Skip to content

Latest commit

 

History

History
51 lines (46 loc) · 1.18 KB

README.md

File metadata and controls

51 lines (46 loc) · 1.18 KB
Raw

keras2ncnn

Now availabel on pypi!

If you failed to convert a model, welcome to open an issue and attach the h5 file.

Usage:

# Install keras2ncnn (only h5py and numpy is required)
python3 -mpip install --upgrade keras2ncnn

# If you only want to convert the model
python3 -m keras2ncnn -i SOME_H5DF_FILE.h5 -o ./  

# You can see the structure of the converted model and the original model(after optimization)
python3 -m keras2ncnn -i SOME_H5DF_FILE.h5 -o DIR_TO_SAVE_NCNN_PARAM --plot_graph/-p

Supported Op

  • InputLayer
  • Conv2D (Linear, Softmax, ReLU, Sigmoid)
  • Conv2DTranspose (Linear, ReLU, Sigmoid)
  • DepthwiseConv2D
  • SeparableConv2D (Linear, Softmax, ReLU, Sigmoid)
  • Add
  • Multiply
  • Concatenate
  • ZeroPadding2D
  • ReLU
  • LeakyReLU
  • Activation (Softmax, ReLU, Sigmoid)
  • UpSampling2D
  • BilinearUpsampling
  • Cropping2D
  • GlobalAveragePooling2D
  • GlobalMaxPooling2D
  • AveragePooling2D
  • MaxPooling2D
  • BatchNormalization
  • Dense (Linear, Softmax, ReLU, Sigmoid)
  • Flatten
  • Reshape
  • Maximum
  • TensorFlowOpLayer (Mul with constant)
  • Permute (Need more testing)

Ops that will be dropped by converter

  • Dropout
  • Lambda
  • TimeDistributed
  • InputLayer with inbound nodes