Converting a Caffe Model¶

Warning

Note that OpenVINO support for Caffe is currently being deprecated and will be removed entirely in the future.

To convert a Caffe model, run mo with the path to the input model .caffemodel file:

mo --input_model <INPUT_MODEL>.caffemodel

The following list provides the Caffe-specific parameters.

Caffe-specific parameters:
  --input_proto INPUT_PROTO, -d INPUT_PROTO
                        Deploy-ready prototxt file that contains a topology
                        structure and layer attributes
  --caffe_parser_path CAFFE_PARSER_PATH
                        Path to python Caffe parser generated from caffe.proto
  -k K                  Path to CustomLayersMapping.xml to register custom
                        layers
  --disable_omitting_optional
                        Disable omitting optional attributes to be used for
                        custom layers. Use this option if you want to transfer
                        all attributes of a custom layer to IR. Default
                        behavior is to transfer the attributes with default
                        values and the attributes defined by the user to IR.
  --enable_flattening_nested_params
                        Enable flattening optional params to be used for
                        custom layers. Use this option if you want to transfer
                        attributes of a custom layer to IR with flattened
                        nested parameters. Default behavior is to transfer the
                        attributes without flattening nested parameters.

CLI Examples Using Caffe-Specific Parameters¶

Launching model conversion for bvlc_alexnet.caffemodel with a specified prototxt file. This is needed when the name of the Caffe model and the .prototxt file are different or are placed in different directories. Otherwise, it is enough to provide only the path to the input model.caffemodel file.
```
mo --input_model bvlc_alexnet.caffemodel --input_proto bvlc_alexnet.prototxt
```
Launching model conversion for bvlc_alexnet.caffemodel with a specified CustomLayersMapping file. This is the legacy method of quickly enabling model conversion if your model has custom layers. This requires the Caffe system on the computer. Example of CustomLayersMapping.xml can be found in <OPENVINO_INSTALLATION_DIR>/mo/front/caffe/CustomLayersMapping.xml.example. The optional parameters without default values and not specified by the user in the .prototxt file are removed from the Intermediate Representation, and nested parameters are flattened:
```
 mo --input_model bvlc_alexnet.caffemodel -k CustomLayersMapping.xml --disable_omitting_optional --enable_flattening_nested_params

This example shows a multi-input model with input layers: ``data``, ``rois``
```
```
layer {
  name: "data"
  type: "Input"
  top: "data"
  input_param {
    shape { dim: 1 dim: 3 dim: 224 dim: 224 }
  }
}
layer {
  name: "rois"
  type: "Input"
  top: "rois"
  input_param {
    shape { dim: 1 dim: 5 dim: 1 dim: 1 }
  }
}
```
Launching model conversion for a multi-input model with two inputs and providing a new shape for each input in the order they are passed to the model conversion API. In particular, for data, set the shape to 1,3,227,227. For rois, set the shape to 1,6,1,1:
```
mo --input_model /path-to/your-model.caffemodel --input data,rois --input_shape (1,3,227,227),[1,6,1,1]
```

Custom Layer Definition¶

For the definition of custom layers, refer to the Cutting Off Parts of a Model page.

Supported Caffe Layers¶

For the list of supported standard layers, refer to the Supported Operations page.

Frequently Asked Questions (FAQ)¶

Model conversion API provides explanatory messages when it is unable to complete conversions due to typographical errors, incorrectly used options, or other issues. A message describes the potential cause of the problem and gives a link to Model Optimizer FAQ which provides instructions on how to resolve most issues. The FAQ also includes links to relevant sections in :doc:`Convert a Model <openvino_docs_MO_DG_Deep_Learning_Model_Optimizer_DevGuide>`to help you understand what went wrong.

Summary¶

In this document, you learned:

Basic information about how model conversion works with Caffe models.
Which Caffe models are supported.
How to convert a trained Caffe model by using model conversion API with both framework-agnostic and Caffe-specific command-line parameters.

Additional Resources¶

See the Model Conversion Tutorials page for a set of tutorials providing step-by-step instructions for converting specific Caffe models.