Melbourne 385 Bourke Street

Level 39, 385 Bourke Street, , Melbourne, Australia, 3000
385 Bourke Street is located in the bustling Central Business District (CBD) and retail precinct of Melbourne's commercial hu...

Cliftons Perth

Parmelia House, 191 St Georges Terrace, Perth, Australia, 6000
Located within the historic Bishops See precinct, it sits at the western end of Perth’s Commercial Business District

Explore Our Courses

Computer Vision with OpenCV

28 Hours
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
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Python and Deep Learning with OpenCV 4

14 Hours
This instructor-led, live training in Melbourne (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.
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Raspberry Pi + OpenCV for Facial Recognition

21 Hours
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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Testimonials (2)

I genuinely enjoyed the hands-on approach.

Kevin De Cuyper
Course - Computer Vision with OpenCV

Trainer was very knowlegable and very open to feedback on what pace to go through the content and the topics we covered. I gained alot from the training and feel like I now have a good grasp of image manipulation and some techniques for building a good training set for an image classification problem.

Anthea King - WesCEF
Course - Computer Vision with Python

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