🌿 Leaf Disease Classification with EfficientNetB0

Leaf-Disease-Classification-EfficientNetB0 is a deep learning-powered app that identifies 38 types of plant diseases from leaf images using a fine-tuned EfficientNetB0 model trained on the New Plant Diseases Dataset.

📸 Upload an image or select an example below. Get instant predictions on plant disease type — with confidence score and class label.

🌐 Demo

Deployed on Hugging Face Spaces:

🧠 Model Details

Model: EfficientNetB0 (Transfer Learning from ImageNet)
Classes: 38 plant disease types (Apple, Corn, Potato, Tomato, etc.)
Input Size: 224×224
Preprocessing: EfficientNet preprocess_input
Training:
- Optimizer: Adam
- Loss Function: Categorical Crossentropy
- Epochs: 20
Validation Accuracy: ~97%

📓 Training Notebook (Kaggle)

The model was trained using TensorFlow and Keras on Kaggle.
🔗 leaf-disease-classification-efficientnetb0-new1-1
Includes:

Data Augmentation (Shear, Zoom, Flip)
Early Stopping & Model Checkpointing
Confusion Matrix Visualization
Final .keras weights file exported

Features

Classifies 38 different plant diseases
Supports image upload and drag-and-drop
Outputs top 3 predicted classes with confidence scores
Lightweight & fast inference — powered by Gradio

📁 Folder Structure

Leaf-Disease-Project-CE180166/
├── app.py                   # Gradio interface main script
├── inference_utils.py       # Helper functions (Load model & Predict)
├── model/
│   └── final_model_20epochs.keras  # Trained Model Weights
├── assets/                  # Demo/test images
│   ├── Potato__Early_blight.jpg
│   └── ...
├── requirements.txt         # Dependencies
└── README.md                # Project Documentation

Downloads last month: 94