OpenCV

OpenCV is a powerful open-source computer vision library with rich algorithms for image and video processing, such as edge detection, object recognition, and feature extraction. It's widely used in machine vision, robotics, autonomous driving, and augmented reality. Its Python interface is especially popular for fast prototyping and development.

Official Website Github Website

Resource Introduction

Related Resources

Pillow

Pillow is a modern fork of the Python Imaging Library (PIL), used for basic image manipulation like opening, editing, and saving various formats. It supports tasks such as cropping, resizing, and applying filters, making it an essential tool for image preprocessing.

scikit-image

Scikit-image is a scientific image processing library built on NumPy, focusing on image analysis and algorithm implementation. It offers functions like morphology, thresholding, and filtering, suitable for research in medical imaging, remote sensing, and microscopy.

dlib

Dlib is a general-purpose library that includes machine learning and image processing modules, particularly excelling in face recognition and object detection. It comes with built-in facial landmark detectors and classifiers, ideal for security systems and human-computer interaction.

pytesseract

Tesseract is an open-source OCR engine developed by Google that supports multiple languages and fonts, capable of extracting text from images. Pytesseract provides a Python interface to integrate Tesseract into image processing pipelines. It's widely used in document scanning and information extraction.

EasyOCR

EasyOCR is a deep learning-based OCR library supporting over 80 languages. It excels at recognizing text in unstructured images using CNN and CTC decoding techniques, performing well even with complex backgrounds or skewed text. Ideal for multilingual and industrial inspection applications.

Keras-OCR

Keras-OCR is an end-to-end OCR toolkit based on Keras/TensorFlow, including both text detection and recognition stages. It uses pre-trained models for inference and works well on natural scene images like street signs and product packaging. Suitable for educational and research purposes.