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 71.5 352 caffemodel graph 6.65 ms 217 msThis project also support ssd framework , and here lists the difference from ssd caffe
Use this tool to compare macc and param , train on 07+12 , test on VOC2007
network mAP resolution macc param pruned IOU_THRESH GIOU MobileNetV2-YOLOv3 0.707 352 1.22G 4.05M N N N MobileNetV2-YOLOv3 0.715 352 1.22G 4.05M N Y Y MobileNetV2-YOLOv3 0.702 352 1.01G 2.88M Y N N Pelee-SSD 0.709 304 1.2G 5.42M N N N Mobilenet-SSD 0.68 300 1.21G 5.43M N N N MobilenetV2-SSD-lite 0.709 336 1.10G 5.2M N N NPelee-Driverable_Maps, run 89 ms on jetson nano , running project
test on coco_minival_lmdb (IOU 0.5)
Supported on Netron , browser version
See wiki
See docker
Please cite MobileNet-YOLO in your publications if it helps your research:
@article{MobileNet-YOLO,
Author = {eric612 , Avisonic , ELAN},
Year = {2018}
}
https://github.com/BVLC/caffe/pull/6384/commits/4d2400e7ae692b25f034f02ff8e8cd3621725f5c
Cudnn convolution
https://github.com/chuanqi305/MobileNetv2-SSDLite/tree/master/src
https://github.com/AlexeyAB/darknet
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