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Core modules for image/video I/O and processing

Imgproc for advanced filtering and geometric transformations

VideoCapture/VideoWriter for camera and file I/O

DNN module for deep learning model inference

HighGUI for GUI and visualization tasks

Images and videos are represented as matrices

Operations applied sequentially or in pipelines

Filters and transformations modify pixel values

DNN modules perform inference on image data

Real-time processing optimized for low latency

Modular design with core, imgproc, video, dnn modules

Support for CPU and GPU acceleration

Separation of preprocessing, analysis, and visualization

Integration with external ML frameworks

HighGUI module for display and user interaction

Autonomous vehicles: object detection and lane tracking

Robotics: real-time navigation and vision

Security: surveillance and facial recognition

Healthcare: medical image analysis

AR/VR: augmented reality object overlay

Open-source and extensible

Cross-platform support

High performance for real-time processing

Integration with ML/DL frameworks

Consistency between Python and C++ APIs

Use GPU for real-time video processing

Batch process images for large datasets

Parallelize tasks with multiprocessing

Optimize memory usage for high-resolution images

Leverage cloud computing for heavy workloads

Upgrade via pip/conda

Update deprecated API calls

Test scripts after upgrading versions

Verify model compatibility

Adapt pipelines to new APIs