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Hello,
I installed Ubuntu 18.04.3 LTS in my pc(HP-ProDesk-400-G3-MT) and installed Intel distribution of OpenvinoToolkit, l_openvino_toolkit_p_2019.3.376.tgz(https://software.intel.com/en-us/openvino-toolkit) as well. I am able to run the demo application successfully to test the Openvino Toolkit installation.
I developed a Keras model backed by a Tensorflow engine, 1.x. I developed this model using the transfer learning strategy, for that reason I used the VGG16 pre-trained model. This Keras model(model_weights_tomato_earlyblight_updated.h5) gives predictions on the testing and validation dataset. To optimize and inference this Keras model through intel distribution of OpenvinoToolkit, I converted this Keras model to TensorFlow model. I just captured the Keras session to capture the frozen graph and save the model as Tensorflow model as protocol buffer or pb format. I have attached the conversion code too. It works fine.
When I try to run the optimization for this Tensorflow model, from, /opt/intel/openvino/deployment_tools/model_optimizer/mo_tf.py , I get the attached errors. Could you please advise me on what to do next or anything I have missed?
I followed the reference for optimization on the Tensorflow model guided by pooja during training and by reading the documentation too.
and
https://docs.openvinotoolkit.org/latest/_docs_MO_DG_Deep_Learning_Model_Optimizer_DevGuide.html
I have also attached the Keras Model(.h5 file, weight file), conversion code, and TensorFlow Model and errors.
Thanks
Fakrul
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Hi Islam, Fakrul,
Thanks for reaching out. I am able to convert the model you have attached just fine, I was able however to reproduce the issue you experienced when specifying the --input_shape flag with the values [1,224,224,3].
Here is the command I used to convert the model, please give it a try and let me know the results. Hope this helps!
python3 /opt/intel/openvino/deployment_tools/model_optimizer/mo_tf.py --input_model tomato_earlyblight_model_tensorflow.pb -b 1
Output:
Model Optimizer arguments: Common parameters: - Path to the Input Model: /home/pse/843155/All contents/tomato_earlyblight_model_tensorflow.pb - Path for generated IR: /home/pse/843155/All contents/. - IR output name: tomato_earlyblight_model_tensorflow - Log level: ERROR - Batch: 1 - 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 TensorFlow specific parameters: - Input model in text protobuf format: False - Path to model dump for TensorBoard: None - List of shared libraries with TensorFlow custom layers implementation: None - Update the configuration file with input/output node names: None - Use configuration file used to generate the model with Object Detection API: None - Operations to offload: None - Patterns to offload: None - Use the config file: None Model Optimizer version: 2019.3.0-408-gac8584cb7 … ... [ SUCCESS ] Generated IR model. [ SUCCESS ] XML file: /home/pse/843155/All contents/./tomato_earlyblight_model_tensorflow.xml [ SUCCESS ] BIN file: /home/pse/843155/All contents/./tomato_earlyblight_model_tensorflow.bin [ SUCCESS ] Total execution time: 5.09 seconds.
Find the converted model attached as well, let me know if you have any questions.
Regards,
Luis

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