🪨 Rock Classification with ResNet18

A simple PyTorch project that classifies rocks by image using a ResNet18 model. The model can predict both:

• Main class: Igneous, Metamorphic, Sedimentary
• Subclass: Basalt, Granite, Marble, Quartzite, Coal, Limestone, Sandstone

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📁 Folder Structure

• Dataset/ → Rock image dataset
• archive/Dataset/ → Backup copy of the dataset
• models/
  • rock_resnet18_mainclass.pth → predicts main rock classes (3)
  • rock_resnet18_subclass.pth → predicts detailed subclasses (7)
• notebooks/
  • resnet18.ipynb → model training
  • preprocessing.ipynb → resizing, normalization, splitting
  • data_augmentation.ipynb → flipping, rotation, brightness

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🧪 How to Use

Open the notebooks in Jupyter or VS Code and run:

• resnet18.ipynb to train or evaluate
• Make sure you have the dataset and models in place

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🔧 Requirements

Install required libs with:

pip install torch torchvision matplotlib