importCaffeLayers

Import convolutional neural network layers from Caffe

Syntax

layers = importCaffeLayers(protofile)

layers = importCaffeLayers(protofile,'InputSize',sz)

Description

layers = importCaffeLayers(protofile) imports the layers of a Caffe [1] network. The function returns the layers defined in the .prototxt file protofile.

This function requires Deep Learning Toolbox™ Importer for Caffe Models support package. If this support package is not installed, then the function provides a download link.

You can download pretrained networks from Caffe Model Zoo [2].

layers = importCaffeLayers(protofile,'InputSize',sz) specifies the size of the input data. If the .prototxt file does not specify the size of the input data, then you must specify the input size.

Examples

Download Importer for Caffe Models Support Package

Download and install Deep Learning Toolbox Importer for Caffe Models support package.

Download the required support package by typing importCaffeLayers at the command line.

importCaffeLayers

If Deep Learning Toolbox Importer for Caffe Models support package is not installed, then the function provides a link to the required support package in the Add-On Explorer. To install the support package, click the link, and then click Install.

Import Layers from Caffe Network

Specify the example file 'digitsnet.prototxt' to import.

protofile = 'digitsnet.prototxt';

Import the network layers.

layers = importCaffeLayers(protofile)

layers = 

  1x7 Layer array with layers:

     1   'testdata'   Image Input             28x28x1 images
     2   'conv1'      Convolution             20 5x5x1 convolutions with stride [1  1] and padding [0  0]
     3   'relu1'      ReLU                    ReLU
     4   'pool1'      Max Pooling             2x2 max pooling with stride [2  2] and padding [0  0]
     5   'ip1'        Fully Connected         10 fully connected layer
     6   'loss'       Softmax                 softmax
     7   'output'     Classification Output   crossentropyex with 'class1', 'class2', and 8 other classes

Input Arguments

protofile — File name

character vector

File name of the .prototxt file containing the network architecture, specified as a character vector. protofile must be in the current folder, in a folder on the MATLAB^® path, or you must include a full or relative path to the file. If the .prototxt file does not specify the size of the input data, you must specify the size using the sz input argument.

Example: 'digitsnet.prototxt'

Data Types: char

sz — Size of input data

row vector

Size of input data, specified as a row vector. Specify a vector of two or three integer values [h,w], or [h,w,c] corresponding to the height, width, and the number of channels of the input data.

Example: [28 28 1]

Output Arguments

layers — Network architecture

Layer array | LayerGraph object

Network architecture, returned as a Layer array or a LayerGraph object. Caffe networks that take color images as input expect the images to be in BGR format. During import, importCaffeLayers modifies the network so that the imported MATLAB network takes RGB images as input.

Tips

• importCaffeLayers can import networks with the following Caffe layer types, with some limitations:

  • Input

  • Convolution

  • Deconvolution

  • Batch Norm

  • ReLU

  • Tanh

  • Local Response Normalization (LRN)

  • Pooling

  • Inner Product/Fully Connected

  • Dropout

  • Concat

  • Eltwise (only sum)

  • Softmax With Loss

  • Euclidean Loss

  If the network contains any other type of layer, then the software returns an error.

  The function imports only the layers that protofile specifies with the include-phase TEST. The function ignores any layers that protofile specifies with the include-phase TRAIN.

References

[1] Caffe. https://caffe.berkeleyvision.org/.

[2] Caffe Model Zoo. https://caffe.berkeleyvision.org/model_zoo.html.