Crop diseases cause significant reductions in agricultural productivity and farmer income. While early detection is critical to preventing large-scale damage, farmers currently lack accessible, offline, and real-time diagnostic tools. This project aims to build an on-device, camera-based machine learning system that operates fully offline to identify crop diseases from leaf photographs, estimate severity levels, and provide actionable treatment recommendations directly at the point of need.
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