Hi everyone,
I’m working on a dataset of 932 images containing 4 classes: healthy leaf, healthy grape, frozen leaf, and frozen grape. The images were taken from different angles. In general:
- Leaves are large and clearly visible,
- Grapes are still in early growth stages and appear very small.
I trained a YOLOv11 model and even tried up to 10x augmentation, but the mAP50 is stuck around 43.2%, with only about a 2% improvement.
This made me wonder if the issue might be related to label quality, especially since the grapes are very small and might be inconsistently labeled or hard to detect.
I’d appreciate any feedback from those with experience:
- How can I check if my labels are the root of the problem?
- Are there any specific practices for labeling small objects?
- Would you recommend any alternative models or preprocessing techniques for this kind of dataset?
I’ve attached one labeled image from each class for reference.
Thanks in advance for your insights! 
