路过的大佬给颗星星吧

待办

• 开放MNN模型转换脚本
• 开放andooid示例项目

MobileNetv2-YOLOv3-SPP Darknet

A darknet implementation of MobileNetv2-YOLOv3-SPP detection network

*emmmm...这个懒得训练，mAP就凑合这样吧

Darknet Group convolution is not well supported on some GPUs such as NVIDIA PASCAL!!! The MobileNetV2-YOLOv3-SPP inference time is 100ms at GTX1080ti, but RTX2080 inference time is 5ms!!!

MobileNetV2-YOLOv3-Lite&Nano Darknet

Mobile inference frameworks benchmark (4*ARM_CPU)

• Darknet Train Configuration: CUDA-version: 10010 (10020), cuDNN: 7.6.4,OpenCV version: 4 GPU:RTX2080ti
• Support mobile inference frameworks such as NCNN&MNN

MobileNetV2-YOLO-Fastest

• 快就完了，要啥mAP

Reference&Framework instructions&How to Train

• https://github.com/AlexeyAB/darknet
• You must use a pre-trained model to train your own data set. You can make a pre-trained model based on the weights of COCO training in this project to initialize the network parameters
• 交流qq群:1062122604

About model selection

• MobileNetV2-YOLOv3-SPP: Nvidia Jeston, Intel Movidius, TensorRT，NPU，OPENVINO...High-performance embedded side
• MobileNetV2-YOLOv3-Lite: High Performance ARM-CPU，Qualcomm Adreno GPU， ARM82...High-performance mobile
• MobileNetV2-YOLOv3-NANO： ARM-CPU...Computing resources are limited
• MobileNetV2-YOLOv3-Fastest： ....... Can you do personal face detection???It’s better than nothing

MobileNetV2-YOLOv3-Lite-COCO Test results

DarkNet2Caffe tutorial

Environmental requirements

• Python2.7
• python-opencv
• Caffe(add upsample layer https://github.com/dog-qiuqiu/caffe-upsample)

    cd darknet2caffe/
    python darknet2caffe.py MobileNetV2-YOLOv3-Nano-voc.cfg MobileNetV2-YOLOv3-Nano-voc.weights MobileNetV2-YOLOv3-Nano-voc.prototxt MobileNetV2-YOLOv3-Nano-voc.caffemodel
    cp MobileNetV2-YOLOv3-Nano-voc.prototxt sample
    cp MobileNetV2-YOLOv3-Nano-voc.caffemodel sample
    cd sample
    python detector.py

MNN conversion tutorial

• Convert darknet model to caffemodel through darknet2caffe
• Manually replace the upsample layer in prototxt with the interp layer
• Take the modification of MobileNetV2-YOLOv3-Nano-voc.prototxt as an example

#layer {
#    bottom: "layer71-route"
#    top: "layer72-upsample"
#    name: "layer72-upsample"
#    type: "Upsample"
#    upsample_param {
#        scale: 2
#    }
#}
layer {
    bottom: "layer71-route"
    top: "layer72-upsample"
    name: "layer72-upsample"
    type: "Interp"
    interp_param {
        height:20 
	      width:20
    }
}

• MNN conversion: https://www.yuque.com/mnn/cn/model_convert

NCNN conversion tutorial

• benchmark:https://github.com/Tencent/ncnn/tree/master/benchmark
• darknet2ncnn: https://github.com/Tencent/ncnn/tree/master/tools/darknet

NCNN Android Sample

• 白嫖中....

Thanks

• https://github.com/shicai/MobileNet-Caffe
• https://github.com/AlexeyAB/darknet
• https://github.com/Tencent/ncnn
• https://gluon-cv.mxnet.io/