This project is a system designed to read and interpret the numbers on container boxes. It leverages image processing and optical character recognition (OCR) techniques to accurately capture and decode the information.

This project is a system designed to read and interpret the numbers on container boxes. It leverages image processing and optical character recognition (OCR) techniques to accurately capture and decode the information.

• Features
• Installation
• Usage
• Contributing
• License

• Image Processing: Enhance and preprocess images of container boxes.
• Optical Character Recognition (OCR): Recognize and interpret numbers on containers.
• Accuracy: High accuracy in reading numbers under various conditions.
• Scalability: Easily scalable to accommodate large datasets.

• Python > 3.9 < 3.12
• Pip install inference

1. Clone the repository:

   git clone https://github.com/Devision789/container-box-number-reader.git
   cd container-box-number-reader

2. Open file in colab / kaggle / jupyter notebook

1. Prepare your image dataset

2. Run the script .ipynb

3. The results will be saved in the excel

We welcome contributions to improve the system. Please follow these steps:

1. Fork the repository.
2. Create a new branch (git checkout -b feature-branch).
3. Make your changes.
4. Commit your changes (git commit -m 'Add some feature').
5. Push to the branch (git push origin feature-branch).
6. Open a pull request.

This project is licensed under the MIT License. See the LICENSE file for details.