pororo-ocr inspired by kakaobrain/pororo, rebuilding only the OCR task of the pororo package for lighteweight and fast performance.

• pororo-ocr is based on torch>=1.6(cuda 10.1) and python>=3.6

• You can install a package through the command below:

pip install pororo-ocr

• pororo-ocr can be used as follows:
• First, in order to import pororo-ocr, you must execute the following snippet

>>> import prrocr

• After the import, you can check languages currently supported by the pororo-ocr through the following commands

>>> import prrocr
>>> prrocr.ocr.get_available_langs()
"Available lanugages are ['en', 'ko']"

• To check which models are supported by each task, you can go through the following process

>>> import prrocr
>>> prrocr.ocr.get_available_models()
"Available models are {'en': ['brainocr'], 'ko': ['brainocr']}"

• If you want to perform in specific language, you can put the language name in the lang argument

>>> import prrocr
>>> ocr = prrocr.ocr(lang="en")

• After object construction, it can be used in a way that passes the input value as follows:

>>> ocr("sample.jpg")
['MAKE TODAY', 'TOLERABLE']

• If you want to get position information for each string, you can turn on detail argument as follows:

>>> ocr("sample.jpg", detail=True)
{'description': ['MAKE TODAY', 'TOLERABLE'], 'bounding_poly': [{'description': 'MAKE TODAY', 'vertices': [{'x': 585, 'y': 397}, {'x': 730, 'y': 397}, {'x': 730, 'y': 520}, {'x': 585, 'y': 520}]}, {'description': 'TOLERABLE', 'vertices': [{'x': 588, 'y': 558}, {'x': 884, 'y': 558}, {'x': 884, 'y': 612}, {'x': 588, 'y': 612}]}]}

pororo-ocr project is licensed under the terms of the Apache License 2.0.