Plant diseases remain one of the biggest challenges to food security, especially for smallholder farmers who rely on staple crops like maize across Eswatini. Traditional methods of detecting leaf blights and rusts require direct visual inspection by agricultural experts, which is often slow, reactive, and hard to scale across remote fields.
Why YOLOv7 for Smart Farming?
By harnessing the real-time object detection capabilities of the YOLOv7 framework, we can identify specific foliar issues seamlessly. The model processes input frames directly from basic smartphones, running inference algorithms that point exactly to lesions on the leaves, allowing localized treatments rather than blanket chemical distributions.