OpenCV (Open Source Computer Vision Library) is a popular open-source toolkit for computer vision, image processing, and machine learning. It allows you to analyze visual input and automate tasks that involve interpreting images or videos.

Key capabilities of OpenCV:

• Image loading and transformation.
• Face detection and recognition.
• Object tracking and contour detection.
• Feature extraction and matching.
• Integration with deep learning frameworks like TensorFlow or PyTorch.

Basic example: Load and display image

pythonКопироватьРедактироватьimport cv2

image = cv2.imread('photo.jpg')
cv2.imshow('Photo', image)
cv2.waitKey(0)
cv2.destroyAllWindows()

Common applications:

• Optical Character Recognition (OCR)
• License plate detection
• Gesture recognition
• Autonomous vehicles and robotics
• Security surveillance

Advanced features:

• Real-time video processing via webcam streams.
• Pre-trained classifiers (e.g., Haar cascades for face detection).
• Integration with deep learning models for more accurate classification.

OpenCV supports multiple languages, including Python, C++, and Java. With growing demand for visual intelligence in smart systems, computer vision is a field with enormous career potential.