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I am working through the C++ Hello Classification example
I am confused by these 2 lines:
output_info = network.getOutputsInfo().begin()->second;
output_name = network.getOutputsInfo().begin()->first;
- What does configuring the output of the model mean?
- Does it mean that it changes the size, the type of inference that is run, where it is saved?
- What is being configured here?
- How does the output change if I had not used these 2 lines, would the example break?
- Is this always optional (?), for any type of inference I want to run, or do some inferences require this configuration?
- What changes in the inference pipeline if these are not included in the example?
- What benefit does this configuration provide in this example?
- I understand "first" and "second" provide info and names, what would happen if I did not have these names, would I not be able to GetBlob?
- Why are they called "first" and "second"?
- Are these arbitrary method names that actually mean get output info and get output name?
(FYI posted something similar here but it seems that the thread has died and Intel won't respond.)
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Hello Adammpolak,
I noticed that your questions already answered in the previous post and thanks for satisfying the provided answers. Hence, I am going to close this case.
If you need any additional information from Intel, please submit a new question as this thread is no longer being monitored.
Regards,
Peh
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