Advantages of Open Source OCR Tools

• Free to use: There are no copyright and licensing restrictions of commercial software, and all functionalities provided by open-source OCR tools can be used for free.

• Open source code: The source code is publicly available, allowing for modifications and customization as needed.

• Flexible and scalable: Different tools can be selected based on actual needs, and these tools have practical applications in various styles and fields, demonstrating universality and scalability.

Eight Common Open Source OCR Tools

Tesseract

Tesseract.js

PaddleOCR

EasyOCR

MMOCR

OCRmyPDF

Umi-OCR

Basic Usage Commands for Eight OCR Open Source Tools

Tesseract

git clone https://github.com/tesseract-ocr/tesseract.git
cd tesseract
./autogen.sh
./configure
make
sudo make install

Tesseract.js

import Tesseract from 'tesseract.js';
Tesseract.recognize('/path/to/image.png')
.then(function(result){
console.log(result.text);
})

PaddleOCR

import paddleocr
# Initialize the recognizer
ocr = paddleocr.OCR()
# Read image file
img_path = '/path/to/image.png'
img = paddleocr.read_image(img_path)
# Perform OCR recognition
result = ocr.ocr(img)
# Output recognition results
for line in result:
print(line)

EasyOCR

import easyocr
# Initialize OCR recognizer
reader = easyocr.Reader(['en', 'ch'])
# Read image file
img_path = '/path/to/image.png'
img = easyocr.imgproc.read(img_path)
# Perform OCR recognition
result = reader.readtext(img)
# Output recognition results
for line in result:print(line)

MMOCR

import mmocr
# Initialize OCR recognizer
pipeline = mmocr.Pipeline(config='configs/textrecog/detector/tp_det_mv3_db.yml')
# Read image file
img_path = '/path/to/image.png'
img = mmcv.imread(img_path)
# Perform OCR recognition
result = pipeline(img)
# Output recognition results
for line in result:
print(line['text'])

simple-ocr-opencv

import cv2
from simple_ocr import OCR
# Initialize OCR recognizer
ocr = OCR()
# Read image file
img_path = '/path/to/image.png'
img = cv2.imread(img_path)
# Perform OCR recognition
result = ocr.ocr(img)
# Output recognition results
print(result)

OCRmyPDF

ocrmypdf /path/to/input.pdf /path/to/output.pdf

Umi-OCR

import umi_ocr
# Initialize recognizer
ocr = umi_ocr.OCR()
# Read image file
img_path = '/path/to/image.png'
img = umi_ocr.read_image(img_path)
# Perform OCR recognition
result = ocr.ocr(img)
# Output recognition results
print(result)

Practical Application Scenarios of OCR

• Tesseract: Widely used in the fields of image recognition and text conversion, such as scanners and digital documents.

• Tesseract.js: Used for web-based OCR recognition, enabling the conversion of text in images into editable text, suitable for online editors, smart forms, online readers, and other application scenarios.

• PaddleOCR: Suitable for OCR recognition in complex text scenarios, such as ID cards, bank cards, license plates, etc.

• EasyOCR: Suitable for OCR application scenarios that require high accuracy in text arrangement and character detection, such as business card recognition, invoice recognition, product label recognition, etc.

• MMOCR: Suitable for OCR recognition in mixed Chinese and English, vertical text, and unstructured scenarios, such as handwritten text, tables, novels, etc.

• simple-ocr-opencv: Suitable for handling common OCR tasks, such as ID cards, business licenses, license plates, etc.

• OCRmyPDF: Converts text in scanned or image files into editable PDF documents, suitable for scenarios that require editing PDF documents.

• Umi-OCR: Helps users quickly generate high-quality OCR models and supports multiple languages and file formats. Suitable for OCR applications that require custom training.

Application Status of OCR Technology in China

• E-commerce: Applications in order processing, invoice management, product recognition, etc., improving efficiency and accuracy.
• Financial services: Recognition in fields such as bank cards, ID cards, and securities accounts can improve customer experience, reduce workload, and error rate.
• Healthcare: Applications in medical record management, drug supervision, and personal privacy protection are also very important.