A nice package OCR for Amazon Textract and Google Document AI
Project description
ReadyOCR
ReadyOCR is a Python library that allows you to quickly and easily parse data from various OCR API services, including AWS Textract and Google Document AI. The package also comes with nice features for searching and visualizing.
Installation
You can install ReadyOCR using pip. Depending on the OCR API service you want to use, you can install the corresponding version of ReadyOCR:
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For minimal usage, if you only want to create ReadyOCR document object format:
pip install readyocr
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Or you can choose a specific version to support a specific API response:
# support AWS Textract response pip install "readyocr[textract]" # support Google Document AI response pip install "readyocr[documentai]" # support all available pip install "readyocr[all]"
Basic Usage
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ReadyOCR allows you to create a Document object, which represents the OCR results. A Document can contain one or many pages, and each page can have multiple page entity objects, such as line, word, or table.
from readyocr.entities import Document, Page, Block, Paragraph, Line, Word, Table, Cell, Key, Value document = Document(...) page = Page(...) word = Word(...) # linking all object page.children.add(word) document.pages.append(page)
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You can define any document structure you want by using the
.children
property for page entities. For example, a line object can have many word objects as children.page = Page(...) line = Line(...) word1 = Word(...) word2 = Word(...) line.children = [word1, word2] # add line object to page children page.children.add(line) # you can get descendant of a object all_page_entity = page.descendant # you can also filter all object by class, tag or attribute all_word = page.descendant.filter_by_class(Word)
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ReadyOCR allows you to read PDF file with page object Line, Character, Figure, and Image
from readyocr.parsers.pdf_parser import load document = load(args.document)
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You can also use tags attribute to identify some specific attribute:
table = Table(...) cell = Cell(...) cell.tags.add('COLUMN_HEADER') table.children.add(cell) # Get all table cell which is column header table.children.filter_by_tags('COLUMN_HEADER')
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ReadyOCR support export json object and also load from same json object
from readyocr.parsers.readyocr_parser import load ... # python object -> python dict dict_resp = document.export_json() # python dict -> python object same_document = load(dict_resp)
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ReadyOCR support visualize for bounding box and textbox
from readyocr.utils.visualize import draw_bbox, draw_textbox bbox_image = page.image.copy() text_image = page.image.copy() for item in page.descendants.filter_by_class(Line): bbox_image = draw_bbox( image=bbox_image, bbox=item, fill_color=(0, 255, 0), outline_color=(0, 255, 0), opacity=0.2 ) text_image = draw_textbox( image=text_image, textbox=item, padding=1, true_font_path="../fonts/arial.ttf", )
Examples
Please find all the available examples for better understanding ReadyOCR.
License
ReadyOCR is released under the MIT license. See the LICENSE file for more details.
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