Tesseract Container

This repository contains a FastAPI application that uses Tesseract OCR to extract text from images and PDFs. The application exposes several endpoints to upload files, retrieve analysis results, generate searchable PDFs, and check the health of the service.

✨ Features

✅ OCR on Images and PDFs
✅ REST Endpoints
✅ Sync / Async Support
✅ Create searchable PDFs
✅ Add more languages with ease

👩‍💻 Getting Started

1. Pull Image

docker pull jannichorst/tesseract-ocr:latest

2. Run Container

docker run -d -p 8000:8000 jannichorst/tesseract-ocr:latest

3. Usage

Access the Swagger documentation under http://localhost:8000/docs.

import requests

url = "http://localhost:8000/ocr/"
file_path = "path_to_your_image_or_pdf.jpg"

with open(file_path, "rb") as file:
    files = {"file": file}
    response = requests.post(url, files=files)

print("OCR Result:", response.json())

Note

Check out more examples in the demo.iypnb notebook

🔗 Endpoints

Perform OCR [SYNC]

URL: /ocr/
Method: POST
Request: Multipart/form-data with a file, language (default: "eng"), DPI (optional), config (optional), and PSM (default: 3)
Response: JSON containing OCR results and job information

Example using curl:

curl -X POST "http://localhost:8000/ocr/" -F "file=@path_to_your_file"

Start OCR Processing [ASYNC]

URL: /start_ocr/
Method: POST
Request: Multipart/form-data with a file, language (default: "eng"), DPI (optional), config (optional), and PSM (default: 3)
Response: JSON containing a task ID

Example using curl:

curl -X POST "http://localhost:8000/start_ocr/" -F "file=@path_to_your_file"

Get OCR Results

URL: /results/{task_id}
Method: GET
Request: Path parameter with the task ID
Response: JSON containing the OCR results or the status of the task

Example using curl:

curl "http://localhost:8000/results/{task_id}"

Create Searchable PDF [SYNC]

URL: /create_searchable/
Method: POST
Request: Multipart/form-data with a file, language (default: "eng"), DPI (optional), PSM (default: 3), and config (optional)
Response: Searchable PDF file

Example using curl:

curl -X POST "http://localhost:8000/create_searchable/" -F "file=@path_to_your_file" --output output_ocr.pdf

Get Jobs

URL: /jobs
Method: GET
Request: Query parameter for status (default: "pending")
Response: JSON containing job information

Example using curl:

curl "http://localhost:8000/jobs?status=all"

Get System Information

URL: /info
Method: GET
Response: JSON containing system information

Example using curl:

curl "http://localhost:8000/info"

Health Check

URL: /health
Method: GET
Response: JSON indicating the health status of the application

Example using curl:

curl "http://localhost:8000/health"

Swagger Documentation

URL: /docs
Method: GET
Response: Autogenerated documentation & testing area

🐳 Build Image Yourself

Note

For the full guide on how to add more languages see: How to add lmore anguages

Clone the repository:

git clone https://github.com/jannichorst/tesseract-container.git
cd tesseract-container

To build and run the Docker container in one step:
```
./scripts/build_and_run.sh
```
Access the Swagger documentation under http://localhost:8000/docs.
Check out the examples in demo.ipynb and install the required packages with:
```
pip install -r requirements.txt
```

About this Repository

The main application code is located in src/app/main.py. The Dockerfile and scripts for building and running the container are located in the root directory and the scripts directory, respectively. Under tests you find a Postman collection that can be run with run-postman-collection.sh (needs Newman CLI).

Directory Structure

tesseract-container
├── Dockerfile
├── README.md
├── requirements.txt
├── examples
│   └── demo.ipynb
├── scripts
│   ├── build.sh
│   ├── run.sh
│   ├── build_and_run.sh
│   └── run-postman-collection.sh
├── src
│   ├── requirements.txt
│   └── app
│       ├── main.py
│       └── ...
└── tests
    ├── postman_collection.json
    ├── test-image.jpg
    └── ...

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