I have been playing with Yolov8 for about 3 weeks now, I have been curating a British number plate tracking dataset. Using videos from youtube I trained a basic model and used this to help me label subsequent datasets. This takes the pain out of labeling every image manually. I have been using labelImg, anylabeling, and python scripts to extract the annotation section and view plates and perfect the dataset. This is the result so far which I am surprised how accurate it is. I have had to use a small batch size of 3 because I am training on 4k resolution images using a rtx3090.

as you can see above it still makes errors however, this was when I turned the confidence down to 0.02 to allow for more training data labels to be created, I then manually delete the false positives predictions by hand, which are not to numerous. This is easier than during the box labels.