ExtReMLapin

I was annotating minutiaes , on big images, so there was two ways of fixing this, boosting the annotations size by 3 (and dividing by 3 at inference) and doing...

I had all my annotations and I decided to do : width = width*3, same for height. Show us some sample of your dataset so we can judge and see...

#3980 and this suggestion might also help a bit https://github.com/ggerganov/llama.cpp/issues/3980#issuecomment-1826269575 I would have expected the compiler to optimize it straight away 🤷🏻

@shroominic on my end it just gets slower the longer it is in printing the json array, no nested objects.

No issue on my end

> Thanks! Here is my another question: I put some pictures of products without flaw and the same quantity of empty labels in training data, will it improve the performance...

What worries me about your metrics is the signal amplitude, precidion goes up and down a lot. Could you show some annotated images (ones from the runs/exp00 folder for example...

What are your training settings ? Which model do you use and what are your images (resized) resolutions, show us the arguments

I was expecting your commandlines arguments, not python code but I guess the image resize is good enough. Try using the P2 model instead of the default ones https://github.com/ultralytics/yolov5/blob/master/models/hub/yolov5-p2.yaml

Yes, I asked for YOUR training params, not to see the python code, I expected you to send us your command line you use to start the training example :...