Hi, i’m currently trying to detect papaya fruit before it’s harvested, to put an example, this is the kind of photos that i will get in real situations:
So, i need to detect at least all fruits in the photo, to do so i’m trying a machine learning approach training using a 300 dataset that i found.
this was used in order of classificate each fruit in 3 categories: unmature, partially and mature. The problem is that this dataset is compose of individual photos of the fruit so after training a cascade model it doesn’t detect any papaya of my stock images (not the one posted here). Do i need to expand my dataset of individual papaya photos or use pictures with groups of papayas?