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Learn how to make a genuine difference in your life by taking our popular Computer Vision By Using C++ and OpenCV with GPU support Course. Our commitment to online learning and our technical experience has been put to excellent use within the content of these educational modules. By enrolling today, you can take your knowledge of Computer Vision By Using C++ and OpenCV with GPU support to a whole new level and quickly reap the rewards of your study in the field you have chosen.
We are confident that you will find the skills and information that you will need to succeed in this area and excel in the eyes of others. Do not rely on substandard training or half-hearted education. Commit to the best, and we will help you reach your full potential whenever and wherever you need us.
Please note that Computer Vision By Using C++ and OpenCV with GPU support provides valuable and significant theoretical training for all. However, it does not offer official qualifications for professional practice. Always check details with the appropriate authorities or management.
By completing the training in Computer Vision By Using C++ and OpenCV with GPU support, you will be able to significantly demonstrate your acquired abilities and knowledge of Computer Vision By Using C++ and OpenCV with GPU support. This can give you an advantage in career progression, job applications, and personal mastery in this area.
This course is designed to provide an introduction to Computer Vision By Using C++ and OpenCV with GPU support and offers an excellent way to gain the vital skills and confidence to start a successful career. It also provides access to proven educational knowledge about the subject and will support those wanting to attain personal goals in this area. Full-time and part-time learners are equally supported, and the study periods are entirely customisable to your needs.
Once you have completed all the modules in the Computer Vision By Using C++ and OpenCV with GPU support course, you can assess your skills and knowledge with an optional assignment. Our expert trainers will assess your assignment and give you feedback afterwards.
Show off Your New Skills with a Certification of Completion
The learners have to successfully complete the assessment of this Computer Vision By Using C++ and OpenCV with GPU support course to achieve the CPD accredited certificate. Digital certificates can be ordered for only £10. Learners can purchase printed hard copies inside the UK for £29, and international students can purchase printed hard copies for £39.
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 | ||
Order Your Certificate | |||
Order your Certificate. | 00:00:00 |
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