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Python ANPR with OpenCV and EasyOCR - Automatic Number Plate Recognition Tutorial

Nicholas Renotte via YouTube

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Overview

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Learn how to implement Automatic Number Plate Recognition (ANPR) using Python, OpenCV, and EasyOCR in this comprehensive tutorial video. Discover edge detection and filtering techniques combined with deep learning-powered optical character recognition to extract number plate text from images. Master reading and visualizing images with OpenCV, applying color shifts and changes, detecting contours, masking number plates for improved text extraction, and using EasyOCR for optical character recognition. Gain practical skills for computer vision projects, including car park management and vehicle identification. Access the provided code repository and additional resources to enhance your learning experience and apply ANPR techniques to real-world scenarios.

Syllabus

- Start
- Reading and visualising images using OpenCV with Python
- Applying color shifts and changes to images e.g. grayscaling and BGR2RGB
- Detecting contours using OpenCV findCountours
- Masking number plates to improve text extraction for OCR
- Extracting number plate text using EasyOCR

Taught by

Nicholas Renotte

Reviews

4.0 rating, based on 1 Class Central review

Start your review of Python ANPR with OpenCV and EasyOCR - Automatic Number Plate Recognition Tutorial

  • Profile image for Rakesh Kanna
    Rakesh Kanna
    The course was overall informative and well-structured. The concepts were explained clearly, and the content was delivered in a logical sequence that made it easy to understand. The instructor demonstrated good subject knowledge and maintained a positive learning environment throughout the sessions.

    The mix of theoretical explanation and practical examples was helpful in understanding how the concepts apply in real situations. The pace of the course was manageable, and the materials provided—such as notes, slides, and assignments—supported the learning objectives effectively
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