OpenCV Training
Level
IntermediateDuration
16h / 2 daysDate
Individually arrangedPrice
Individually arrangedOpenCV Training
An intensive two-day OpenCV training focused on practical image processing. The course combines theory with extensive workshops, enabling participants to quickly master key techniques of digital image analysis and manipulation. Gain the skills necessary in fields such as computer vision, object recognition, and augmented reality.
What You Will Learn
- Master basic and advanced image processing techniques with OpenCV
- Gain practical skills in object detection, image segmentation, and motion tracking
- Learn to implement real-world projects using computer vision
- Understand best practices and performance optimization methods for working with OpenCV
Requirements
- Basic knowledge of Python programming
- General understanding of linear algebra and statistics
- Ability to work in a programming environment (e.g. PyCharm, Jupyter Notebook)
Who is this training for?
Programmers wanting to expand their skills into image processing-
Engineers working on computer vision projects
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Scientists and researchers analyzing visual data
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Computer science and related students interested in AI and CV
Training Program
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Day 1: Introduction to OpenCV and Image Processing Basics
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Environment Setup
- Installing and configuring the OpenCV environment
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Basic Image Handling
- Loading, displaying, and saving images
- Pixel-level image preview
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Basic Image Operations
- Geometric transformations: scaling, rotation, translation
- Image filtering: blurring, sharpening, edge detection
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Color Processing and Color Spaces
- Conversion between RGB, HSV, and grayscale
- Color-based image segmentation
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Feature Detection and Extraction
- Detecting corners and edges
- Feature descriptors: SIFT, SURF, ORB
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Day 2: Advanced Image Processing Techniques
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Advanced Techniques
- Mathematical morphology: erosion, dilation, opening, closing
- Hough transform for line and circle detection
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Image Segmentation
- Thresholding methods
- Segmentation algorithms: watershed, mean-shift
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Object Detection and Tracking
- Haar cascades for face and object detection
- Object tracking using KCF and CSRT
