If you use our dockerfile, you can run the code easily.
If you want to set up your own env, please follow these steps:
If you are in China Mainland, you can use these to speedup pip install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple
We only support python2.7 now
Install tk: sudo apt-get -y install python-tk
Install OpenCV 3.4.1
Install needed python packages with pip install -r requirements.txt
Then sh init.sh to build the lib for faster-rcnn Because we use the code from Deformable ConvNets and the dataloader has some dependencies on faster-rcnn, so you need to build the lib first.
2. Prepare Data and Pretrained Model
Cityscapes Data
You need to download the cityscapes data from the official webpapge and unzip the data Put the data into data/cityscapes, you can use soft link to set the data path as the following: ln -s Dataset_path ./data/cityscapes
If you want to try DFF, you should download cityscapes video data and put it into data/cityscapes_video
Pretrained Model
Download pretrained resnet model flow net from Onedrive, and put the model into mode/pretrained_model/