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OCR PDFs

A Docker-powered service for OCRing PDFs

Dependencies and requirements

  • Redis server for managing queues
  • Docker (install)
  • Docker-compose (install)
    • Note: On mac Docker-compose is installed with Docker

Quick Start

Start the service:

./run start

This script will start the service with default configurations. You can override default values with file ./src/config.yml (you may need to create the file) with the following values:

redis_host: localhost
redis_port: 6379
service_host: localhost
service_port: 5050

Development and testing

A virtual env is needed for some of the development tasks

./run install_venv

Start the service for testing (with a redis server included)

./run start:testing

Check service is up and get general info on supported languages and other important information:

curl localhost:5050/info

Test OCR is working (basic sync method)

curl -X POST -F 'file=@./src/test_files/sample-english.pdf' localhost:5051 --output english.pdf

If language is not specified, english will be used by default. In order to specify a language for better OCR results:

curl -X POST -F 'language=fr' -F 'file=@./src/test_files/sample-french.pdf' localhost:5050 --output french.pdf

Remember you can check supported languages on localhost:5050/info

To list all available commands just run ./run, some useful commands:

./run test
./run linter
./run check_format
./run formatter

Contents

Asynchronous OCR

  1. Upload PDF file to the OCR service

    curl -X POST -F 'file=@/PATH/TO/PDF/pdf_name.pdf' localhost:5051/upload/[namespace]

Alt logo

  1. Add OCR task to queue

To add an OCR task to queue, a message should be sent to a ocr_tasks Redis queue. Params should include filename and, optionally, a supported language.

Python code: TODO: check python code!!!

from rsmq import RedisSMQ
queue = RedisSMQ(host=[redis host], port=[redis port], qname='ocr_tasks', quiet=True)
message_json = '{"tenant": "tenant_name", "task": "ocr", "params": {"filename": "pdf_file_name.pdf", "language": 'fr'}}'
queue.sendMessage().message(message_json).execute()
  1. Retrieve OCRed PDF

Upon completion of the OCR process, a message is placed in the ocr_results Redis queue. This response is, for now, using specific Uwazi terminology. To check if the process for a specific file has been completed:

queue = RedisSMQ(host=[redis host], port=[redis port], qname='ocr_results', quiet=True)
results_message = queue.receiveMessage().exceptions(False).execute()

# The message.message contains the following information:
# {
#   "tenant": "namespace",
#   "task": "pdf_name.pdf",
#   "success": true,
#   "error_message": "",
#   "file_url": "http://localhost:5050/processed_pdf/[namespace]/[pdf_name]"
#   }


curl -X GET http://localhost:5050/processed_pdf/[namespace]/[pdf_name]

HTTP server

The container HTTP server is coded using Python 3.9 and uses the FastApi web framework.

If the service is running, the end point definitions can be founded in the following url:

http://localhost:5050/docs

The endpoints code can be found inside the file ./src/app.py.

The errors are logged in file ./data/service.log.

Queue processor

The container Queue processor is coded using Python 3.9, and it is in charge of communications with the Redis queue.

The code can be found in the file ./src/QueueProcessor.py and it uses the library RedisSMQ to interact with the Redis queues.

Troubleshooting

In MacOS, the following config.yml can be used in order to access Redis in the host's localhost:

redis_host: host.docker.internal
redis_port: 6379
service_host: localhost
service_port: 5050

Issue: Error downloading pip wheel

Solution: Change RAM memory available to the docker containers to 3Gb or 4Gb