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Hi, great tutorial. I have chosen Yolov5s6 model for training my data. My results for inferences didn't come out as I expected. Each image was detected 50% sth on average. I annotated 1274 images. Do you think I should've selected more images? Does this result have to do with my number of inputs?
Hi, Lihi! Where do I get the requirements.txt file?
The requirements.txt file is in the yolov5 repo.
Hi. Where is the 'hyp.finetune.yaml'? Does it not exist anymore? Should I use something else like 'hyp.VOC.yaml'. I believe I will have to decrease the learning rate further.
where is all the data now? I'm trying to reproduce this and there is no images nor .jaml file
Thanks for this tutorial!
Do the input images need to have the expected size (1280x1280)? If they are a different size, will they be rescaled?
Hi @eribnick,
I'm glad you found the tutorial helpful. The detector was optimized for that specific input size, but you can use any other input size. The images are rescaled before entering the network. You can choose the image size to which you want to rescale your images using the --img parameter.
Good luck!
Changes
Hello @Lihi-Gur-Arie, thanks for the tutorial it helped me understand, how to use yolo. One thing I'd like to understand better would be, let's say I have 5000 images of same class, do I need to manually label all 5k images, or labeling let's say 10% is enough? ( I know there are other factors which can effect that percentage, I just want to know if it's doable with 10% or not)
Hello @Lihi-Gur-Arie, Thank you very much for this tutorial.
Could you please provide some information about the sizes of the training, validation and testing sets?
Thanks again, Good Luck!
Hi there, great tutorial; I was wondering if was possible to share the roboflow repository too?
Thanks!