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2 hours 31 minutes
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Overview
By enroling in Computer Vision By Using C++ and OpenCV with GPU support, you can kickstart your vibrant career and strengthen your profound knowledge. You can learn everything you need to know about the topic.
The Computer Vision By Using C++ and OpenCV with GPU support course includes all of the most recent information to keep you abreast of the employment market and prepare you for your future. The curriculum for this excellent Computer Vision By Using C++ and OpenCV with GPU support course includes modules at all skill levels, from beginner to expert. You will have the productivity necessary to succeed in your organisation once you have completed our Computer Vision By Using C++ and OpenCV with GPU support Program.
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Description
Enroling in this Computer Vision By Using C++ and OpenCV with GPU support course can improve your Computer Vision By Using C++ and OpenCV with GPU support perspective, regardless of your skill levels in the Computer Vision By Using C++ and OpenCV with GPU support topics you want to master. If you're already a Computer Vision By Using C++ and OpenCV with GPU support expert, this peek under the hood will provide you with suggestions for accelerating your learning, including advanced Computer Vision By Using C++ and OpenCV with GPU support insights that will help you make the most of your time. This Computer Vision By Using C++ and OpenCV with GPU support course will act as a guide for you if you've ever wished to excel at Computer Vision By Using C++ and OpenCV with GPU support.
Why Choose Us?
This course is accredited by the CPD Quality Standards.
Lifetime access to the whole collection of the learning materials.
Online test with immediate results.
Enroling in the course has no additional cost.
You can study and complete the course at your own pace.
Study for the course using any internet-connected device, such as a computer, tablet, or mobile device.
Will I Receive A Certificate Of Completion?
Upon successful completion, you will qualify for the UK and internationally-recognised CPD certificate and you can choose to make your achievement formal by obtaining your PDF Certificate at a cost of £4.99 and Hardcopy Certificate for £9.99.
Who Is This Course For?
This Computer Vision By Using C++ and OpenCV with GPU support course is a great place to start if you're looking to start a new career in Computer Vision By Using C++ and OpenCV with GPU support field. This training is for anyone interested in gaining in-demand Computer Vision By Using C++ and OpenCV with GPU support proficiency to help launch a career or their business aptitude.
Requirements
The Computer Vision By Using C++ and OpenCV with GPU support course requires no prior degree or experience. All you require is English proficiency, numeracy literacy and a gadget with stable internet connection. Learn and train for a prosperous career in the thriving and fast-growing industry of Computer Vision By Using C++ and OpenCV with GPU support, without any fuss.
Career Path
This Computer Vision By Using C++ and OpenCV with GPU support training will assist you develop your Computer Vision By Using C++ and OpenCV with GPU support ability, establish a personal brand, and present a portfolio of relevant talents. It will help you articulate a Computer Vision By Using C++ and OpenCV with GPU support professional story and personalise your path to a new career. Furthermore, developing this Computer Vision By Using C++ and OpenCV with GPU support skillset can lead to numerous opportunities for high-paying jobs in a variety of fields.
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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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