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Udemy Computer Vision by using C++ and OpenCV with GPU support

Video Introducing this tutorial


Introduction :
Course Overview

Set up Necesssary Environments :
Driver installation
Cuda toolkit installation
Compile OpenCV from source with CUDA support part-1
Compile OpenCV from source with CUDA support part-2
Python environment for flownet2-pytorch

Introduction with a few basic examples! :
Read camera & files in a folder (C++)
Edge detection (C++)
Color transformations (C++)
Using a trackbar (C++)
Image filtering with CUDA (Introduction to using OpenCV GPU methods on C++)

Background segmentation :
Background segmentation with MOG (C++)
MOG and MOG2 cuda implementation (C++ - cuda)
Special app: Track class
Special app: Track bgseg Foreground objects

Object detection with openCV ML module (C++ CUDA) :
A simple application to prepare dataset for object detection (C++)
Train model with openCV ML module (C++ and CUDA)
Object detection with openCV ML module (C++ CUDA)

Optical Flow :
Optical flow with Farneback (C++)
Optical flow with Farneback (C++ CUDA)
Optical flow with Nvidia optical flow SDK (C++ CUDA)
Optical flow with Nvidia Flownet2 (Python)
Performance Comparison