# Create your python env
conda create -n afforddp python=3.8
conda activate afforddp
# Install torch
pip install torch==2.4.1 torchvision==0.19.1 torchaudio==2.4.1 --index-url https://download.pytorch.org/whl/cu118 
# Install Xformers, note the version compatibility with torch.
pip install -U xformers==0.0.28.post1 --index-url https://download.pytorch.org/whl/cu118
# Other package
pip install -r requirements.txt

pip install "git+https://github.com/facebookresearch/pytorch3d.git"

cd third_party
cd curobo
pip install -e . --no-build-isolation

cd third_party
cd GroundedSAM
pip install -e GroundingDINO
pip install -e segment_anything
# Pretrained model weight
cd ../..
wget https://dl.fbaipublicfiles.com/segment_anything/sam_vit_h_4b8939.pth -P assets/ckpts/
wget https://github.com/IDEA-Research/GroundingDINO/releases/download/v0.1.0-alpha/groundingdino_swint_ogc.pth -P assets/ckpts/

cd third_party
cd Point_SAM
# Install torkit3d
pip install third_party/torkit3d
# Install apex
pip install -v --disable-pip-version-check --no-cache-dir --no-build-isolation --config-settings "--build-option=--cpp_ext" --config-settings "--build-option=--cuda_ext" third_party/apex

tar -zxvf IsaacGym_Preview_4_Package.tar.gz
cd isaacgym/python
pip install -e .
# You can test whether isaacgym can be used.
cd examples
python joint_monkey.py

python collect_demonstrations.py --save_dir $YOUR_DATA_SAVE_PATH --object_id $GAPartNet_obj_id --part_id $Manip_Part_id 

python process_data.py --data_dir $YOUR_DATA_SAVE_PATH --save_dir $PROCESS_DATA_SAVE_PATH 

sh train.sh ${seed} ${cuda_id}

sh eval.sh ${ckpt_path} ${object_id}

python demo.py