Overview
After completing this course, you will have an array of abilities to secure your dream career. Furthermore, you will gain free access to all of the materials in this course for a whole year and will learn a plethora of highly sought-after abilities to advance your career.
With this complete and thorough course, you’ll have all of your questions addressed and all of the knowledge you need. Aside from preparing you for success, this course provides various benefits to make your learning experience more enjoyable and less tiring. So, add this course to your cart and boost your expertise!
Why Choose Study Booth?
- Learn using compelling voice-over and graphic elements to help you along the way.
- Get a year’s worth of unlimited access to the course.
- Get expert assistance 24 hours a day, seven days a week.
- Take part in quick assessments and receive immediate feedback on your progression.
- You can study on your own time and from the comfort of your own home.
Who Is This Course For?
Those who want to improve their professional skills while preparing for a specific job can take advantage of this opportunity! This course will assist you to stay updated on the newest advancements and will coach you accordingly. So, if you want the best training possible, invest in this course.
Requirements
No formal entry or relevant experience is required for this course!
This training is open to everyone who is willing to learn. All you need is –
- A smart device that has a constant internet connection
- A strong desire to learn the topic
- And being over the age of 16
Career Path
Use this all-inclusive course to gain the knowledge and abilities you’ll need to succeed in the job.
Course Curriculum
| 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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Offer Ends in
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Access01 Year
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LevelLevel 3
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Students3
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Duration2 hours, 31 minutes