Package: readyocr
ReadyOCRReadyOCR 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.InstallationYou can install ReadyOCR using pip. Depending on the OCR API service you want to use, you can install the corresponding version of ReadyOCR:For minimal usage, if you only want to create ReadyOCR document object format:pip install readyocrOr 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 UsageReadyOCR 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.add(word)
document.pages.append(page)You can define any document structure you want by using the.childrenproperty 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.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)ReadyOCR allows you to read PDF file with page object Line, Character, Figure, and Image. You can read from both path and byte streamfrom readyocr.parsers.pdf_parser import load

document = load(pdf_path, load_image=True, remove_text=False)
...
with open(pdf_path, 'rb') as fp:
    byte_obj = fp.read()
    document = load(byte_obj, load_image=True, remove_text=False)You can also use tags attribute to identify some specific attribute:table = Table(...)
cell = Cell(...)
cell.tags.add('COLUMN_HEADER')
table.add(cell)

# Get all table cell which is column header
table.children.filter_by_tags('COLUMN_HEADER')ReadyOCR support export json object and also load from same json objectfrom readyocr.parsers.readyocr_parser import load

...
# python object -> python dict
dict_resp = document.export_json()

# python dict -> python object
same_document = load(dict_resp)ReadyOCR support visualize for bounding box and textboxfrom 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",
    )ExamplesPlease find all the availableexamplesfor better understanding ReadyOCR.LicenseReadyOCR is released under the MIT license. See theLICENSEfile for more details.