Image Classification
ultralytics
LiteRT
Bengali
English
yolo26-cls
agriculture
bangladesh
crop-disease
yolo26
on-device
brassica
chashibhai
Instructions to use Shaq2/chashibhai-brassica-disease-cls with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use Shaq2/chashibhai-brassica-disease-cls 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-brassica-disease-cls") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Add v2 labels.json
Browse files- v2/labels.json +32 -0
v2/labels.json
ADDED
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{
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"crop": "brassica-disease",
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"task": "classify",
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"imgsz": 640,
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"inputShape": [
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1,
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640,
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640,
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3
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],
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"outputShape": [
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1,
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11
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],
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"softmaxed": true,
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"preprocess": "centercrop",
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"preprocessVerified": true,
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"names": [
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"Cabbage__Alternaria_Spot",
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"Cabbage__Black_Rot",
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"Cabbage__Downy_Mildew",
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"Cabbage__Healthy_Leaf",
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"Cauliflower__Alternaria_Disease",
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"Cauliflower__Bacterial_Soft_Rot",
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"Cauliflower__Bacterial_Spot",
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"Cauliflower__Black_Spot",
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"Cauliflower__Downy_Mildew",
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"Cauliflower__Healthy",
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"Cauliflower__Nutrient_Deficiency"
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],
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"version": "v2"
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}
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