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Computer vision is a field in which computers are taught to understand digital images and video input the way a human would. In this workshop, we'll introduce you to the OpenCV library, and build a motorized slide system that uses a webcam and OpenCV on a Raspberry Pi to sort differently colored cubes into organized stacks by color

Python 100.00%

build-a-motorized-color-sorter-with-computer-vision's Introduction

Build-a-Motorized-Color-Sorter-with-Computer-Vision

Getting Started

Objective of this workshop is to introduce Computer Vision using Raspberry Pi to the community in a fun and interactive way. The colored objects will be processed by the webcam and it will be sorted into their respective stacks based on the color identified by the webcam.

Prerequisites

  • A Laptop
  • Basic Python programing skills

Components Needed

  • Raspberry Pi 3 (1)
  • Webcam (1)
  • Servo Motors (2)
  • LM7805 voltage regulator(1)
  • Male to Male Jumper wires and Male to Female Jumper Wires
  • Breadboard (1)
  • 9v Battery and Power Bank (1 of each)
  • Colored cubes (or objects - Red,Blue,Yellow)

Software/Libraries Needed

  • Python 2.7
  • OpenCV 3.x

Installation

Python 2.7

You can find the instructions for installation from the following link: https://www.python.org/downloads/

OpenCV

Windows:
You can find the instructions for installation from the following link:
https://docs.opencv.org/master/d5/de5/tutorial_py_setup_in_windows.html

MacOS:
You can find the instructions for installation from the following link:
https://www.codingforentrepreneurs.com/blog/install-opencv-3-for-python-on-mac

Ubuntu:
You can find the instructions for installation from the following link:
https://docs.opencv.org/master/d2/de6/tutorial_py_setup_in_ubuntu.html

Running the code

All the examples can be found in the examples folder. It is advised that you clone the entire repository and try out the examples to gain deeper understanding of the working of OpenCV.

To run the code
Type the following in your command line:
python <filename.py>
For example:
python image_test.py

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