Version 1.0.0 — Initial release

CottonVerse 🌿

CottonVerse is a multi-model Flask-based web application for image classification tasks in the agricultural and textile domains. It enables interpretable prediction using Grad-CAM and supports four independent models:

• 🍃 Cotton Leaf Disease (CottonLeafNet)
• 🌿 Cotton Leaf Disease (SAR-CLD-2024)
• 🧵 Fabric Texture Percentage (CottonFabricImageBD)
• 🩸 Fabric Stain Type (FabricSpotDefect)

🚀 Features

• 📁 Drag-and-drop file upload
• ✅ Prediction probabilities with visual bar chart
• 🔥 Grad-CAM visualization for interpretability
• 📸 Upload preview and CAM download
• 🖼️ Multiple datasets and models supported
• 🧠 Powered by LEViT model (via PyTorch + timm)
• 🎨 Responsive, modern, and interactive UI

📂 Project Structure

cottonverse/
├── app.py                     # Flask app
├── utils.py                   # Preprocessing & Grad-CAM logic
├── models/                    # Trained .pth models
├── static/
│   ├── uploads/               # Uploaded images
│   └── cams/                  # Grad-CAM outputs
├── templates/                 # HTML templates
└── requirements.txt           # Dependencies
└── README.md

⚙️ Installation

1. Clone the repository:

git clone https://github.com/rezaul-h/CottonVerse.git
cd cottonverse

1. Create and activate a virtual environment:

python -m venv venv
source venv/bin/activate  # or venv\Scripts\activate

1. Install dependencies:

pip install -r requirements.txt

1. Run the application:

python app.py

1. Open http://127.0.0.1:5000 in your browser 🌐

📊 Models & Datasets

| Model Name | Dataset | Classes | |------------|------------------------|---------| | LEViT | CottonLeafNet | 8 | | LEViT | SAR-CLD-2024 | 9 | | LEViT | CottonFabricImageB | 13 | | LEViT | FabricSpotDefect | 12 |

All models are trained using the LEViT architecture with PyTorch, saved in .pth format.

🧪 How to Use

1. Click on a model on the landing page.
2. Upload an image for classification.
3. View prediction probabilities and Grad-CAM.
4. Download the CAM if desired.

📦 Dependencies

• Flask
• PyTorch
• timm
• torchvision
• OpenCV
• matplotlib
• pytorch-grad-cam

🙏 Acknowledgements

• LEViT model: Facebook AI
• GradCAM: Jacob Gildenblat (pytorch-grad-cam)