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

I use the following training path to improve accuracy , and decrease lite version trainning time

• First , train MobileNet-YOLOv3 on coco dataset
• Second , train MobileNet-YOLOv3-Lite on coco dataset , pretrain weights use the first step output
• Finally , train MobileNet-YOLOv3-Lite on voc dataset , pretrain weights use the second step output

Caffe-YOLOv3-Windows

Converter

test on coco_minival_lmdb (IOU 0.5)

• I haven't implement correct_yolo_boxes and relative function , so here only support square input resolution

Compare with YOLO , (IOU 0.5)

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

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

See wiki

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

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