Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.

Advanced real-time screen translator for games, hardcoded subtitles in videos, static text and etc.

📄 Awesome OCR multiple programing languages toolkits based on ONNXRuntime, OpenVINO and PaddlePaddle.

学习python操作selenium的一个🌰 ，也是一种京东全自动退会方案

🔍 Better text detection by combining multiple OCR engines (EasyOCR, Tesseract, and Pororo) with 🧠 LLM.

License Plate Detection using YOLOv8

Proceed with text detection only in the selected area of ​​the image

Automatic number plate recognition using tech: Yolo, OCR, Scene text detection, scene text recognation, flask, torch

Educational application aimed at automating user-defined workflows for the mobile game, "Granblue Fantasy", using a variety of CV technologies in the backend such as OpenCV, PyAutoGUI and EasyOCR and a frontend coded in Typescript.

Anansi is a computer vision (cv2 and FFmpeg) + OCR (EasyOCR and tesseract) python-based crawler for finding and extracting questions and correct answers from video files of popular TV game shows in the Balkan region.

Automatic information extraction from identity card with ocr

This is a project that translates a .pdf file, preserving the original layout of that .pdf file. [UPDATED] We have achieved the Second Prize of the Cinnamon AI Bootcamp 2023.

Perform optical character recognition on receipts

Comparison-of-OCR (KerasOCR, PyTesseract,EasyOCR)

Custom C++ implementation of deep learning based OCR

Source code of ALPR (Automatic License Plate Recognition System) 🔥

MyLittleOCR 是一个统一的 OCR 库包装器，提供一致的 API，便于集成和切换多个 OCR 引擎。 MyLittleOCR is a unified OCR wrapper providing a consistent API for seamless integration and switching between multiple OCR engines.

A minimal Pokémon shiny hunter app built with Python for the GB Operator.

License Plate Detection and Text Extraction with YoloV8 and EasyOCR

This project is used to detect the license plate of the vehicle in real time, trained using Car Detection Licence Plate dataset available on Kaggle. Used yolov4 because it performs much better than traditional cv techniques and then used EasyOCR to extract text from the number plate. Please see readme for details.