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Wed, 22 Jul

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Futurise Center

PYTHON 3: Computer Vision with Pi

This course introduces OpenCV for Python 3 while integrating with Raspberry Pi 4 to come out. It will show how to leverage the image-processing power of OpenCV to identify and recognize features. This course also include machine learning part in doing facial recognition using classifier.

Registration is Closed
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Time & Location

22 Jul 2020, 9:00 am – 5:00 pm

Futurise Center, Persiaran Apec, Cyber 8, 63000 Cyberjaya, Selangor, Malaysia

About the Event

OpenCV is an open source toolkit for Advanced Computer Vision. It is one of the most popular tools for facial recognition, used in a wide variety of security, marketing, and photography applications, and it powers a lot of cutting-edge tech, including augmented reality and robotics. 

This course introduces OpenCV for Python 3 while integrating with Raspberry Pi 4 to come out. It will show how to leverage the image-processing power of OpenCV to identify and recognize features. This course also include machine learning part in doing facial recognition using classifier.

Course Highlights

● Installing and configuring SimpleCV and OpenCV

● Using Pi Camera

● Integrating into Raspberry Pi 4

● Object detection and image processing

● Face and feature detection

● Facial Recognition 

Course Objectives

After successfully completing this course, participants should be able...

1. To understand how to use Opencv for computer vision.

2. To integrate computer vision application into hardware.

3. To create computer vision application using Pi and OpenCV.

4. Differentiate between machine learning library and classifier.

Who this course is for:

1. Students/Lecturers

2. Researchers

3. Engineers

Level: Intermediate

Age Group: 17 and Above

Additional Note: Please bring your own laptop for hands-on training with Linux OS/Windows. 

Tickets

  • Individual Fee*

    After 27th January 2020

    RM 900.00
  • Early Bird Individual*

    Before 27th January 2020

    RM 750.00
  • Group (Min 3pax)

    RM 700.00

Total

RM 0.00

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