Eurosat Deep Learning for Land Use and Land Cover Classification 🌍🛰️

This project aims at classifying land use and land cover from the Eurosat dataset using Deep Learning techniques. The dataset comprises satellite images from the Sentinel-2 mission, which are used to train a Convolutional Neural Network (CNN) for image classification.

Features 🌟

• Utilizes the Eurosat dataset for training and testing the model.
• Employs the VGG-16 architecture with modifications to adapt to the number of classes and input channels.
• Provides detailed data loading and preprocessing to handle multi-band satellite images.
• Offers insights into the model's performance through accuracy, precision, recall, F1-score, and a confusion matrix.
• Visualizes training progress, class distributions, and predictions.

Setup and Installation 🛠️

1. Clone the repository.
2. Install the necessary Python packages listed in requirements.txt.
3. Download the Eurosat dataset and prepare it according to the instructions provided.

Data 📁

The Eurosat dataset contains labeled satellite images covering 10 different classes of land use and land cover. Images are in TIFF format with multiple spectral bands.

Model Training and Testing 🚀

• The model is trained using a pre-processed subset of the Eurosat dataset.
• Training includes several epochs with batch processing, validation checks, and performance logging.
• Testing is performed to evaluate the model's accuracy and generalization on unseen data.

Results and Evaluation 📊

• Performance metrics are calculated for the test dataset to evaluate model accuracy.
• A confusion matrix is generated to understand the classification performance across different classes.
• Sample images with predictions are displayed to visualize the model's capabilities.

Contributing 🤝

We welcome contributions to improve the project. Feel free to fork the repository, make your changes, and submit a pull request.

License 📜

The project is licensed under the MIT License - see the LICENSE file for more details.

Acknowledgements 🙌

• The Eurosat dataset providers for creating and distributing such a valuable resource for satellite image analysis.
• The PyTorch team for providing an excellent deep learning framework.

For more information and updates, visit the GitHub repository.