🌿 AI Cassava Disease Detection Lab

Advanced Deep Learning System for diagnosing Cassava leaf diseases with Explainable AI (Grad-CAM) and Real-time Camera integration.

---

📸 Demo Preview

⚡ Real-time Diagnosis in Action

🖥️ Interface Gallery

Desktop UI (Upload Mode)	Mobile UI (Camera Mode)
Modern Glassmorphism Design with Drag & Drop support.	Optimized for Mobile with Rear Camera integration.

📊 Dashboard & Analytics

Smart Archive System
Automatic statistics generation (Chart.js) and history tracking.

---

✨ Key Features

• 🧠 High-Accuracy AI: Utilizes a fine-tuned CNN model (MobileNet/ResNet) to classify 5 specific cassava leaf conditions (CBB, CBSD, CGM, CMD, Healthy).
• 🔥 Explainable AI (XAI): Integrated Grad-CAM Heatmap technology to visualize exactly where the AI is "looking" on the leaf, increasing trust and transparency.
• 📷 Dual-Mode Input:
  • Upload Mode: Drag & drop support for high-res images.
  • Camera Mode: Real-time capture supported on both Desktop (Webcam) and Mobile (Environment/Rear Camera).
• 📊 Smart Dashboard: Automatically tracks diagnosis history and visualizes disease distribution using interactive charts (Chart.js).
• 📄 Automated Reporting: Generates professional PDF reports with original images, heatmaps, and expert advice with a single click.
• 🎨 Modern UI/UX: Responsive Glassmorphism design (Dark/Light mode adaptive) providing a "Lab-like" experience.

---

🛠️ Tech Stack

• Core: Python 3.10
• Deep Learning: TensorFlow, Keras
• Computer Vision: OpenCV (cv2), NumPy
• Web Framework: Flask (Python)
• Frontend: HTML5, CSS3 (Animations), JavaScript
• Visualization: Chart.js (Analytics), Matplotlib (Heatmaps)

---

🚀 Installation & Setup

1. Clone the repository

   git clone [https://github.com/MingDanng/Cassava_WebApp.git](https://github.com/MingDanng/Cassava_WebApp.git)
   cd Cassava-AI-Lab

2. Install dependencies

   pip install -r requirements.txt

3. Download the Model

   • Note: The model file (>100MB) is hosted externally due to GitHub limits.
   • 👉 CLICK HERE TO DOWNLOAD MODEL
   • Action: Download the file cassava_best.keras and place it in the root directory of this project (same folder as app.py).

4. Run the Application

   python app.py

   Access the app at: http://127.0.0.1:5000

---

📂 Project Structure

Cassava_AI_Project/
│
├── assets/                  # Demo Images (.png) & GIFs for README
├── static/                  # CSS, Images, JS
│   ├── heatmaps/            # Generated Heatmaps
│   ├── images/              # Uploaded Images
│   └── pdfs/                # Generated Reports
├── templates/               # HTML Interfaces
│   ├── index.html           # Main Upload/Camera Page
│   ├── result.html          # AI Result & Heatmap Page
│   └── archive.html         # Dashboard & Statistics
├── app.py                   # Main Flask Application
├── cassava_best.keras       # Trained AI Model (Downloaded separately)
└── requirements.txt         # Dependencies list

---

👨‍💻 Author

Nguyen Phuc Minh Dang

• Role: Developer & AI Researcher
• GitHub: https://github.com/MingDanng
• Email: dangnguyen0303@gmail.com
• Project: University Capstone / Portfolio 2026