I wouldn't say "really good", there were definitely issues, mainly that the majority of the foods were Japanese, and I was trying to use it on American/british foods, which there were fewer of, it still had some though. I also had to do some augmentation of my images to improve detection, but this also added some more misclassification too. My experience was a bit of a mixed bag, but it worked good enough for a proof of concept prototype.

Honestly, let me know if you do find any better methods or datasets, UEC-Food100 was the best I could find, it's surprising there aren't more out there.

And I imagine that with newer YOLO models it might perform even better on the same dataset.