Optical Character Recognition (OCR) is a powerful technology that converts different types of documents, such as scanned paper documents, PDF files, or images captured by a digital camera, into editable and searchable data. Tesseract is one of the most popular open-source OCR engines available today. In this article, we will explore how to use Tesseract within a Docker container to perform OCR on PDF documents.
Why Use Docker for OCR?
Docker provides a consistent environment for running applications, ensuring that the software behaves the same way regardless of where it is deployed. By using Docker, you can easily manage dependencies and avoid the “it works on my machine” problem. This is particularly useful for OCR tasks, which often require specific versions of libraries and tools.
Setting Up Tesseract with Docker
Step 1: Install Docker
Before you begin, ensure that Docker is installed on your system. You can download Docker from the official website and follow the installation instructions for your operating system.
Step 2: Pull the Tesseract Docker Image
Tesseract has an official Docker image available on Docker Hub. You can pull this image using the following command:
docker pull tesseractshadow/tesseract4re
This command downloads the Tesseract OCR engine version 4, which includes support for LSTM-based OCR.
Step 3: Convert PDF to Images
Tesseract works with image files, so the first step in processing a PDF is to convert it into images. You can use a tool like pdftoppm, which is part of the Poppler utilities, to accomplish this. Install Poppler on your system and run the following command:
pdftoppm input.pdf output -png
This command converts each page of input.pdf into a PNG image, naming them output-1.png, output-2.png, and so on.
Step 4: Run Tesseract on Images
With the images ready, you can now use the Tesseract Docker container to perform OCR. Run the following command for each image:
docker run --rm -v $(pwd):/data tesseractshadow/tesseract4re output-1.png output-1
This command mounts the current directory into the Docker container and processes output-1.png, saving the OCR result to output-1.txt.
Step 5: Automate the Process
To automate the OCR process for all pages of a PDF, you can use a simple shell script:
#!/bin/bash
# Convert PDF to images
pdftoppm input.pdf output -png
# Perform OCR on each image
for img in output-*.png; do
docker run --rm -v $(pwd):/data tesseractshadow/tesseract4re "$img" "${img%.png}"
done
Save this script as ocr_pdf.sh, make it executable with chmod +x ocr_pdf.sh, and run it with ./ocr_pdf.sh.
Conclusion
Using Docker to run Tesseract for OCR tasks provides a robust and consistent environment that simplifies dependency management and deployment. By converting PDFs to images and processing them with Tesseract, you can easily extract text from scanned documents and images. This approach is not only efficient but also leverages the power of open-source tools to achieve high-quality OCR results.
References
By following the steps outlined in this article, you can effectively integrate OCR capabilities into your document processing workflows using Docker and Tesseract.