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OCR Model using TensorFlow and Keras

Overview

This project implements an Optical Character Recognition (OCR) model using TensorFlow and Keras. The model is trained on a dataset containing images of characters and their corresponding labels. It utilizes convolutional neural networks (CNNs) for feature extraction and recurrent neural networks (RNNs) for sequence modeling.

Installation

To run the OCR model, follow these steps:

  1. Upload your Kaggle API key file (kaggle.json) to the Google Colab environment.
  2. Install the Kaggle Python package using pip.
  3. Download the "ml-codefest" dataset using the Kaggle API.
  4. Unzip the downloaded dataset to a target folder.
  5. Run the provided code to train the OCR model.

The above 5 steps are done automatically after uploading the kaggle.json

You can get this from "https://www.kaggle.com/"

Usage

Once the model is trained, you can use it to perform OCR on images containing characters. The model can be used for tasks such as recognizing text in images, digitizing documents, etc.

Contributing

Contributions to this OCR model project are welcome. If you have any ideas, suggestions, or improvements, feel free to open an issue or create a pull request.

License

This project is licensed under the MIT License.