I have truncated version of vgg16 in .pb format. I am unable to convert to IR getting following error:
[ ANALYSIS INFO ] It looks like there is IteratorGetNext as input
Run the Model Optimizer with:
--input "IteratorGetNext:0[-1 224 224 3]"
And replace all negative values with positive values
[ ERROR ] Exception occurred during running replacer "REPLACEMENT_ID" (<class 'extensions.front.output_cut.OutputCut'>): Graph contains 0 node after executing <class 'extensions.front.output_cut.OutputCut'>. It considered as error because resulting IR will be empty which is not usual
python3 /opt/intel/openvino_2020.3.194/deployment_tools/model_optimizer/mo_tf.py --input_model fp_firesmokenet-2803-epoch-99.pb
Thanks for reaching out.
I would suggest that you first try specifying your input shapes. More information is available at the following page :
More information regarding converting a model using Model Optimizer is available as follows:
Additionally, please share more information about your model, whether it's an object detection/classification model, the layers used if it's a custom model and also environment details (versions of OS, TF, Python, CMake, etc.).
If possible, please share the trained model files for us to reproduce your issue (files can be shared via Private Message).
We suspect that the performance issue is due to conversion from TensorFlow to Intermediate Representation (IR), and would like to check the .json file that you are using as well.
As such, please share the command given to Model Optimizer to convert your trained model to IR.
More relevant information is available at the following page:
Thanks for the reply. Actually I was able to convert the model to IR. There are some performance issues now, it's basically a fire and smoke detection model, model is able to identify smoke when inference is done with checkpointed model. When doing inference with openvino, it doesn't detect smoke.
I am attaching the files, please check.
OpenVINO toolkit officially supports only non-frozen version of VGG-16 models.
More information is available at the following page:
Hence, I would suggest you try converting again using Model Optimizer based on the steps available in the following page: