This is a Pytorch implementation of the paper "Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks". I reference faster_rcnn_pytorch and faster rcnn pytorch tuturial pytorch pull request but this request is not completed and closed.
I was about to study faster rcnn code but codes are too difficult to me. I need some simple tutorial but there is no simple code. so I tried to write simple code than other repo.
this repo's code are
Requirements
pytoch
tensorflow (Using tensorboad)
matplotlib
Usage
I use floydhub to train model Floydhub is simple deeplearining training tool
pip install -U floyd-cli
#./input
floyd data init voc
floyd data upload
#./FRCNN
floyd init frcnn
floyd data status
floyd run --env pytorch --gpu --data [your data id] "python3 main.py"
This porject structure is fitted with floydhub structure, so parent directory contain input, output, FRCNN directory
but you can traning any environment without floydhub
Training on Pascal VOC 2007
Follow this project (TFFRCNN) to download and prepare the training, validation, test data and the VGG16 model pre-trained on ImageNet.
Since the program loading the data in FRCNN/input by default, you can set the data path as following.
this repo is not completed. it's performance is low than other repo