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https://github.com/maxent-ai/ocrpy

OCR, Archive, Index and Search: Implementation agnostic OCR framework.
https://github.com/maxent-ai/ocrpy

aws azure computer-vision cv deep-learning google-vision-api image-processing information-retrieval nlp ocr ocr-python python semantic-search tesseract-ocr transformers

Last synced: 6 days ago
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OCR, Archive, Index and Search: Implementation agnostic OCR framework.

Host: GitHub
URL: https://github.com/maxent-ai/ocrpy
Owner: maxent-ai
License: mit
Created: 2020-10-18T13:13:36.000Z (about 4 years ago)
Default Branch: main
Last Pushed: 2023-11-03T05:03:49.000Z (about 1 year ago)
Last Synced: 2024-08-02T13:33:55.484Z (3 months ago)
Topics: aws, azure, computer-vision, cv, deep-learning, google-vision-api, image-processing, information-retrieval, nlp, ocr, ocr-python, python, semantic-search, tesseract-ocr, transformers
Language: Jupyter Notebook
Homepage: https://maxentlabs.com/ocrpy
Size: 32.4 MB
Stars: 221
Watchers: 4
Forks: 11
Open Issues: 3
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.rst
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Authors: AUTHORS.rst

Awesome Lists containing this project

README

        # ocrpy

[![Downloads](https://static.pepy.tech/personalized-badge/ocrpy?period=total&units=abbreviation&left_color=black&right_color=blue&left_text=Downloads)](https://pepy.tech/project/ocrpy)

![contributors](https://img.shields.io/github/contributors/maxent-ai/ocrpy?color=blue)

![PyPi](https://img.shields.io/pypi/v/ocrpy?color=blue)

![tag](https://img.shields.io/github/v/tag/maxent-ai/ocrpy)

![mit-license](https://img.shields.io/github/license/maxent-ai/ocrpy?color=blue)

__Unified interface to google vision, aws textract, azure, tesseract and other OCR tools__

The core objective of `ocrpy` is to let users perform OCR, archive, index and search any document with ease, providing an intuitive interface and a powerful Pipeline API to solve common OCR-based tasks.

`ocrpy` achieves this by wrapping around the most popular OCR engines like [Tesseract OCR](https://tesseract-ocr.github.io/), [Aws Textract](https://aws.amazon.com/textract/), [Google Cloud Vision](https://cloud.google.com/vision/docs/ocr) and [Azure Computer Vision](https://azure.microsoft.com/en-in/services/cognitive-services/computer-vision/#features). It unifies the multitude of interfaces provided by a wide range of cloud tools & other open-source libraries under a common and easy-to-use interface for the user.

![](docs/_static/ocrpy-workflow.png)

## Getting Started

`ocrpy` is a Python-only package hosted on [PyPI](https://pypi.org/project/ocrpy/).

The recommended installation method is [pip](https://pip.pypa.io/en/stable/)

```bash

pip install ocrpy

```

## Day-to-Day Usage

`ocrpy` provides various levels of abstraction for the user to perform OCR on different types of documents. The recommended and the best way to use `ocrpy` is through it's `pipeline` API as shown below.

The Pipeline API can be invoked in two ways. The first method is to define the config for running the pipeline as a yaml file and and then run the pipeline by loading it as follows: 

```python

   from ocrpy import TextOcrPipeline

   ocr_pipeline = TextOcrPipeline.from_config("ocrpy_config.yaml")

   ocr_pipeline.process()

```

Alternatively you can run a pipeline by directly instantiating the pipeline class as follows:

```python

   from ocrpy import TextOcrPipeline

   pipeline = TextOcrPipeline(source_dir='s3://document_bucket/', 

                              destination_dir="gs://processed_document_bucket/outputs/", 

                              parser_backend='aws-textract', 

                              credentials_config={"AWS": "path/to/aws-credentials.env/file", 

                                           "GCP": "path/to/gcp-credentials.json/file"})

   pipeline.process()

```

> :memo: For a more detailed set of examples and tutorials on how you could use ocrpy for your use case can be found at [ocrpy documentation](https://maxentlabs.com/ocrpy/).

## Support and Documentation

* For an in-depth reference of the `ocrpy` API refer to our [API docs](https://maxentlabs.com/ocrpy/api-reference.html).

* For inspiration on how to use ocrpy for your usecase, check out our [tutorials](https://maxentlabs.com/ocrpy/tutorials.html) or our [examples](https://maxentlabs.com/ocrpy/examples.html).

* If you're interested in understanding how ocrpy works, check out our [Ocrpy Overview](https://maxentlabs.com/ocrpy/overview.html).

## Feedback and Contributions

* If you have any questions, Feedback or notice something wrong, please open an issue on [GitHub Issues](https://github.com/maxent-ai/ocrpy/issues/).

* If you are interested in contributing to the project, please open a PR on [GitHub Pull Requests](https://github.com/maxent-ai/ocrpy/pulls).

* Or if you just want to say hi, feel free to [contact us]([email protected]).

## Citation

If you wish to cite this project, feel free to use this [BibTeX](http://www.bibtex.org/) reference:

```bibtex

@misc{ocrpy,

    title={Ocrpy: OCR, Archive, Index and Search any documents with ease},

    author={maxentlabs},

    year={2022},

    publisher = {GitHub},

    howpublished = {\url{https://github.com/maxent-ai/ocrpy}}

}

```

## License and Credits

* `ocrpy` is licensed under the [MIT](https://choosealicense.com/licenses/mit/) license.

The full license text can be also found in the [source code repository](https://github.com/maxent-ai/ocrpy/blob/main/LICENSE).

* `ocrpy` is written and maintained by [Bharath G.S](https://github.com/bharathgs) and [Rita Anjana](https://github.com/AnjanaRita).

* A full list of contributors can be found in [GitHub's overview](https://github.com/maxent-ai/ocrpy/graphs/contributors).