🌱 New Project: Deep Learning CNN Model for Tomato Leaf Disease Prediction
📌 Description
This project introduces a Deep Learning-based Convolutional Neural Network (CNN) model trained on a Tomato Leaf Image Dataset to detect and classify various tomato plant diseases. The model can distinguish between multiple disease categories as well as healthy leaves, helping farmers and researchers in early disease detection and crop protection.
🦠 Diseases Covered
The trained CNN model can accurately classify tomato leaves into the following categories:
- Bacterial spot
- Early blight
- Late blight
- Leaf mold
- Septoria leaf spot
- Spider mites (Two-spotted spider mite)
- Target spot
- Tomato Yellow Leaf Curl Virus
- Healthy Tomato Leaf 🌿
📊 Model Performance
- ✅ Training Accuracy: 99.96%
- ✅ Testing Accuracy: 96.99%
- ⚖️ The model is not overfit or underfit, indicating strong generalization.
🖼️ Sample Outputs
- Tomato Leaf with Bacterial Spot
- Tomato Leaf with Septoria Leaf Spot
- Tomato Leaf with Tomato Yellow Leaf Curl Virus
📂 Repo Placement
projects/Day-XXX-Tomato-Disease-Prediction-CNN/
│── dataset/
│── model/
│── tomato_cnn.py
│── README.md
⚙️ Tech Stack
- Python 3
- TensorFlow / Keras (Deep Learning)
- OpenCV / Pillow (Image Preprocessing)
- NumPy, Pandas (Data Handling)
- Matplotlib / Seaborn (Visualization)
▶️ How to Run
-
Clone the repository
-
Navigate to the project folder
-
Install dependencies:
pip install tensorflow keras numpy pandas matplotlib seaborn opencv-python
-
Train or load the pretrained model:
-
Test on sample images
🚀 Future Enhancements
- Deploy as a Streamlit web app for user-friendly predictions
- Add real-time detection using camera feed
- Extend the dataset with more crop varieties
- Provide disease treatment recommendations along with predictions
🔗 Event: GirlScript Summer of Code (GSSoC’25)
🏷️ Type: New Project Addition
🌱 New Project: Deep Learning CNN Model for Tomato Leaf Disease Prediction
📌 Description
This project introduces a Deep Learning-based Convolutional Neural Network (CNN) model trained on a Tomato Leaf Image Dataset to detect and classify various tomato plant diseases. The model can distinguish between multiple disease categories as well as healthy leaves, helping farmers and researchers in early disease detection and crop protection.
🦠 Diseases Covered
The trained CNN model can accurately classify tomato leaves into the following categories:
📊 Model Performance
🖼️ Sample Outputs
📂 Repo Placement
⚙️ Tech Stack
Clone the repository
Navigate to the project folder
Install dependencies:
Train or load the pretrained model:
Test on sample images
🚀 Future Enhancements
🔗 Event: GirlScript Summer of Code (GSSoC’25)
🏷️ Type: New Project Addition