openvino/docs/MO_DG/prepare_model/convert_model/Converting_Model.md

Converting a Model to Intermediate Representation (IR)

Use the mo.py script from the <INSTALL_DIR>/deployment_tools/model_optimizer directory to run the Model Optimizer and convert the model to the Intermediate Representation (IR). The simplest way to convert a model is to run mo.py with a path to the input model file and an output directory where you have write permissions:

python3 mo.py --input_model INPUT_MODEL --output_dir <OUTPUT_MODEL_DIR>

Note

: Some models require using additional arguments to specify conversion parameters, such as --scale, --scale_values, --mean_values, --mean_file. To learn about when you need to use these parameters, refer to Converting a Model Using General Conversion Parameters.

The mo.py script is the universal entry point that can deduce the framework that has produced the input model by a standard extension of the model file:

• .caffemodel - Caffe* models
• .pb - TensorFlow* models
• .params - MXNet* models
• .onnx - ONNX* models
• .nnet - Kaldi* models.

If the model files do not have standard extensions, you can use the --framework {tf,caffe,kaldi,onnx,mxnet,paddle} option to specify the framework type explicitly.

For example, the following commands are equivalent:

python3 mo.py --input_model /user/models/model.pb

python3 mo.py --framework tf --input_model /user/models/model.pb

To adjust the conversion process, you may use general parameters defined in the Converting a Model Using General Conversion Parameters and Framework-specific parameters for:

• Caffe,
• TensorFlow,
• MXNet,
• ONNX,
• Kaldi.
• Paddle.

See Also

• Configuring the Model Optimizer
• IR Notation Reference
• Model Optimizer Extensibility
• Model Cutting