qqadssp / RetinaNet-Pytorch

An implementation of RetinaNet in Pytonch

RetinaNet

This is an implementation of RetinaNet in Pytorch, using ResNet as backbone and FPN. Its base on the code of Detectron and pytorch-retinanet.

Train on VOC

1.Download PASCAL VOC 2012 trainval datasets and unzip it. Its path should be '{root_dir}/VOCdevkit/..'

2.Download this repo

git clone [e-mail]:qqadssp/RetinaNet.git  
cd RetinaNet  

3.Download pretrained weights from https://download.pytorch.org/models/resnet50-19c8e357.pth

cd checkpoint  
wget https://download.pythorch.org/models/resnet50-19c8e357.pth  
cd ..  

4.Initialize the model

python init.py  

5.Modify configs file in 'config'. For VOC datatsets, modify 'TRAIN: DATASETS_DIR' with your {root_dir}

6.Trian the model

python train.py --cfg ./configs/RetinaNet_ResNet50_FON_VOC.yaml  

Test on VOC

1.Download PASCAL VOC 2012 test datasets and unzip it. Its path should be '{root_dir}/VOCdevkit_test/..'

2.Modify ocnfig file in 'configs'. For VOC datasets, modify 'TEST: DATASETS_DIR' with your {root_dir}, and 'TEST: WEIGHTS' with the trained weights in 'checkpoint'

3.Test the model. The result files will be in 'result'.

python test.py --cfg ./configs/RetinaNet_ResNet50_FPN_VOC.yaml