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Environment Setup

This project uses CUDA 11.8 and recommends Conda for environment management.

Follow this guide to set up your environment for running HERMES.

1. Create and Activate Conda Environment

conda create -n hermes python=3.9 -y
conda activate hermes
pip install --upgrade pip setuptools wheel

2. Install InternVL and Dependencies

pip install torch==2.7.0 torchvision==0.22.0 torchaudio==2.7.0 --index-url https://download.pytorch.org/whl/cu118# custom 

# mmcv and mmdet to avoid trouble
cd mmcv/
export MMCV_WITH_OPS=1
python setup.py develop
cd ../
cd mmdetection/
python setup.py develop
cd ../

pip install mmsegmentation==0.30.0
pip install -r requirements_internvl.txt
pip install flash-attn==2.3.6 --no-build-isolation
pip install deepspeed==0.13.5

To ensure compatibility between Torch and DeepSpeed, you may need to replace from torch.distributed.elastic.agent.server.api import log, _get_socket_with_port with from torch.distributed.elastic.agent.server.api import logger as log.

3. Install MMDet3D and Additional Packages

pip install einops fvcore seaborn iopath==0.1.9 timm==0.6.13 typing-extensions==4.5.0 pylint ipython==8.12  numpy==1.22 matplotlib==3.5.2 numba==0.57 pandas==1.4.4 scikit-image==0.19.3 setuptools==59.5.0, boto3
python -m pip install  'git+https://github.com/facebookresearch/detectron2.git' --no-build-isolation
pip install plyfile==1.0.3, nuscenes-devkit==1.1.10, plotly==5.22.0, pandas==1.4.4, scipy==1.10.1, flake8==7.1.0, pytest==8.2.2, lyft_dataset_sdk, yapf==0.40.1
pip install spconv-cu118
pip uninstall opencv-python -y
python setup.py install

4. Compile Third-Party Libraries

cd third_lib/chamfer_dist/chamferdist/
pip install .
cd ../../..

cd projects/mmdet3d_plugin/bevformer/backbones/ops_dcnv3
sh make.sh
cd ../../../../..

5. Install PyG Dependency

pip install https://data.pyg.org/whl/torch-2.7.0%2Bcu118/torch_scatter-2.1.2%2Bpt27cu118-cp39-cp39-linux_x86_64.whl

6. Install InternVL-Chat Plugin

cd projects/mmdet3d_plugin/models/internvl_chat
pip install -e .
pip install numba==0.57, torchmetrics==1.4.1, networkx==2.5
pip install transformers==4.57.3

Please refer to Data.md for instructions on handling datasets and pretrained weights.