Local, instructorled live OpenCV (Open Source Computer Vision Library) training courses demonstrate through interactive discussion and handson practice how to utilize OpenCV for computer vision projects
OpenCV training is available as "onsite live training" or "remote live training" Onsite live training can be carried out locally on customer premises in Norge or in NobleProg corporate training centers in Norge Remote live training is carried out by way of an interactive, remote desktop
NobleProg Your Local Training Provider.
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Testimonials
Den praktiske tilnærmingen
Kevin De Cuyper
Kurs: Computer Vision with OpenCV
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Den enkle bruken av VideoCapture-funksjonaliteten til å skaffe videobilder fra bærbar kamera.
HP Printing and Computing Solutions, Sociedad Limitada Unipe
Kurs: Computer Vision with OpenCV
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Jeg likte instruksjonene fra treneren om hvordan jeg bruker verktøyene. Dette er noe som ikke kan hentes fra internett og er veldig nyttige.
HP Printing and Computing Solutions, Sociedad Limitada Unipe
Kurs: Computer Vision with OpenCV
Machine Translated
Jeg likte instruksjonene fra treneren om hvordan jeg bruker verktøyene. Dette er noe som ikke kan hentes fra internett og er veldig nyttige.
HP Printing and Computing Solutions, Sociedad Limitada Unipe
Kurs: Computer Vision with OpenCV
Machine Translated
Det var lett å følge.
HP Printing and Computing Solutions, Sociedad Limitada Unipe
Kurs: Computer Vision with OpenCV
Machine Translated
OpenCV Kursplaner
Publikum
Dette kurset er rettet mot ingeniører og arkitekter som søker å benytte seg av OpenCV til prosjekter med datasyn
This instructor-led, live training (onsite or remote) is aimed at software engineers who wish to program in Python with OpenCV 4 for deep learning.
By the end of this training, participants will be able to:
- View, load, and classify images and videos using OpenCV 4.
- Implement deep learning in OpenCV 4 with TensorFlow and Keras.
- Run deep learning models and generate impactful reports from images and videos.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
The hardware used in this lab includes Rasberry Pi, a camera module, servos (optional), etc. Participants are responsible for purchasing these components themselves. The software used includes OpenCV, Linux, Python, etc.
By the end of this training, participants will be able to:
- Install Linux, OpenCV and other software utilities and libraries on a Rasberry Pi.
- Configure OpenCV to capture and detect facial images.
- Understand the various options for packaging a Rasberry Pi system for use in real-world environments.
- Adapt the system for a variety of use cases, including surveillance, identity verification, etc.
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
Note
- Other hardware and software options include: Arduino, OpenFace, Windows, etc. If you wish to use any of these, please contact us to arrange.
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