I am trying to do the inference for an image enhancement workload in openvino. I could convert the model into IR. I tried to do the inference for the same using the ‘style_transfer_sample’ in python samples of openvino inference engine. But I am facing multiple issues.
assert len(net.outputs) == 1, "Sample supports only single output topologies"
AssertionError: Sample supports only single output topologies
I commented the assertions and tried running the same and now faces the below error.
"Invalid number of channels in input image:
Could you please let me know whether this sample (style_transfer_sample) is recommended for such a workload? If so, what all are the steps/changes I should make to do the inference without errors.
Thanks in advance.
The OpenVINO™ toolkit does not include a pre-trained model to run the Neural Style Transfer sample. A public model from the Zhaw's Neural Style Transfer repository can be used. To use the style transfer sample from OpenVINO™, follow the steps below as no public pre-trained style transfer model is provided with the OpenVINO toolkit:- https://docs.openvinotoolkit.org/2019_R3/_docs_MO_DG_prepare_model_convert_model_mxnet_specific_Conv...
The style transfer sample supports only single output topologies, which means the model should have single output layer as demonstrated in the above link.