Online or onsite, instructor-led live OpenCV (Open Source Computer Vision Library) training courses demonstrate through interactive discussion and hands-on practice how to utilize OpenCV for computer vision projects.
OpenCV training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live OpenCV training can be carried out locally on customer premises in Guatemala City or in NobleProg corporate training centers in Guatemala City.
NobleProg -- Your Local Training Provider
Guatemala - Europlaza
5a Avenue 5-55 Zone 14, Guatemala City, Guatemala, 1014
The Guatemala Europlaza Center is located on the second floor of one of the four modern 19-story towers that form the Europlaza World Business Center. The Guatemala Europlaza Center is convenient for public transport connections, including the new Transmetro bus system introduced to improve traffic flow, and the city Center is just 10 minutes away.
Guatemala - Citibank Tower
3r avenue 13-78, zone 10 , Guatemala City, Guatemala, 01010
Experience convenient access to Citibank Tower via public transportation or by car, with on-site parking available. Additionally, relish seamless international travel with the airport a mere 15-minute drive from the tower.
OpenCV (Open Source Computer Vision Library: http://opencv.org) is an open-source BSD-licensed library that includes several hundreds of computer vision algorithms.
Audience
This course is directed at engineers and architects seeking to utilize OpenCV for computer vision projects
This instructor-led, live training in Guatemala City (online or onsite) 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.
This instructor-led, live training introduces the software, hardware, and step-by-step process needed to build a facial recognition system from scratch. Facial Recognition is also known as Face Recognition.
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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