This is a Python application that processes answer sheets in PDF format and retrieves the score and symbol number of students.

The Answer Sheet Processing Application allows users to upload answer sheets in PDF format. The application then extracts relevant information, such as the score and symbol number, from the uploaded answer sheets using computer vision techniques. The extracted information is displayed to the user on a result page.

The project directory structure is as follows: app.py answer_sheets/ answer_sheet_1.pdf answer_sheet_2.pdf ... templates/ index.html result.html

• app.py: The main Python file that contains the application code.
• answer_sheets/: A directory that stores the answer sheets in PDF format.
• templates/: A directory that contains HTML templates for the user interface.

To set up and run the application, follow these steps:

1. Clone this repository to your local machine.
2. Install the required dependencies by running pip install opencv-python PyPDF2 Flask.
3. Place the answer sheets you want to process in the answer_sheets/ directory.
4. Run the app.py file using Python: python app.py.
5. Open your web browser and visit http://localhost:5000 to access the application.

1. Open the application in your web browser.
2. Fill out the form on the home page.
3. Upload an answer sheet in PDF format.
4. Click the "Submit" button.
5. The application will process the answer sheet and display the result page.
6. The result page will show the retrieved score and symbol number for the uploaded answer sheet.

The Answer Sheet Processing Application relies on the following dependencies:

• OpenCV: A computer vision library for image processing.
• PyPDF2: A library to handle PDF files.
• Flask: A web framework for building the user interface.

These dependencies are listed in the requirements.txt file.

Contributions are welcome! If you find any issues or have suggestions for improvements, please open an issue or submit a pull request.

This project is licensed under the MIT License.