- Below procedure is Workstation Setup and instruction to setting Step by Step
- If you want to use already setup env please follow docker setup instruction
- Notice: Following lectures are built on the version of Isaac Sim 2023.1.1.
- Dependency check
- Ubuntu
- Lecture Tested on: 20.04
- Isaac Sim Recommanded : 20.04 / 22.04
- NVIDIA Driver version
- Lecture Tested on: 510.108.03
- Isaac Sim Recommanded: 525.60.11
- Isaac Sim Minimum: 510.73.05
- Ubuntu
- Download Omniverse
-
move to
Isaac-sim
installed pathversion=2023.1.1 isaac_path=/home/${USER}/.local/share/ov/pkg/isaac-sim-${version} cd ${isaac_path}
-
clone repository
git clone https://github.com/gist-ailab/AILAB-summer-school.git --recurse-submodules --remote-submodules
-
Notice: Following lectures are built on the version of Python 3.10 & Anaconda environment
- Replaceable with python-venv and miniconda
-
Create conda env
- This procedure run inside
isaac sim
path(ex. .../isaac-sim-2023.1.1$) - This process can take a long time.
conda env create -f environment.yml conda activate isaac-sim
- This procedure run inside
-
Setup environment variables so that Isaac Sim python packages are located correctly
source setup_conda_env.sh
-
Install requirment pakages
- This procedure takes place within the
AILAB-summer-school
repository.
cd AILAB-summer-school pip install -r requirements.txt
- This procedure takes place within the
-
Install pycocotools
conda install -c conda-forge pycocotools
-
Install CLIP
pip install git+https://github.com/openai/CLIP.git
-
Detection model checkpoint download
cd lecture/data mkdir -p checkpoint/faster_r-cnn_ckpt cd checkpoint/faster_r-cnn_ckpt gdown https://drive.google.com/uc?id=16AnvrmyTgm-1xZMIQTmKc4aZVgj76OXt
-
Grasp model checkpoint download
cd lecture/data mkdir -p checkpoint/contact_grasp_ckpt cd checkpoint/contact_grasp_ckpt gdown https://drive.google.com/uc?id=16XYFNjSosM7W7DxXUNcI9VNGIPbol6tY
-
Asset files download
cd lecture/data gdown https://drive.google.com/uc?id=1SA9Q6HPGmsNEY4RNGUMHsFq3HtGRoP_1 unzip scene_generate_usd.zip
-
Detection dataset (PennFudanPed Dataset) download
cd lecture/data gdown https://drive.google.com/uc?id=15EbsaKLnkhHxGHYejORDTsS9rThELJMR unzip PennFudanPed.zip
-
install Docker on local & set permission
sudo apt install docker.io sudo usermod -aG docker ${USER} sudo service docker restart # To apply permission settings, you must log out and reconnect the logged-in session.
-
Install the nvidia Docker Container Toolkit to Use the gpu Option in Docker (official instruction)
curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg \ && curl -s -L https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list | \ sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' | \ sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list
sudo apt-get update
sudo apt-get install -y nvidia-container-toolkit
sudo systemctl restart docker
-
Docker cache store for local
mkdir -p ~/docker/isaac-sim/cache/kit mkdir -p ~/docker/isaac-sim/cache/ov mkdir -p ~/docker/isaac-sim/cache/pip mkdir -p ~/docker/isaac-sim/cache/glcache mkdir -p ~/docker/isaac-sim/cache/computecache
-
Pull docker image
docker login id : birdomi pwd : dckr_pat_c3afN9jUpcVUVMqKlWxzFNL8Y_Y
docker pull docker.io/birdomi/ailab-summer-camp-2024:1.0.4
-
Start the container
docker run -it --entrypoint bash --name isaac-sim -e "ACCEPT_EULA=Y" --gpus all --rm --network=host \ -e DISPLAY \ -v ~/docker/isaac-sim/cache/kit:/isaac-sim/kit/cache:rw \ -v ~/docker/isaac-sim/cache/ov:/root/.cache/ov:rw \ -v ~/docker/isaac-sim/cache/pip:/root/.cache/pip:rw \ -v ~/docker/isaac-sim/cache/glcache:/root/.cache/nvidia/GLCache:rw \ -v ~/docker/isaac-sim/cache/computecache:/root/.nv/ComputeCache:rw \ birdomi/ailab-summer-camp-2024:1.0.4
-
In the docker,some alias are alreadly set.
code: run visual studio code. sim: run isaac-sim.