Overview
OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. It contains over 2,500 optimized algorithms for real-time computer vision applications, including image processing, object detection, face recognition, and video analysis.
Key Features
- Real-time processing: Optimized algorithms for real-time applications
- Cross-platform: Works on Windows, Linux, macOS, iOS, and Android
- Language support: Python, C++, Java interfaces
- Hardware acceleration: GPU support via CUDA and OpenCL
- Extensive algorithms: Image processing, feature detection, object tracking, machine learning
- Deep learning integration: DNN module for neural network inference
Getting Started
Installation
pip install opencv-python opencv-contrib-python
Basic Setup
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Core Concepts
Image Representation
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Color Spaces
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Coordinate Systems
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Image Processing
Loading and Saving Images
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Image Transformations
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Filtering and Smoothing
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Edge Detection
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Morphological Operations
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Feature Detection
Corner Detection
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SIFT and SURF
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ORB Features
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Feature Matching
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Object Detection
Haar Cascades
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HOG Detector
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Deep Learning Models
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Video Processing
Capturing Video
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Video Writing
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Frame Processing
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Face Detection and Recognition
Face Detection
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Face Recognition
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Facial Landmarks
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Image Segmentation
Thresholding
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Contour Detection
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Watershed Algorithm
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Camera Calibration
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Object Tracking
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Deep Learning Integration
Loading Pre-trained Models
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Object Detection with YOLO
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Image Classification
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Performance Optimization
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Best Practices
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Real-World Applications
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