nexus-ocr

Task:

A command‐line tool to do OCR and extract text from a given scanned document image.

Input

Scanned document images ( include English only ). Your command accepts the following file formats.

• PNG
• JPEG
• PDF

Output

Extracted texts as a text file.

python your_code.py --input=./test.pdf --output=output.text --verbose

Interface

• –input : input file
• –output : output text file
• –verbose : verbose mode ( output detailed logs )

Requirements

Before doing the OCR process with TessaractOCR, does pre‐processing to improve OCR accuracy.

Regulations

• Uses Click as an command line interface builder
• Uses Poetry to install required thirdparty packages
• Uses yapf and isort to format python codes
• Uses logging package to do output. Never use print for log output.

OCR Streamlit Application

This application performs Optical Character Recognition (OCR) on PDF and image files (PNG, JPG) using easyocr and pdf2image libraries. The application is built using Streamlit for a user-friendly web interface.

Features

• Extract text from PDF files.
• Extract text from image files (PNG, JPG).
• Supports verbose logging for detailed processing information.

Requirements

• Python 3.7+
• Streamlit
• OpenCV
• EasyOCR
• PDF2Image
• Poppler (for PDF support)

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/ocr-streamlit-app.git
   cd ocr-streamlit-app

2. Set up a virtual environment (optional but recommended):

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install the required Python packages:

   pip install -r requirements.txt

4. Install Poppler:

   On Windows:

   • Download the latest release from Poppler for Windows.
   • Extract the ZIP file to a directory, e.g., C:\poppler.
   • Add the bin directory of Poppler to your system PATH.
     • Open the Start Menu and search for "Environment Variables".
     • Select "Edit the system environment variables".
     • Click "Environment Variables...".
     • Under "System variables", find and select the Path variable, then click "Edit...".
     • Click "New" and add the path to the bin directory, e.g., C:\poppler\bin.

   On macOS:

   • Install Homebrew if not already installed:

     /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"

   • Install Poppler using Homebrew:

     brew install poppler

   On Linux:

   • For Debian-based systems (Ubuntu):

     sudo apt-get install poppler-utils

   • For Red Hat-based systems (Fedora):

     sudo dnf install poppler-utils

Running the Application

1. Start the Streamlit app:

   streamlit run ocr_app.py

2. Open your web browser and go to:

   http://localhost:8501
   

3. Upload a PDF or image file and extract text.

Example

Here's a quick example of how to use the application:

1. Run the Streamlit app.
2. Upload a PDF or image file.
3. Click on the "Process" button.
4. The extracted text will be displayed on the web page.

Troubleshooting

• AttributeError: module 'PIL.Image' has no attribute 'Resampling':

  • Upgrade Pillow to the latest version:

    pip install --upgrade pillow

• PDFInfoNotInstalledError: Unable to get page count. Is poppler installed and in PATH?:

  • Ensure that Poppler is installed and the path to its bin directory is added to your system PATH.

License

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

Contributing

Contributions are welcome! Please open an issue or submit a pull request for any changes.