/ocr-tutorial

Primary LanguagePythonMIT LicenseMIT

OCR using Azure Cognitive Services (Computer Vision API)

This implementation is for learning purposes. The class ocr.py could be used to extract text from images (OCR) using the Azure Computer Vision REST API.

Could be used in a lot of scenarios to help extract valuable information from images. Use your creativity to expand the use to have fun to fix a lot of real world problems and feel free to clone this repo and adapt this code for your requirements :)

This tutorial was inspired from Microsoft Oficial Quickstart Tutorial.

Activate environment

Pipenv will install all the libraries required automatically. pipenv shell

Flake8 config

Use the bellow code to adjust the max line length limit flake8 --max-line-length=140

If you use VSCode you can add this config to settings.json adding the code:

"python.linting.flake8Args": [
        "--max-line-length=140",
    ]

Set environment variables

You can find API Key in Quick start section of your API on Azure Portal

export COMPUTER_VISION_SUBSCRIPTION_KEY=<KEY_1>

You can find API endpoint in Quick start section of your API on Azure Portal

export COMPUTER_VISION_ENDPOINT=<COMPUTER_VISION_ENDPOINT>

How to run

Run run.py and change the variables IMAGE_PATH, OUTPUT_JSON_PATH and OUTPUT_IMAGE_PATH.

IMAGE_PATH: is the path of the image that will be used to extract the text from its content

OUTPUT_JSON_PATH : is the path to the json file generated from the OCR process

OUTPUT_IMAGE_PATH: is the path of the image with the boundingBoxes TODO: Need to make more tests (I know that is not working in images with multiple pages)

Clean up resources

To clean up resources you can delete the Resource Group or the API using Azure Portal.