CornerNet

tensorflow

CornerNet: Training and Evaluation Code

Code for reproducing the results in the following paper:

CornerNet: Detecting Objects as Paired Keypoints
Hei Law, Jia Deng
European Conference on Computer Vision (ECCV), 2018

environment

tensorflow==1.10
python3.6

Our current implementation only supports GPU so you need a GPU and need to have CUDA installed on your machine.

You also need to install the MS COCO APIs.

cd <CornetNet dir>/data
git clone https://github.com/cocodataset/cocoapi.git 
cd <CornetNet dir>/data/coco/PythonAPI
make

Download the training/validation split we use in our paper from here (originally from Faster R-CNN)
Unzip the file and place annotations under <CornetNet dir>/data/coco
Download the images (2014 Train, 2014 Val, 2017 Test) from here
Create 3 directories, trainval2014, minival2014 and testdev2017, under <CornerNet dir>/data/coco/images/
Copy the training/validation/testing images to the corresponding directories according to the annotation files

We provide the configuration file (CornerNet.json) and the model file (CornerNet.py) for CornerNet in this repo.

To train CornerNet:

python train.py

To use the trained model:

python test.py

##In the next few days I will provide model parameters that are trained on coco.