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Crop_Disease_Detection_CNN
Shuvam-Maity/Crop_Disease_Detection_CNN
Crop_Disease_Detection_CNN is a machine learning model from Shuvam-Maity. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Nine specialist CNN models trained from scratch on 40,000+ leaf images across 9 crops and 33 disease classes.
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Public
Updated Jun 28, 2026
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At a glance
- Access
- Public
- Created
- Jun 28, 2026
- Updated
- Jun 28, 2026
- SHA
- b0b7e62b
Model card
From the Hugging Face model README
Crop Disease Detection CNN
Nine specialist CNN models trained from scratch on 40,000+ leaf images across 9 crops and 33 disease classes.
Models Included
| Crop | Classes | Test Accuracy |
|---|---|---|
| Tomato | 10 | 89.80% |
| Grape | 4 | 98.69% |
| Corn | 4 | 96.03% |
| Apple | 4 | 97.27% |
| Peach | 2 | 99.50% |
| Bell Pepper | 2 | 100% |
| Potato | 3 | 96.30% |
| Cherry | 2 | 99.65% |
| Strawberry | 2 | 99.15% |
Framework
TensorFlow / Keras — trained from scratch, no transfer learning.
Dataset
PlantVillage (via Mohanty et al.)
Usage
from tensorflow import keras
model = keras.models.load_model("tomato_model.keras")
- Created
- Jun 28, 2026
- Updated
- Jun 28, 2026