This a comprehensive implementation on YOLO V3. It includes training, testing, detecting using local images and using webcam. Besides this repo, I have a blog post that elaborates the key concepts in YOLO and more details about the coding process. Click here!
git clone https://github.com/Ray-Luo/YOLOV3-PyTorch.git
cd YOLOV3-PyTorch/
sudo pip3 install -r requirements.txt
wget https://www.dropbox.com/s/bnwucfzv6torx2t/weights.zip
wget https://www.dropbox.com/s/6qihvaqt0aqdlf2/sample.zip
unzip -q weights.zip
unzip -q sample.zip
python3 ./train.py
python3 ./detect.py
python3 ./camera.py
python3 ./test.py
@article{yolo,
title={You Only Look Once: Unified, Real-Time Object Detection},
author={Redmon, Joseph and Farhadi, Ali},
journal = {arXiv},
year={2016}
}
@article{yolov2,
title={YOLO9000: Better, Faster, Stronger},
author={Redmon, Joseph and Farhadi, Ali},
journal = {arXiv},
year={2016}
}
@article{yolov3,
title={YOLOv3: An Incremental Improvement},
author={Redmon, Joseph and Farhadi, Ali},
journal = {arXiv},
year={2018}
}
https://github.com/marvis/pytorch-yolo2
https://github.com/pjreddie/darknet
https://github.com/eriklindernoren/PyTorch-YOLOv3
https://github.com/ayooshkathuria/pytorch-yolo-v3