Workshop

Artificial Intelligence in Machine Vision

Unlock the power of AI and machine vision by mastering Python, OpenCV, and Mediapipe to create dynamic applications and innovative solutions.

About the workshop

The course covers Python basics, including setting up virtual environment using Visual Studio Code,  OpenCV for image processing, video stream handling, and advanced techniques like object tracking and face detection. Additionally, the course introduces Media pipe for hand detection and gesture recognition, culminating in practical projects like creating a Pong game and controlling devices with gestures.

Key points

  • Building Machine Vision applications using Python
  • Designing an interactive game using Machine Vision
  • Creating Machine Vision applications using Arduino
  • Using Google’s MediaPipe framework for your applications

Requirements

  • Must have clear understanding of Python Basics
  • WebCam is necessary to learn the video streaming content
  • Windows 10 with install permission is preferred

Course Module

3 Day Workshop

This course covers an introduction to machine vision, Python, and OpenCV.

Day 1 - Introduction and setting-up

AI and Its Applications:
  • Explore the fundamentals of artificial intelligence, its practical applications, and its influence across various industries.
  • Break down machine learning, deep learning, and computer vision as integral components of AI.
  • Showcase real-world instances where AI technologies are making a significant impact.
Relevance of Python in AI:
  • Cover the essentials of Python programming, including syntax, data types, and control structures.
  • Highlight Python's widespread adoption in the AI and machine learning community.
  • Installing and setting up python.
Using Visual Studio Code as an Integrated Development Environment (IDE):
  • Demonstrate the features and setup of Visual Studio Code, emphasizing its user-friendly interface, integrated terminal, and broad language support.
  • Creating and Utilizing Virtual Environments. Explain the concept of virtual environments for project isolation and organization.
Getting Started with OpenCV and webcam:
  • Introduce OpenCV and elucidate its capabilities in image processing and computer vision.
  • Discuss the pivotal role of OpenCV in diverse applications.
  • Working with Webcams and Video Streams in OpenCV: Guide through the process of accessing and capturing video streams from webcams or video files using OpenCV.
  • Adjusting OpenCV Window Size and Position: Teach techniques for resizing and repositioning OpenCV windows to enhance visualization.

Day 2 - Images and Face Detection

Images and pre-processing:
  • Discuss the representation of images as arrays in OpenCV.
  • Introduce the HSC color space and explain its relevance in image processing.
  • Image manipulation techniques and why they are needed.
  • Functions in OpenCV for adding text, rectangles, and circles to images.
Handling Mouse Clicks, Trackbars, and Events in OpenCV:
  • Explain the concept of regions of interest and demonstrate how to extract specific parts of an image.
  • Teach how to interactively process images using mouse events and trackbars in OpenCV.
Object Tracking
  • Explore methods for tracking and detecting objects based on color in OpenCV.
  • Explain contour detection and its practical applications.
  • Face Detection Using Haar Cascades.
File System
  • Saving Training Data for Machine Learning'
  • Provide an overview of the os.walk function for effective navigation through file systems.
Face Recognition
  • Saving Training Data for Machine Learning'
  • Provide an overview of the os.walk function for effective navigation through file systems.

Day 3 - Advanced Machine Vision

Introduction to Mediapipe
  • Hand Detection and
  • Pose Estimation:
  • Right hand and left-hand detection.
Creating a Pong Game Using Machine Vision:
  • Implement a simple Pong game by integrating machine vision principles.
Gesture Detection:
  • Explore the realm of gesture detection using Medipipe.
Using Gestures to Control External Devices:
  • Implement a practical application where gestures and microcontroller is used to control LEDs.

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