This repository contains code for a Convolutional Neural Network (CNN) model that classifies images of Dungeons and Dragons (DnD) dice.

The model is built using TensorFlow and Keras, and trained on a dataset of images of DnD dice.

• train_model.py: Contains the code for training the CNN model on your dataset.

• predict.py: Contains the code for loading a trained model and using it to classify a new image.

• dataset/: Directory containing the training and testing datasets. The dataset should be organized in the following structure:

• dataset/ train/ d20/ test/ d20/

Each subdirectory should contain images for the respective die.

1. Ensure you have the required dependencies installed:

pip install -r requirements.txt

2. Run train_model.py:

python train_model.py

The script will train the model on the images in the dataset/train directory and save the trained model to disk.

1. Ensure you have the required dependencies installed (if you haven't already):

pip3 install -r requirements.txt

2. Run predict.py with the path to the image you want to classify:

python3 predict.py

The script will load the trained model, process the input image, and output the predicted class of the dice.

This project is licensed under the terms of the MIT license.