Unable to Run OpenCV* text_detection.cpp Sample with CRNN_CS Model Using OpenVINO™ Toolkit

• Converted crnn_cs.onnx text recognition model to Intermediate Representation (IR):
  python mo.py --input_model crnn_cs.onnx
• Encountered error when running OpenCV text_detection.cpp sample with the generated IR files:
  (expected: 'outs.size() == (size_t)1'), where 'out.size()' is 5 must be equal to '(size_t)1' is 1
• The IR files contain 5 outputs, while the original ONNX model has only one output.

OpenCV text_detection.cpp sample expects DNN library to perform an output check and will prompt an error if more than 1 output is detected.

Replace Result  to FakeResult  in crnn_cs.xml file for extra nodes:

• name="LSTM_183/FinalConcat/CellState/sink_port_0" type="Result"
• name="LSTM_183/FinalConcat/HiddenState/sink_port_0" type="Result"
• name="LSTM_201/FinalConcat/CellState/sink_port_0" type="Result"
• name="LSTM_201/FinalConcat/HiddenState/sink_port_0" type="Result"

• name="LSTM_183/FinalConcat/CellState/sink_port_0" type="FakeResult"
• name="LSTM_183/FinalConcat/HiddenState/sink_port_0" type="FakeResult"
• name="LSTM_201/FinalConcat/CellState/sink_port_0" type="FakeResult"
• name="LSTM_201/FinalConcat/HiddenState/sink_port_0" type="FakeResult"

When converting models to IR using Model Optimizer, it is possible that certain layers are split during optimization, and the additional nodes are recognized as valid nodes by OpenVINO library.