RiceBorer-CLS: Rice Stem-Borer Symptom Classification using YOLO26
This research prototype classifies uploaded rice-plant images into Healthy, Dead Heart, or White Head using the trained YOLO26s-cls Ultralytics image-classification model exported to ONNX. Developed by Partha Pratim Ray, Sikkim University, on 31 July 2026.
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Input: 320 × 320
Execution: Browser/WASM
Images remain on your device
2. Classification result
Upload an image and select Classify Image.
Model information
| Model | YOLO26s-cls |
|---|---|
| Format | ONNX, dynamic export, opset 17 |
| Task | Three-class image classification |
| Classes | Healthy, Dead Heart, White Head |
| Input size | 320 × 320 pixels |
| Runtime | ONNX Runtime Web with WebAssembly |
Dataset information
| Dataset | Symptom-Labeled Image Dataset of Rice Plants for Stem Borer Infestation Classification |
|---|---|
| Authors | Chonchal Khan and Md Assaduzzaman |
| Original images | 2,096 |
| Distribution | Healthy 1,106; Dead Heart 439; White Head 551 |
| DOI | 10.17632/hnfjs42d5g.1 |
| Licence | CC BY 4.0 |