Hello @fernando_paradiso
I think, in that case, you don’t have enough data. I tried your model on Universe with a sample from your test dataset and it did show up when I was down to 1% confidence. This is the reason your label assist and inference weren’t working.
Also, looking at your dataset, you might be better off with an image classification model. It seems that your images always only have one plum and you have one label you want to assign to each image. It might be worth looking through this blog post to see if classification is the way to go for you.
Otherwise, I think you need more images to train with. One way to easily create more training data is to add more augmentations. I saw you have horizontal and vertical flip, which is a good start, but adding more types of augmentations to add variety to your dataset will likely help your model perform better and avoid overfitting.
Hope this helps.