Foliar Disease
Detection
in your browser.
YOLO26m-seg trained on 6,000+ field images of sugarcane leaves, exported to LiteRT and served entirely client-side via WebGPU — no server roundtrip for inference.
Try the Demo0.0%
mAP@0.5 Precision
Object detection accuracy measured across all confidence thresholds
5
Disease Classes
~0ms
p99 Latency
Typical on desktop GPU via WebGPU — measured live on your device in the dashboard
Sugarcane Leaf Disease Detection
Model loads on first use
Drag & drop a leaf image or click to upload
JPEG, PNG, or WebP — max 10MB