Course Outline

Introduction

  • Setting up OpenCV
  • API concepts

Main Modules

  • The Core Functionality(Core Module)
  • Image Processing(Imgproc Module)
  • High Level GUI and Media (highgui module)
  • Image Input and Output (imgcodecs module)
  • Video Input and Output (videoio module)
  • Camera calibration and 3D reconstruction (calib3d module)
  • 2D Features framework (feature2d module)
  • Video analysis (video module)
  • Object Detection (objdetect module)
  • Machine Learning (ml module)
  • Computational photography (photo module)
  • OpenCV Viz

Bonus topics

  • GPU-Accelerated Computer Vision (cuda module)
  • OpenCV iOS

Bonus topics are not available as a part of a remote course. They can be delivered during classroom-based courses, but only by prior agreement, and only if both the trainer and all participants have laptops with supported NVIDIA GPUs (for the CUDA module) or MacBooks, Apple developer accounts and iOS-based mobile devices (for the iOS topic). NobleProg cannot guarantee the availability of trainers with the required hardware.

Requirements

One of the following:

  • C++
  • Java
  • Python
  • MATLAB
  • CUDA
  • OpenCL

And basic knowledge of machine learning. Knowledge of linear algebra, statistics, probability are helpful.

  28 Hours
 

Testimonials

Related Courses

Deep Learning for Vision with Caffe

  21 hours

Computer Vision with Python

  14 hours

Computer Vision with SimpleCV

  14 hours

Real-Time Object Detection with YOLO

  7 hours

YOLOv7: Real-time Object Detection with Computer Vision

  21 hours

Marvin Framework for Image and Video Processing

  14 hours

Python and Deep Learning with OpenCV 4

  14 hours

Pattern Matching

  14 hours

Raspberry Pi + OpenCV for Facial Recognition

  21 hours

Deep Learning for Self Driving Cars

  21 hours

Hardware-Accelerated Video Analytics

  14 hours