conda create -n itpn_det python=3.7
source activate itpn_det
conda install pytorch==1.8.0 torchvision==0.9.0 torchaudio==0.8.0 cudatoolkit=10.2 -c pytorch
pip install mmcv-full==1.3.0 mmsegmentation==0.11.0
pip install scipy timm==0.3.2
# install apex
git clone https://github.com/NVIDIA/apex
cd apex
pip install -v --disable-pip-version-check --no-cache-dir --no-build-isolation --global-option="--cpp_ext" --global-option="--cuda_ext" ./
cd ..
Follow mmseg to prepare the ADE20k dataset.
bash tools/dist_train.sh \
./configs/itpn/pixel_upernet_itpn_base_12_512_slide_160k_ade20k_pt2ft.py 8 \
--work-dir /path/to/save --seed 0 --deterministic \
--options model.pretrained=<PRETRAIN_CHECKPOINT_PATH>
bash tools/dist_test.sh \
./configs/itpn/pixel_upernet_itpn_base_12_512_slide_160k_ade20k_pt2ft.py \
<FINETUNED_CHECKPOINT_PATH> 8 \
--eval mIoU