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Interactive Handwritten Digit Recognition: An intuitive Keras and TensorFlow powered app with Streamlit UI. Draw and predict digits in real-time.

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Digit-Delineator

Description

Digit Delineator is an application that predicts handwritten digits. It uses a model trained on the MNIST dataset with TensorFlow and Keras, and the user interface is built with Streamlit.

App Screenshot

Installation

  1. Clone the repository:
git clone https://github.com/achrafib1/Digit-Delineator.git
  1. Navigate to the project directory:
cd Digit-Delineator
  1. (Recommended) Create a virtual environment:
python3 -m venv env
  1. Activate the virtual environment:

    • On Windows:
      .\env\Scripts\activate
      
    • On Unix or MacOS:
      source env/bin/activate
      
  2. Install the required packages:

pip install -r requirements.txt

Usage

To run the application, use the following command:

  • On Windows, use:

    streamlit run src\app.py
  • On macOS or Linux, use:

    streamlit run src/app.py

Then, open your web browser and go to http://localhost:8501 to view the app.

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Interactive Handwritten Digit Recognition: An intuitive Keras and TensorFlow powered app with Streamlit UI. Draw and predict digits in real-time.

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