Open Source Python API to Integrate OCR Capabilities
Free Python OCR API for Accurate and Fast Text Recognition from Images & Documents. Read both Natural Scene Text and Dense Text in document.
Optical Character Recognition (OCR) technology has been around for a while, and it's used in various industries to automate data entry and document processing tasks. EasyOCR is an open-source OCR (Optical Character Recognition) engine that is fast, accurate, and easy to use. It provides an easy-to-use interface for developers to integrate OCR into their applications. With the EasyOCR library, Software developers can extract text from images and scanned documents in a matter of seconds, making it an ideal tool for document management, data extraction, and automation.
EasyOCR is written in Python and supported over 80+ languages, making it a powerful tool for businesses operating in multi-lingual environments. There are several important features part of the library such as accurate text extraction, multi-language support, simple integration with existing applications, customizing the OCR engine to meet your specific needs, cost-effective solutions, extracting text from scanned documents, receiving & store the extracted text, and many more. The API is a cloud-based solution that does not require any hardware or software installation, making it a cost-effective solution for businesses of all sizes.
The EasyOCR API uses deep learning algorithms to achieve high accuracy rates and can process large volumes of data quickly. It is a flexible and scalable solution that can be integrated into existing workflows using a simple RESTful API. EasyOCR API is a powerful OCR solution that can help businesses of all sizes automate their data entry processes, improve accuracy, and reduce costs. With support for multiple languages, it's an ideal tool for document management, data extraction, and automation. If you're looking for an OCR engine to integrate into your application, give EasyOCR a try.
Getting Started with EasyOCR
The recommend way to install EasyOCR is using pip. Please use the following command for a smooth installation.
Install EasyOCR via pip
pip install easyocr You can also install it manually; download the latest release files directly from GitHub repository.
Text Reading & Extraction from Image via Python API
The open source EasyOCR API uses deep learning algorithms to load, recognize and extract text from images and PDF files inside Python applications. EasyOCR can read multiple languages at the same time but they have to be compatible with each other. Languages that share most of character (e.g. latin script) with each other are compatible. The API allows reading and extracting text from images, including how to preprocess the images and adjust the OCR engine's parameters to improve accuracy. The following example shows how to read and extract text from images and automate data entry tasks with ease.
Read and Extract Text from Images via Python API
import easyocr
reader = easyocr.Reader(['en']) # Set the language of the OCR engine
# Load the image and preprocess it
from PIL import Image
import cv2
image = Image.open('text_image.png')
image = image.convert('L') # Convert the image to grayscale
image = cv2.imread('text_image.png')
# Use the OCR engine to extract text from the image.
result = reader.readtext(image, detail=0)
Recognizing Characters from Text Boxes via Python API
Recognizing characters from text boxes is a common use case for OCR engines. The open source EasyOCR API provides a powerful and user-friendly solution to this use case. It helps software developers to recognize characters from text boxes with ease and how to preprocess the images and adjust the OCR engine's parameters to improve accuracy. Text boxes can have different shapes, sizes, and orientations, and this can impact the accuracy of the OCR engine. So applying some preprocessing steps can improve the accuracy of the OCR engine, such as Deskew the image, Apply binarization and Apply noise reduction.
How to Recognizing Characters from Text Boxes via Python API?
import easyocr
reader = easyocr.Reader(['en']) # Set the language of the OCR engine
# Load the image and preprocess it
from PIL import Image
import cv2
image = Image.open('text_box.png')
image = image.convert('L') # Convert the image to grayscale
image = cv2.imread('text_box.png')
# OCR engine to recognize the characters in the text box
result = reader.readtext(image, detail=0)
# The result is a list of strings, where each string represents a recognized character in the text box.
