Python OCR Library: Top Features

OCR library (Optical Character Recognition) is a technology that converts text content from images into editable text. There are some commonly used OCR libraries in Python, which include but are not limited to:

1. Text recognition: identify the text in the image and convert it into editable text.
2. Handwriting recognition: Recognizing handwritten text and converting it into editable text.
3. Table recognition: Recognize tables in images and convert them into editable spreadsheets.
4. Extracting text from an image and converting it into editable text.
5. Image translation: translating the text in the image into another language.
6. Text detection: Identifying and marking the position of text in an image.
7. Text Correction: Correcting the text in the image to improve recognition accuracy.
8. Text segmentation: Segmenting the text in the image into individual characters or words.
9. Post-processing of text recognition results: processing the recognition results such as removing unnecessary characters and merging broken lines.

These features may vary depending on the specific OCR library being used, commonly used Python OCR libraries include Tesseract, OpenCV, Pytesseract, easyocr, etc.