A RetroSearch Logo

Home - News ( United States | United Kingdom | Italy | Germany ) - Football scores

Search Query:

Showing content from https://github.com/eric612/Caffe-YOLOv2-Windows below:

eric612/Caffe-YOLOv3-Windows: A windows caffe implementation of YOLO detection network

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

Network mAP Resolution Download NetScope Inference time (GTX 1080) Inference time (i5-4440) MobileNet-YOLOv3-Lite 0.747 320 caffemodel graph 6 ms 150 ms MobileNet-YOLOv3-Lite 0.757 416 caffemodel graph 11 ms 280 ms

MobileNet-YOLO

Compare with YOLO , (IOU 0.5)

Converter

test on coco_minival_lmdb (IOU 0.5)

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

network mAP resolution macc param PVA-YOLOv3 0.703 416 2.55G 4.72M Pelee-YOLOv3 0.703 416 4.25G 3.85M Configuring and Building Caffe

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

> cd $caffe_root
> script/build_win.cmd 
> cd $caffe_root/
> examples\demo_yolo_lite.cmd

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

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

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

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

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

RetroSearch is an open source project built by @garambo | Open a GitHub Issue

Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo

HTML: 3.2 | Encoding: UTF-8 | Version: 0.7.4