Create README.md

Author: curtainteddy

README.md

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+# Nepali Currency Recognition Classifier
+
+This repository contains code for a Nepali currency recognition classifier implemented in Python using TensorFlow and Keras.
+
+## Overview
+
+The classifier is based on a pre-trained VGG16 model with additional layers added for fine-tuning to the specific task of recognizing Nepali currency notes. It is trained on a dataset consisting of images of Nepali currency notes belonging to 7 different classes.
+
+## Files
+
+- `Nepali_Currency_Recognition_Classifier.ipynb`: Jupyter Notebook containing the code for the classifier.
+- `currency_classifier_model.h5`: Saved model file containing the trained classifier model.
+- `Prediction Checker/`: Folder containing test images for evaluating the classifier.
+
+## Usage
+
+1. **Training**: The notebook contains code for training the classifier. Simply run the notebook cells to train the model.
+
+2. **Testing**: Once trained, you can test the classifier on new images by placing them in the `Prediction Checker/` folder and running the prediction code provided in the notebook.
+
+## Dataset
+
+Please note that the training dataset is not included in this repository due to its size. You can download the dataset from [Kaggle](https://www.kaggle.com/datasets/gauravneupane/nepali-rupees-collection). After downloading, extract the dataset and arrange the folder structure as follows:
+
+dataset/
+│
+├── train/
+│ ├── class_1/
+│ ├── class_2/
+│ ├── ...
+│ └── class_n/
+│
+└── valid/
+├── class_1/
+├── class_2/
+├── ...
+└── class_n/
+
+
+Replace `class_1`, `class_2`, etc., with the actual class names or labels of the currency notes.
+
+## Dependencies
+
+- TensorFlow
+- Keras
+- Matplotlib
+- NumPy
+
+## License
+
+This project is licensed under the GPL-3.0 License - see the [LICENSE](LICENSE) file for details.
+