README.md

Renewable Energy Potential Predictor

This Hugging Face Space provides an interactive interface for predicting wind and solar power potential based on satellite imagery and environmental data.

How to Use

1. Upload the required images:

   • RGB Satellite Image
   • NDVI (Normalized Difference Vegetation Index) Image
   • Terrain Map
   • Elevation Data (as .npy file)

2. Enter weather parameters:

   • Wind Speed (m/s)
   • Wind Direction (degrees)
   • Temperature (°C)
   • Humidity (%)

3. Click "Submit" to generate predictions

The model will output two heatmaps showing the predicted wind and solar power potential for the given location.

Input Requirements

• All images should be in RGB or grayscale format
• Elevation data should be a NumPy array saved as .npy file
• Weather parameters should be within reasonable ranges

Example Data

The interface includes example data that you can use to test the model. Click "Run Example" to try it out.

Model Details

The predictor uses a deep learning model trained on satellite imagery and environmental data to estimate renewable energy potential. The model architecture combines CNN-based image processing with weather data integration for comprehensive predictions.