Unit 01: Set up Necesssary Environments | |||
Module 01: Driver installation | 00:06:00 | ||
Module 02: Cuda toolkit installation | 00:01:00 | ||
Module 03: Compile OpenCV from source with CUDA support part-1 | 00:06:00 | ||
Module 04: Compile OpenCV from source with CUDA support part-2 | 00:05:00 | ||
Module 05: Python environment for flownet2-pytorch | 00:09:00 | ||
Unit 02: Introduction with a few basic examples! | |||
Module 01: Read camera & files in a folder (C++) | 00:11:00 | ||
Module 02: Edge detection (C++) | 00:08:00 | ||
Module 03: Color transformations (C++) | 00:07:00 | ||
Module 04: Using a trackbar (C++) | 00:06:00 | ||
Module 05: Image filtering with CUDA (Introduction to using OpenCV GPU methods on C++) | 00:13:00 | ||
Unit 03: Background segmentation | |||
Module 01: Background segmentation with MOG (C++) | 00:04:00 | ||
Module 02: MOG and MOG2 cuda implementation (C++ – CUDA) | 00:03:00 | ||
Module 03: Special app: Track class | 00:06:00 | ||
Module 04: Special app: Track bgseg Foreground objects | 00:08:00 | ||
Unit 04: Object detection with openCV ML module (C++ CUDA) | |||
Module 01: A simple application to prepare dataset for object detection (C++) | 00:08:00 | ||
Module 02: Train model with openCV ML module (C++ and CUDA) | 00:13:00 | ||
Module 03: Object detection with openCV ML module (C++ CUDA) | 00:06:00 | ||
Unit 05: Optical Flow | |||
Module 01: Optical flow with Farneback (C++) | 00:08:00 | ||
Module 02: Optical flow with Farneback (C++ CUDA) | 00:06:00 | ||
Module 03: Optical flow with Nvidia optical flow SDK (C++ CUDA) | 00:05:00 | ||
Module 04: Optical flow with Nvidia Flownet2 (Python) | 00:05:00 | ||
Module 05: Performance Comparison | 00:07:00 | ||
Additional Resource | |||
Resources | 00:00:00 | ||
Assignment | |||
Assignment – Computer Vision by Using C++ and OpenCV | 00:00:00 |
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