caffe-yolov3-windows

A caffe implementation of MobileNet-YOLO detection network , first train on COCO trainval35k then fine-tune on 07+12 , test on VOC2007

• the benchmark of cpu performance on Tencent/ncnn framework
• the deploy model was made by merge_bn.py , or you can try my custom version
• bn_model download here

Linux Version

MobileNet-YOLO

Performance

Compare with YOLO , (IOU 0.5)

• (*) testdev-2015 server was closed , here use coco 2014 minival

Oringinal darknet-yolov3

Converter

test on coco_minival_lmdb (IOU 0.5)

Other models

You can find non-depthwise convolution network here , Yolo-Model-Zoo

Configuring and Building Caffe

Requirements

• Visual Studio 2013 or 2015
• CMake 3.4 or higher (Visual Studio and Ninja generators are supported)
• Anaconda

The build step was the same as MobileNet-SSD-windows

> cd $caffe_root
> script/build_win.cmd 

Mobilenet-YOLO Demo

> cd $caffe_root/
> examples\demo_yolo_lite.cmd

If load success , you can see the image window like this

Trainning Prepare

Download lmdb

Unzip into $caffe_root/

Please check the path exist "$caffe_root\examples\VOC0712\VOC0712_trainval_lmdb"

Trainning Mobilenet-YOLOv3

> cd $caffe_root/
> examples\train_yolov3_lite.cmd

Reference

https://github.com/weiliu89/caffe/tree/ssd

https://pjreddie.com/darknet/yolo/

https://github.com/gklz1982/caffe-yolov2

https://github.com/duangenquan/YoloV2NCS

https://github.com/eric612/Vehicle-Detection

https://github.com/eric612/MobileNet-SSD-windows

License and Citation

Please cite MobileNet-YOLO in your publications if it helps your research:

@article{MobileNet-YOLO,
  Author = {eric612,Avisonic},
  Year = {2018}
}