INSTALL.md

Installation

We used PyTorch 0.4.1 on Ubuntu 18.04 LTS with Anaconda Python 3.6.

1. [Optional but recommended] Create a new Conda environment.

   conda create --name CircleNet python=3.6
   

   And activate the environment.

   conda activate CircleNet
   

2. Install Pytorch 0.4.1:

   conda install pytorch=0.4.1 cuda92 torchvision -c pytorch
   

   And disable cudnn batch normalization(Due to this issue).

   # PYTORCH=/path/to/pytorch # usually ~/anaconda3/envs/CenterNet/lib/python3.6/site-packages/
   # for pytorch v0.4.0
   sed -i "1194s/torch\.backends\.cudnn\.enabled/False/g" ${PYTORCH}/torch/nn/functional.py
   # for pytorch v0.4.1
   sed -i "1254s/torch\.backends\.cudnn\.enabled/False/g" ${PYTORCH}/torch/nn/functional.py
   

   For other pytorch version, you can manually open torch/nn/functional.py and find the line with torch.batch_norm and replace the torch.backends.cudnn.enabled with False. We observed slight worse training results without doing so.

3. Install the requirements

   pip install -r requirements.txt
   

4. Install COCOAPI:

   COCOAPI=/path/to/clone/cocoapi
   git clone https://github.com/cocodataset/cocoapi.git $COCOAPI
   cd $COCOAPI/PythonAPI
   make
   python setup.py install --user
   

5. Clone this repo:

   CircleNet_ROOT=/path/to/clone/CircleNet
   git clone https://github.com/hrlblab/CircleNet.git $CircleNet_ROOT
   

6. Compile deformable convolutional (from DCNv2).

   cd $CircleNet_ROOT/src/lib/models/networks/DCNv2git 
   ./make.sh
   

7. Compile NMS.

   cd $CircleNet_ROOT/src/lib/external
   make