Potato-Disease-Classification

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Potato-Disease-Classification

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# 🥔 Potato Leaf Disease Classification using CNN

This project is a **Deep Learning–based Potato Leaf Disease Classifier** built using a **Convolutional Neural Network (CNN)**.  
The model classifies potato leaf images into **Healthy**, **Early Disease Detection**, and **Late Disease Detection** stages, helping in **early identification and prevention of crop loss**.

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## 🚀 Project Objective

- Detect potato leaf diseases at an early stage  
- Reduce crop damage by enabling timely treatment  
- Provide an automated and accurate classification system using Deep Learning

---

## 🧠 Model Overview

- Model Type: **Convolutional Neural Network (CNN)**
- Learning Type: **Supervised Learning**
- Framework: **TensorFlow + Keras**
- Visualization: **Matplotlib**

---

## 🏷️ Classes

The dataset is categorized into **three classes**:

1. **Healthy Leaf**
2. **Early Disease Detection**
3. **Late Disease Detection**

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## 📂 Dataset Description

- Image-based dataset of potato leaves  
- Contains real-world leaf images  
- Labeled into three categories:
  - Healthy
  - Early stage infected
  - Late stage infected  
- Used for training, validation, and testing

📌 **Purpose of Dataset:**  
To detect disease severity and help farmers take preventive actions at the right time.

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## 🛠️ Technologies & Libraries Used

### 🔧 Programming Language
- Python

### 📚 Libraries & Frameworks
- TensorFlow
- Keras
- NumPy
- Pandas
- Matplotlib

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## ⚙️ Model Architecture (CNN)

- Convolutional Layers
- ReLU Activation
- Max Pooling Layers
- Flatten Layer
- Fully Connected (Dense) Layers
- Softmax Output Layer

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## 📊 Training & Evaluation

- Data preprocessing and normalization
- Image augmentation for better generalization
- Loss Function: **Categorical Crossentropy**
- Optimizer: **Adam**
- Evaluation Metrics:
  - Accuracy
  - Loss
  - Confusion Matrix
  - Classification Report

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## 📈 Visualization

- Training vs Validation Accuracy
- Training vs Validation Loss
- Confusion Matrix
- Prediction results visualization using Matplotlib

---

## ▶️ How to Run the Project

```bash
# Clone the repository
git clone https://github.com/your-username/potato-leaf-disease-classifier.git

# Navigate to project directory
cd potato-leaf-disease-classifier

# Install required libraries
pip install -r requirements.txt

# Train the CNN model
python train.py

# Test the model
python test.py

Potato-Disease-Classification

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