abhijit-tk / deforest-detection-analyser

Deforest-Detection-Analyser

This Streamlit app is designed to detect deforestation in images using K-means clustering. It takes an image as input and segments it into regions of potential afforestation and deforestation.

Usage

1. Clone the repository:

   git clone https://github.com/your_username/deforestation-detection.git

2. Navigate to the project directory:

   cd deforestation-detection

3. Install the required packages:

   pip install -r requirements.txt

4. Run the Streamlit app:

   streamlit run app.py

5. Upload an image using the file uploader and observe the segmentation of the image into afforestation and deforestation regions.

Requirements

• Python 3.6+
• OpenCV
• NumPy
• Streamlit
• Matplotlib

File Structure

• app.py: The main Streamlit application code.
• requirements.txt: Contains the list of required Python packages and their versions.
• assets/: Directory to store static assets like images, CSS, or JavaScript files.

Acknowledgements

This project is based on the concept of K-means clustering for image segmentation and utilizes Streamlit for building the interactive web application.

License

This project is licensed under the MIT License.