ChashiBhAI on-device disease classifiers
Collection
Mobile-verified YOLO26-cls TFLite disease classifiers for ChashiBhAI (rice, brassica, corn). Author: Shakil Ahmed (Shaq2). • 4 items • Updated
How to use Shaq2/chashibhai-disease-classifiers with ultralytics:
# Couldn't find a valid YOLO version tag.
# Replace XX with the correct version.
from ultralytics import YOLOvXX
model = YOLOvXX.from_pretrained("Shaq2/chashibhai-disease-classifiers")
source = 'http://images.cocodataset.org/val2017/000000039769.jpg'
model.predict(source=source, save=True)Author: Shaq2 (Shakil Ahmed)
Collection: ChashiBhAI on-device disease classifiers
This repository is the suite landing page. Each crop is published as its own model (Hub convention: one model card, one artifact set, independent versioning).
| Model | Classes | TFLite | Preprocess vs .pt |
Role in app |
|---|---|---|---|---|
| chashibhai-rice-disease-cls | 8 | ~3.1 MB | Verified (variant C, 100% top-1) | Bundled in APK — demo primary |
| chashibhai-brassica-disease-cls | 11 | ~10.9 MB | Verified | Model Manager download |
| chashibhai-corn-disease-cls | 4 | ~10.9 MB | Pending OOD | Research preview / download |
This folder still hosts a combined snapshot under tflite/ and pytorch/ for a single-click download of the whole pack. Prefer the per-crop repos for citation and app wiring.
nms: false, softmaxed [1, nClasses]/255.0 RGB NHWClabels.json is canonical (never hardcode class names or preprocess)KrishokChat LLM, RAG, and extra .pt packs belong to RaiyanKhaan/KrishokChat-Advisory-System (arXiv:2606.29243). Those are cited, not claimed.
ChashiBhAI — Expo React Native, Bangla-first, on-device diagnosis.
Code: GitHub
MIT. See LICENSE and NOTICE.md.