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Support most of operator which convert mxnet to caffe.

Python 100.00%

advanced-mxnet2caffe's Introduction

Advanced-Mxnet2Caffe

Operator Support Lists

  • Convolution
  • ChannelwiseConvolution
  • BatchNorm
  • Activation
  • ElementWiseSum
  • _Plus
  • Concat
  • Crop
  • Pooling
  • Flatten
  • FullyConnected
  • SoftmaxOutput&SoftmaxFocalOutput
  • SoftmaxActivation
  • LeakyReLU
  • elemwise_add
  • UpSampling
  • Deconvolution
  • Clip
  • Reshape

Tested models

  • Mxnet-SSH
  • MobileNet-V2
  • Resnet-50
  • RetinaFace with ( Resnet-50 ,Mobilenet 0.25 backbone)
  • All models from Insightface Model Zoo .

Note&Bugs

The convertor Is not fully automatically, The convertor not

  • if you wanna convert upsampling operator , the convertor will convert Upsampling operator to Deconvolution in Caffe , The Deconvolution channels need to be set (in prototxt_basic.py names_output).
  • If you use Flatten Layer ,You need to manually to connect them becasuse the converted compute graph will be divided into two parts.
  • If convert a detection model. You need to remove the anchor process and put it into post process.
  • Usually,If you find that conversion errors, please set the prefix name of you backbone network in mxnet2caffe.py.

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