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A caffe implementation of MobileNet-YOLO detection network

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CODE UPDATED FOR OPENCV 3

MobileNet-YOLO Caffe

This project also support ssd framework , and here lists the difference from ssd caffe

  • Multi-scale training , you can select input resoluton when inference
  • Modified from last update caffe (2018)
  • Support multi-task model
  • pelee + driverable map

MobileNet-YOLO

A caffe implementation of MobileNet-YOLO detection network , train on 07+12 , test on VOC2007

Network mAP Resolution Download NetScope Inference time (GTX 1080) Inference time (i5-7500)
MobileNetV2-YOLOv3 70.7 352 caffemodel graph 6.65 ms 217 ms
  • inference time was log from script , does not include pre-processing
  • the benchmark of cpu performance on Tencent/ncnn framework
  • the deploy model was made by merge_bn.py, set eps = your prototxt batchnorm eps
  • old models please see here

CNN Analyzer

Use this tool to compare macc and param , train on 07+12 , test on VOC2007

network mAP resolution macc param
MobileNetV2-YOLOv3 0.707 352 1.22G 4.05M
Pelee-SSD 0.709 304 1.2G 5.42M
Mobilenet-SSD 0.68 300 1.21G 5.43M

Coverted TensorRT models

TensorRT-Yolov3-models

Pelee-Driverable_Maps, run 89 ms on jetson nano , running project

YOLO Segmentation

How to use

Windows Version

Caffe-YOLOv3-Windows

Oringinal darknet-yolov3

Converter

test on coco_minival_lmdb (IOU 0.5)

Network mAP Resolution Download NetScope
yolov3 54.2 416 caffemodel graph
yolov3-spp 59.8 608 caffemodel graph

Model VisulizationTool

Supported on Netron , browser version

Build , Run and Training

See wiki

License and Citation

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

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

Reference

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

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

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

https://github.com/yonghenglh6/DepthwiseConvolution

https://github.com/alexgkendall/caffe-segnet

https://github.com/BVLC/caffe/pull/6384/commits/4d2400e7ae692b25f034f02ff8e8cd3621725f5c

https://www.cityscapes-dataset.com/

https://github.com/TuSimple/tusimple-benchmark/wiki

https://github.com/Robert-JunWang/Pelee

https://github.com/hujie-frank/SENet

Cudnn convolution

https://github.com/chuanqi305/MobileNetv2-SSDLite/tree/master/src

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A caffe implementation of MobileNet-YOLO detection network

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  • C++ 70.5%
  • Makefile 9.1%
  • Python 9.0%
  • Cuda 6.1%
  • CMake 3.7%
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