🥔 Potato Disease Classification - Deep Learning Project

A deep learning web application built with TensorFlow and Flask that classifies potato leaf diseases from uploaded images. The app predicts whether the leaf is:

• Early Blight 🍂
• Late Blight 🧫
• Healthy ✅

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🚀 Features

• Image upload and real-time prediction
• Clean, responsive frontend with CSS styling
• Background image with blur effect
• Trained on custom dataset using Convolutional Neural Networks
• Outputs the disease class only (no probability/confidence)

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🧠 Model Overview

• Input shape: 256x256x3
• 6 Conv2D layers with ReLU and MaxPooling
• Dense layers for final classification (Softmax)
• Model saved as potatoes.h5

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🗂️ Project Structure

Potato-Disease-Classification/ │ ├── app.py # Flask backend ├── potatoes.h5 # Trained model ├── requirements.txt # Python dependencies │ ├── static/ │ ├── css/ │ │ └── style.css # App styling │ └── images/ │ └── logo.png # Background image │ ├── templates/ │ └── index.html # Main HTML page │ └── README.md # Project description

yaml Copy Edit

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⚙️ Installation & Setup

✅ 1. Clone the repo

git clone https://github.com/aliahmad552/Potato-Disease-Classification.git
cd Potato-Disease-Classification

✅ 2. Install dependencies

pip install -r requirements.txt

✅ 3. Run the Flask app

python app.py
Now visit: http://127.0.0.1:5000

📂 Dataset

Custom dataset with three classes (Early Blight, Late Blight, Healthy)

Train/Validation/Test split handled using ImageDataGenerator

Image size: 256x256, normalized between 0-1

💻 Author

Ali Ahmad BS Software Engineering – The Islamia University of Bahawalpur GitHub: aliahmad552