INSTALL.md

Most of the requirements of this projects are exactly the same as cvpods. If you have any problem of your environment, you should check their issues page first. Hope you will find the answer.

Install Packages

Conda Environments

# first, make sure that your conda is setup properly with the right environment
# for that, check that `which conda`, `which pip` and `which python` points to the
# right path. From a clean conda env, this is what you need to do

conda create -y --name sgtr
conda activate sgtr

MISC packages

pip install -r requirements.txt

Pytorch 1.10

# CUDA 10.2
conda install pytorch==1.10.1 torchvision==0.11.2 torchaudio==0.10.1 cudatoolkit=10.2 -c pytorch
# CUDA 11.3
conda install pytorch==1.10.1 torchvision==0.11.2 torchaudio==0.10.1 cudatoolkit=11.3 -c pytorch -c conda-forge

Path Environments

• Add the path env into your bashrc or zshrc.

cvpods_env (){
     export CVPODS_OUTPUT=/path/to/your/outputs/
     export CVPODS_HOME=/path/to/your/outputs/
     export GLOO_SOCKET_IFNAME=ib0
     export NCCL_SOCKET_IFNAME=ib0
}
cvpods_env

• Change the /path/to/your/outputs/ to your own folder for saving the training outputs.

Build Project

python setup.py build develop

Update VG Evaluation Config

Update /your/project/dir/ in the L528 of cvpods/evaluation/sgg_vg_evaluation.py

def classic_vg_sgg_evaluation(
        cfg,
        predictions,
        groundtruths,
        predicates_categories: list,
        output_folder,
        logger,
):
    # get zeroshot triplet
    zeroshot_triplet = torch.load(
        "/your/project/dir/sgtr_release/datasets/vg/vg_motif_anno/zeroshot_triplet.pytorch",
        map_location=torch.device("cpu")).long().numpy()