unable to understand outputs from IR model after converting it from Pytorch

[vkana3]

Hi

I'm Vishnu, I created a skin cancer detection pytorch model and successfully converted it to onnx and then to IR model.

However, when I perform inference on the model with an image to predict the class, I get output as given below:

  

for reference please use the links below:

The github link for this project : https://github.com/KVishnuVardhanR/skin_cancer_detection 

the colab notebook for the pytorch model : https://colab.research.google.com/drive/11-jb9W0FWbXZWAlzZluiLOwEMSHOY_CY#scrollTo=85XZfpL9qC5z 

Can anyone please help me resolve this issue!!!

[Iffa_Intel]

Greetings,

First and foremost, can you clarify what kind of output you were expecting and the format you expect to see from Pytorch.

This is to ensure that it is possible to achieve your target output with OpenVino.

Sincerely,

Iffa

[vkana3]

hi

In Pytorch, after passing the input to model, we use  torch.max(F.softmax(out,dim=1), dim=1)[1], to get our output.

In Openvino, as we are coverting our model, we have to use something like torch.max(F.softmax(out,dim=1), dim=1)[1] this to post process our outputs, but in numpy.

Can you please tell me how to do that in numpy?

[Iffa_Intel]

Generally, the torch.max returns the maximum value of all elements in the input tensor.

You can refer here for the similar function of torch.max in numpy:

https://github.com/torch/torch7/wiki/Torch-for-Numpy-users

*Refer to calculation section

Hope this helps!

Sincerely,

Iffa

[Iffa_Intel]

Greetings,

Intel will no longer monitor this thread since we have provided a solution. If you need any additional information from Intel, please submit a new question.

Sincerely,

Iffa