Example exercise from our OpenCV course

OpenCV and Deep Learning in Python


35 hours – 5 days.


  • Basic familiarity with Python (Jupyter notebook) is preferred.


Computer vision is increasingly used in industry and research labs across the world. In this course we will provide an introduction to the subject with the open-source library OpenCV.

Course Outline

  • Introduction to OpenCV.
  • GUI Features in OpenCV and Jupyter Notebook.
  • Core operations: resizing, filtering, color conversions.
  • Image processing: histogram equalization, image arithmetics, image pyramids.
  • Feature detection and description: corners, edges, histogram of oriented gradients, SIFT, SURF, ORB and BRIEF algorithms.
  • Video Analysis: optical flow, mean shift and cam shift, Lucas-Kanade algorithm.
  • Camera calibration and 3D reconstruction.
  • Object detection.
  • Machine learning within OpenCV.
  • Using pre-trained deep neural networks in OpenCV.


  • Developers, engineers and computer vision enthusiasts.

Format of the course


750 EUR/person + VAT.

  • Live coding and lecture by the facilitator, exercises (with solutions) for the participants.

Note:  The course is designed to provide a broad overview. However, we can customize the course to cover your specific needs.

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