11785-project's Introduction

Instruction for running baseline models

Environment

We are running our baseline models on AWS EC2 G4 instances with Pytorch 1.6.0. Below are some packages you might need to install for running the baseline models

python -m pip install cityscapesscripts
pip install mmcv-full

Dataset

The dataset we are currently using is Cityscapes, you can download it with from https://www.cityscapes-dataset.com/ or you can simply run the following commands.

wget --keep-session-cookies --save-cookies=cookies.txt \
    --post-data 'username=yourusername&password=yourpassword&submit=Login'https://www.cityscapes-dataset.com/login/
wget --load-cookies cookies.txt --content-disposition https://www.cityscapes-dataset.com/file-handling/?packageID=1
wget --load-cookies cookies.txt --content-disposition https://www.cityscapes-dataset.com/file-handling/?packageID=3
unzip leftImg8bit_trainvaltest.zip && rm leftImg8bit_trainvaltest.zip
unzip gtFine_trainvaltest.zip && rm gtFine_trainvaltest.zip

The final file structure will be:

    .
    ├── ...
    ├── data                    
    │   ├── cityscapes
    │   │   ├── getFine 
    │   │   ├── leftImg8bit
    └── ...

Running

Train DeepLabv3+ with ResNet50 backbone:

./tools/dist_train.sh configs/deeplabv3plus/deeplabv3plus_r50-d8_512x1024_80k_cityscapes.py 1

Evaluate DeepLabv3+:

python tools/test.py configs/deeplabv3plus/deeplabv3plus_r50-d8_512x1024_80k_cityscapes.py \
    checkpoints/FileGeneratedInTraining.pth\
    --eval mIoU cityscapes

For running DeepLabv3+ with ResNet101 backbone and FCN-8s, you can also run similar commands above.

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