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OpenVINO: Model optimizer conversion error



When I run the Model Optimizer on  Faster-R-CNN model  ( Win10,  Caffe),  conversion doesn't work. Please help me solve the problem, thank you very much.


C:\Intel\computer_vision_sdk_2018.4.420\deployment_tools\inference_engine\samples\object_detection_demo>python %MO_ROOT_PATH%/ --input_model ZF_faster_rcnn_final.caffemodel --input_proto test.prototxt

Model Optimizer arguments:
Common parameters:
        - Path to the Input Model:      C:\Intel\computer_vision_sdk_2018.4.420\deployment_tools\inference_engine\samples\object_detection_demo\ZF_faster_rcnn_final.caffemodel
        - Path for generated IR:        C:\Intel\computer_vision_sdk_2018.4.420\deployment_tools\inference_engine\samples\object_detection_demo\.
        - IR output name:       ZF_faster_rcnn_final
        - Log level:    ERROR
        - Batch:        Not specified, inherited from the model
        - Input layers:         Not specified, inherited from the model
        - Output layers:        Not specified, inherited from the model
        - Input shapes:         Not specified, inherited from the model
        - Mean values:  Not specified
        - Scale values:         Not specified
        - Scale factor:         Not specified
        - Precision of IR:      FP32
        - Enable fusing:        True
        - Enable grouped convolutions fusing:   True
        - Move mean values to preprocess section:       False
        - Reverse input channels:       False
Caffe specific parameters:
        - Enable resnet optimization:   True
        - Path to the Input prototxt:   C:\Intel\computer_vision_sdk_2018.4.420\deployment_tools\inference_engine\samples\object_detection_demo\test.prototxt
        - Path to CustomLayersMapping.xml:      C:\Intel\computer_vision_sdk_2018.4.420\deployment_tools\model_optimizer\extensions\front\caffe\CustomLayersMapping.xml
        - Path to a mean file:  Not specified
        - Offsets for a mean file:      Not specified
Model Optimizer version:
Please expect that Model Optimizer conversion might be slow. You are currently using Python protobuf library implementation.
However you can use the C++ protobuf implementation that is supplied with the OpenVINO toolkitor build protobuf library from sources.
Navigate to "install_prerequisites" folder and run: python -m easy_install protobuf-3.5.1-py($your_python_version)-win-amd64.egg

 For more information please refer to Model Optimizer FAQ (<INSTALL_DIR>/deployment_tools/documentation/docs/MO_FAQ.html), question #80.
[ ERROR ]  Cannot infer shapes or values for node "rpn_conv/3x3".
[ ERROR ]  -1
[ ERROR ]  It can happen due to bug in custom shape infer function <function Convolution.infer at 0x00000282D83BB400>.
[ ERROR ]  Or because the node inputs have incorrect values/shapes.
[ ERROR ]  Or because input shapes are incorrect (embedded to the model or passed via --input_shape).
[ ERROR ]  Run Model Optimizer with --log_level=DEBUG for more information.
[ ERROR ]  Stopped shape/value propagation at "rpn_conv/3x3" node.
 For more information please refer to Model Optimizer FAQ (<INSTALL_DIR>/deployment_tools/documentation/docs/MO_FAQ.html), question #38.

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