Manuscript Digits Recogition

Application of Machine Learning and AI methods, such as Convolutional Neural Networks (CNN) and some preprocessing techniques for building a model capable of recoginizing manuscript digits precisely (PA 4 from Artificial Intelligence Course - DCOMP - UFSJ).

1. Requirements

• Python3 and pip package manager:

  sudo apt install python3 python3-pip build-essential python3-dev
  

• virtualenv tool:

  pip install virtualenv
  

• Libraries: Keras, TensorFlow, scikit-learn, Matplotlib, numpy, gdown and OpenCV;

• Environments: Jupyter.

2. Setting the Environment

1. Clone the repository

   git clone https://github.com/juliorodrigues07/manuscript_digit_recognition.git
   

2. Enter the repository's directory

   cd manuscript_digit_recognition
   

3. Create a virtual environment

   python3 -m venv .venv
   

4. Activate the virtual environment

   source .venv/bin/activate
   

5. Install the dependencies

   pip install -r requirements.txt
   

3. Execution

• To visualize the notebook online and run it (Google Colaboratory), click here:

• To run the notebook locally, run the following command in the notebooks directory:

  jupyter notebook digit_recognition.ipynb
  

4. Project Structure

.
├── README.md                       # Project's documentation
├── requirements.txt                # File containing all the required dependencies to run the project
├── plots                           # Directory containing all the graph plots generated
├── docs                            
|   ├── Documentação.pdf            <- Detailed documentation about the project
|   └── LaTeX           
├── notebooks                       # Directory containing project's main jupyter notebook
|   └── digit_recognition.ipynb
├── datasets                        # Directory containing all used or generated datasets in the project
|   └── digits                      # Directory containing own made digits for testing models
└── models                          # Directory containing all generated models in the project    

5. Outro

• To uninstall all dependencies, run the following command:

  pip uninstall -r requirements.txt -y
  

• To deactivate the virtual environment, run the following command:

  deactivate