Hopefully you’re not including unlabelled images with objects you want to detect in training. If you do, assuming that 90% of your data is unlabeled, it would be indicating to the model that 90% of data does not have any objects to detect. Additionally, 144 images is not going to be enough data to train a model that performs well. If you look at the COCO dataset, which is what the pretrained YOLO models are trained on, you’ll see that there are several thousand images/instances of objects like car, truck, person, cat, dog, etc. That’s how these models are able to perform well on new data. Icons don’t change a lot, but there are an infinite number of layouts, so you’ll need to ensure you have lots of variation in the layouts for the various symbols you want to detect.
BurhanQ
6
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