So… I followed the tutorial from Jetson AI Fundamentals from here https://www.youtube.com/watch?v=sN6aT9TpltU . I encounter the problem when it comes to the running final command “imagenet --model=models/tools/resnet18.onnx --labels=data/tools/labels.txt --input_blob=input_0 --output_blob=output_0 c…

[image] sushi5005wot: Do you know if there is any hardware/software for Jetson Nano to communicate via EtherCat? Hi @sushi5005wot , I’m not familiar with EtherCat - you may want to open a new topic, or try searching the forums. Here is one I found about it: [image] Is…

Hi @sushi5005wot , what are the contents of your labels.txt? Do you see any classification confidence results being printed out to the terminal? Can you post the terminal log? Thanks.

Hi @dusty_nv , thanks for your reply. In labels.txt I have just 4 entries - “background, battery, bottle, foam.” Here’s the terminal log file: terminallog.txt (9.5 KB). I do not see anything suspicious, when launching cat_dog classification program I do not have problems. Thank you in advance.

What accuracy did you train your PyTorch model to? From looking at your log, the only way it would not print out any of the results, are if the confidence values are negative or very small (which typically means the model is invalid or not trained). Can you try commenting out this line from jetson…

Hi @dusty_nv , thanks for your advice. After commenting the line number 525 from imageNet.cpp object recognition works fine. But what should I do to set everything up properly without commenting line 525? Mabye I should re-install whole PyTorch?

[image] sushi5005wot: After commenting the line number 525 from imageNet.cpp object recognition works fine. What kind of confidence values are output by that print statement after you uncomment it? Are they very small?

@dusty_nv well, it depends. Confidence level for background is ~50%; for objects it is 40-70% (depends on the object.) Every class has 100 pictures in total and I trained them for 64 epochs, so this should work way better.

[image] sushi5005wot: Confidence level for background is ~50%; for objects it is 40-70% (depends on the object.) That is strange that it has “normal” confidence values, even though you had to comment out that line. Can you try un-commenting it out and running it again? Maybe it was unrel…

@dusty_nv it has pretty much the same confidence values, no matter if that line is commented out or not.

OK, and it is still working now even with that line the way it originally way (not commented out)? If so, I bet something else was going on, like for example the TensorRT engine needing refreshed based on your latest PyTorch model.

@dusty_nv After uncommenting, upper-left corner statement is still shown, so commenting, then uncommenting solved this issue. That is kinda strange. I guess I’ll try re-installing TensorRT engine and I will give some feedback then. Would you recommend any other useful tools/steps to build custom r…

Jetson Nano - Training image classification models

Robotics & Edge Computing Jetson Systems Jetson Nano

dusty_nv January 15, 2021, 6:29pm 14

Hi @sushi5005wot, I’m not familiar with EtherCat - you may want to open a new topic, or try searching the forums. Here is one I found about it:

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Jetson Nano - Training image classification models

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