DISEASE_DETECTOR

🐮 About The Project

DISEASE_DETECTOR is an AI-powered web application designed to identify livestock diseases from images. Built with a robust MobileNetV2 deep learning model and wrapped in a Flask backend, this tool provides rapid, on-site disease diagnosis to help protect herds and ensure animal health.

The frontend features a distinct Modern Brutalism design aesthetic—prioritizing raw functionality, high contrast, and a bold, industrial look.

🛠️ Tech Stack

• Core: Python 3
• Deep Learning: TensorFlow, Keras (MobileNetV2 architecture)
• Backend: Flask
• Frontend: HTML5, CSS3 (Brutalism Style), JavaScript
• Image Processing: Pillow (PIL), NumPy

✨ Features

• Instant Analysis: Upload an image and get immediate disease predictions.
• High Accuracy: Utilizes a pre-trained MobileNetV2 model fine-tuned for livestock skin conditions.
• 7 Detectable Classes:
  • Bovine Respiratory Disease
  • Contagious Ecthyma
  • Dermatitis
  • Healthy
  • Lumpy Skin Disease
  • And more...
• Responsive Design: Works on desktop and mobile devices.

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🚀 Getting Started

Follow these steps to set up the project locally.

Prerequisites

• Python 3.8 or higher
• pip (Python package manager)

Installation

1. Clone the repository

   git clone https://github.com/im-Amrith/DISEASE_DETECTOR.git
   cd DISEASE_DETECTOR

2. Set up the Virtual Environment It is recommended to use the provided virtual environment or create a new one.

   # Create a new venv (if not using venv1)
   python -m venv venv
   
   # Activate it
   # Windows:
   .\venv\Scripts\activate
   # Mac/Linux:
   source venv/bin/activate

3. Install Dependencies

   pip install -r requirement.txt

   Note: This project requires tf_keras for legacy model compatibility.

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🖥️ Usage

1. Navigate to the app directory

   cd app

2. Run the Flask Server

   python server.py

3. Access the Application Open your web browser and go to: http://127.0.0.1:5000

4. Analyze an Image

   • Click [ UPLOAD IMAGE ].
   • Select a clear photo of the livestock skin condition.
   • Click ANALYZE NOW.
   • View the status report and prediction.

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📂 Project Structure

DISEASE_DETECTOR/
├── app/
│   ├── trained_model/      # Contains the .h5 model file
│   ├── static/             # CSS and JavaScript files
│   ├── templates/          # HTML templates
│   ├── server.py           # Main Flask application
│   └── class_indices.json  # Mapping of class IDs to names
├── requirement.txt         # Python dependencies
└── README.md               # Project documentation

⚠️ Disclaimer

This tool is for educational and supportive purposes only. It should not replace professional veterinary diagnosis. Always consult with a qualified veterinarian for definitive treatment plans.