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开源软件名称(OpenSource Name):KaleidoZhouYN/mobilefacenet-caffe开源软件地址(OpenSource Url):https://github.com/KaleidoZhouYN/mobilefacenet-caffe开源编程语言(OpenSource Language):Python 100.0%开源软件介绍(OpenSource Introduction):mobilefacenet-caffea caffe implementation of mobilefacenet,with the record of trainnig log update the deploy.prototxt & training log of Amsoftmax on Webface @ 24/4/2018 update the solver.prototxt & training log of 6W iteration in ./proto_revise/ @ 30/4/2018 update @ 7/5/2018: since there is a re-implementation of mobilefacenet by insightface: https://github.com/deepinsight/insightface you can train on public dataset using insightface then transform the mxnet model to caffe model using MxNet2Caffe pay attention that: 1.there is something to be fixed in insightface/src/symbols/fmobilefacenet.py you can just download the fmobilefacent.py in this project and replace it in insightface. then type: CUDA_VISIBLE_DEVICES='0,1,2,3' python -u train_softmax.py --network y1 --loss-type 4 --margin-m 0.5 --data-dir ../datasets/faces_ms1m_112x112 --prefix ../model-y1 --emb-size = 128 to train the mobilefacenet with insightface. 2.if you are using cudnn,the group convolution with cause a memory error while using Mxnet2Caffe so you have to add engine:CAFFE in each group convolution layer or you can download the prototxt_basic.py in this project and replace it in MXNet2Caffe Links: paper:MobileFaceNets: Efficient CNNs for Accurate Real-time Face Verification on Mobile Devices amsoftmax:happynear/AMSoftmax depthwise convolution:yonghenglh6/DepthwiseConvolution mobilenetv2-caffe:shicai/MobileNet-Caffe |
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