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caffe-yolov3-windows's Introduction

caffe-yolov3-windows

A caffe implementation of MobileNet-YOLO (YOLOv2 base) detection network, with pretrained weights on VOC0712 and mAP=0.709

Network mAP Resolution Download NetScope
MobileNet-YOLO-Lite 0.675 416 deploy graph
MobileNet-YOLOv3-Lite 0.737 416 deploy graph
MobileNet-YOLOv3-Lite 0.717 320 deploy graph

Note :

  1. Training from linux version and test on windows version , the mAP of MobileNetYOLO-lite was 0.668

Performance

Compare with YOLOv2 , I can't find yolov3 score on voc2007 currently

Network mAP Weight size Inference time (GTX 1080) Inference time (i5-4440)
MobileNet-YOLOv3-Lite 0.717 20.3 mb 6 ms (320x320) 150 ms
MobileNet-YOLOv3-Lite 0.737 20.3 mb 11 ms (416x416) 280 ms
Tiny-YOLO 0.57 60.5 mb N/A N/A
YOLOv2 0.76 193 mb N/A N/A

Note : the yolo_detection_output_layer not be optimization , and the deploy model was made by merge_bn.py

Oringinal darknet-yolov3

Converter

mAP Resolution Download NetScope
53.9 416 caffemodel graph

test on coco_minival_lmdb (IOU 0.5)

Other models

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

Linux Version

MobileNet-YOLO

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

alt tag

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

Future work

  1. COCO training and eval

Reference

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

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

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

https://github.com/duangenquan/YoloV2NCS

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