR/codes/basicsr/models/__init__.py"

Getting Started

Pretrained Weight

cd UniAD
mkdir ckpts
wget 'https://github.com/icandle/CAMixerSR/blob/main/pretrained_models/LightSR/CAMixerSRx4_DF.pth'
wget 'https://github.com/OpenDriveLab/UniAD/releases/download/v1.0.1/uniad_base_e2e.pth'

Running service with FastAPI

cd UniAD
python demo/uniad_fast_api.py