Skip to content

Latest commit

 

History

History
29 lines (21 loc) · 1.25 KB

File metadata and controls

29 lines (21 loc) · 1.25 KB

Installation

The installation follows Detectron2. Here we provide a quickstart guide, and refer to the solutions from Detectron2 should any issue arise.

Requirements

  • Linux or macOS with Python 3.9
  • PyTorch 1.9 and torchvision that matches the PyTorch installation
  • OpenCV is optional for training and inference, yet is needed by our demo and visualization

Quick Start

# environment
conda create -n regionclip python=3.9
source activate regionclip
conda install nvidia/label/cuda-11.3.0::cuda-toolkit
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

# RegionCLIP
git clone git@github.com:microsoft/RegionCLIP.git
python -m pip install -e RegionCLIP

# other dependencies
pip install opencv-python timm diffdist h5py scikit-learn ftfy numpy==1.26.4 setuptools==59.5.0
pip install git+https://github.com/lvis-dataset/lvis-api.git

To rebuild, use rm -rf build/ **/*.so to clean the old build first. You often need to rebuild detectron2 after reinstalling PyTorch.