Tesseract-OCR-5-Docker 📜

Docker Image with latest Tesseract OCR Version 5.x.x built from sources.

The sources are pulled from the latest main branch and latest releases of the Tesseract OCR project.

Docker Hub: https://hub.docker.com/r/franky1/tesseract

Usage 🛠️

Pull Docker Image ⌨️

Pull the docker image from Docker Hub:

docker pull franky1/tesseract

Run Docker Container ⌨️

Mount your image data to the /tmp directory and run Tesseract OCR container with the required command line options, for example, run Tesseract OCR container with test image:

docker run -it -v ${PWD}/testdata:/tmp --rm franky1/tesseract \
  tesseract english.png output --oem 1 -l eng

For the Tesseract command line options, please refer to the Tesseract Manual

Mount more languages 🗣️

Test if the mounted languages from your local subfolder /tessdata are available in the Docker container. Be aware that the local languages overwrite the installed languages in the Docker image. Example here with french language:

docker run -it -v ${PWD}/testdata:/tmp \
  -v ${PWD}/tessdata:/usr/local/share/tessdata/ \
  --rm franky1/tesseract

Test the mounted languages in the Docker container with a sample image. Example here with french language:

docker run -it -v ${PWD}/testdata:/tmp \
  -v ${PWD}/tessdata:/usr/local/share/tessdata/ \
  --rm franky1/tesseract \
  tesseract french.jpg output --oem 1 -l fra

Alternatively, you can build a new Docker image if you want other languages, see next section.

Build Docker Image yourself 🐳

For details have a look into the Dockerfile.

1. Git clone this repo.
2. Add your required languages to the languages.txt file.
3. Build the docker image.
   • To build with the main branch of Tesseract:

     docker build --progress=plain --tag tesseract .

   • To build with a specific release version of Tesseract:

     docker build --progress=plain --tag tesseract --build-arg TESSERACT_VERSION=5.0.0 .

4. Run Tesseract OCR container with test image:

docker run -it --name tesseract -v ${PWD}/testdata:/tmp --rm \
  tesseract tesseract english.png output --oem 1 -l eng

Image conditions ☑️

• Only supported target for this docker image currently is linux/amd64.
• Working directory for ocr images is /tmp inside the container. See example above.
• Directory for trained data is /usr/local/share/tessdata/ inside the container. See example above.
• This image was built without the Tesseract training tools.
• This image currently includes only the following languages:
  • English: tessdata_best > eng.traineddata
  • German: tessdata_best > deu.traineddata
  • If you need other languages, you have to build your own image or mount trained data to the /usr/local/share/tessdata/ directory. See example above.

Tesseract Trained Data for all available languages 🏋️

• Overview of supported languages https://tesseract-ocr.github.io/tessdoc/Data-Files-in-different-versions.html
• Trained models with support for legacy and LSTM OCR engine https://github.com/tesseract-ocr/tessdata
• Fast integer versions of trained LSTM models https://github.com/tesseract-ocr/tessdata_fast
• Best (most accurate) trained LSTM models https://github.com/tesseract-ocr/tessdata_best

Further documentation 🔗

• Docker Hub: https://hub.docker.com/repository/docker/franky1/tesseract
• Original Tesseract Github Repository: https://github.com/tesseract-ocr/tesseract
• Original Tesseract Documentation: https://tesseract-ocr.github.io/
• Original Tesseract Manual: https://tesseract-ocr.github.io/tessdoc/
• More tessdata_best languages: https://github.com/tesseract-ocr/tessdata_best

ToDo ✅

• Update README.md to latest Dockerfile and Usage
• Add dependabot on Github
• Add vulnerability scanning in Github Actions with Snyk
• Use multi-stage build in Dockerfile and clone from git
• Add GitHub Action for check container efficiency with Dive https://github.com/MartinHeinz/dive-action
• Add documentation for GitHub Actions Workflow
• Add more inline comments in GitHub Actions related files
• Build image for more targets
• Building Tesseract with TensorFlow?
• Building Tesseract with Training tools?

Issues 🐛

If you have any bugs or requests regarding this Docker image, please post an issue in this Github Repository.

Project status ✔️

11.09.2025: Docker Image is ready for usage, still some slight improvements possible, sometimes build issues