/CenterNetPerson

CenterNet used for pedestrian detection

Primary LanguagePython

##Pedestrian detection based on CenterNet

In this repo, we re-train the centernet on CityPerson dataset to get a pedestrian detector CenterNet

##Preparation

Please first install Anaconda and create an Anaconda environment using the provided package list.

conda create --name CenterNet --file conda_packagelist.txt

After you create the environment, activate it.

source activate CenterNet

Compiling Corner Pooling Layers

cd <CenterNet dir>/models/py_utils/_cpools/
python setup.py install --user

Compiling NMS

cd <CenterNet dir>/external
make

CityPerson dataset

  • Download the CityPerson dataset and label files in images, label
  • create a softlink in data to your CityPerson data 
    ln -s  #to/yourdata/CityPerson data/

Training and Evaluation

To train CenterNet-52

python train.py --cfg_file CenterNet-52

The default configure in config/CenterNet-52.json is 2 (12G) GPUs and batchsize=12, you can modify them according to your case.

To evaluate your detector

python test.py --cfg_file CenterNet-52 --testiter  #checkpoint_epoch

Demo

The demo images are stored in data/demo

python demo.py