Make a Virtual Pen and Eraser Using Python || Virtual Pen and Eraser Using OpenCV || Draw Using a Virtual Pen || Creation Code

 Introduction

The project aims to create a virtual pen and eraser using OpenCV and python. This project is very simple and easy to implement. The code is given in this article which you can easily copy and paste into a file and run it on your machine. In this article, we will be using OpenCV for detection of the mouse movements, PyQt5 for GUI creation, Numpy for storing data as well as NumPy array manipulation functions such as slicing and indexing along with Pandas Dataframes which are very helpful while working with Numpy arrays.

Virtual Pen and Eraser Using OpenCV

In this section, you will learn how to create a virtual pen and eraser by using OpenCV.

The first step is importing the required Python libraries. We need to import the cv2 module from opencv library

import cv2

import numpy as np

This project aims to create a virtual pen and eraser using OpenCV and Python

The project aims to create a virtual pen and eraser using opencv and python. This is a very interesting topic for the students who are learning computer vision in college or school. OpenCV is a library that works on different platforms like Windows, Linux, MacOS and Android; it provides cutting-edge features including face detection, object detection, text detection etc. Python is a high-level programming language used for general productivity purposes such as web development or scripting applications.

This project has been divided into tow parts

• First take the range 
• Image proccessing

Before diving into this project, please make sure that you have installed Python3, OpenCV, and Numpy on your PC.

Before diving into this project, you should make sure that you have installed Python3, OpenCV and Numpy on your PC.

Install Python 3:

To install Python 3 on the the Windows platform, go to python.org/downloads and download the latest version of Python 3 (recommended is 64-bit). A setup wizard will be launched after downloading the file which will guide you through the installation process. You can also check out their official documentation for more information about installation steps at

 https://docs.python.org/3/installation/#installing-on-windows-and-macosx

Install opencv3:

OpenCV library is available both through Conda package manager or pip package manager depending on which way suits you best in installing packages in the python environment

If you want to install them, please follow the below link for step by step installation guide.

• pip install numpy
• pip install opencv-python

Installation of Python3, OpenCV3 and NumPy on Ubuntu 16.04 LTS for Python 3.5 

Step 1: Install python 3.5 on Ubuntu 16.04 LTS

sudo apt-get update

sudo apt-get install python3.5 python3-dev python3-pip python3-numpy libhdf5-dev libjpeg62 libpng-dev libtiff5 libtiffxx0c2 libjasper1v5 jasper2 openjpeg2 tbb# mkdir ~/virtual_keyboard# cd virtual_keyboard

Now let’s begin building your virtual pen and eraser.

First, create a file name penrange.py to take the range

import cv2

import numpy as np

cap=cv2.VideoCapture(0)

def nothing(x):

    pass

#Create trackbar to adjust HSV range

cv2.namedWindow("trackbar")

cv2.createTrackbar("L-H","trackbar",0,179,

nothing)

cv2.createTrackbar("L-S","trackbar",0,255,

nothing)

cv2.createTrackbar("L-V","trackbar",0,255,

nothing)

cv2.createTrackbar("U-H","trackbar",179,179,

nothing)

cv2.createTrackbar("U-S","trackbar",255,255,

nothing)

cv2.createTrackbar("U-V","trackbar",255,255,

nothing)

while True:

    ret,frame =cap.read()

    hsv=cv2.cvtColor(frame,cv2.COLOR_BGR2HSV)    

     

    l_h=cv2.getTrackbarPos("L-H","trackbar")

    l_s=cv2.getTrackbarPos("L-S","trackbar")

    l_v=cv2.getTrackbarPos("L-V","trackbar")

    h_h=cv2.getTrackbarPos("U-H","trackbar")

    h_s=cv2.getTrackbarPos("U-S","trackbar")

    h_v=cv2.getTrackbarPos("U-V","trackbar")

   

    low=np.array([l_h,l_s,l_v])

    high=np.array([h_h,h_s,h_v])

 

    mask=cv2.inRange(hsv,low,high)

    result=cv2.bitwise_and(frame,frame,mask=

mask)    

    cv2.imshow("result",result)# If the user

presses ESC then exit the program

    key = cv2.waitKey(1)

    # If the user presses `s` then print and

save this array.

    if key == ord('s'):

        thearray = [[l_h,l_s,l_v],

[h_h, h_s, h_v]]

        # Save this array as penrange.npy

        np.save('penrange',thearray)

        break

    #if esc pressed exit

    if key == 27:

        break

 

cap.release()

cv2.destroyAllWindows()

Now create a main.py, this is our main code

import cv2

import numpy as np

class drawingCanvas():

    def __init__(self):

      self.penrange = np.load('penrange.npy')

# load HSV range

      self.cap = cv2.VideoCapture(0)        

 #0 means primary camera .

      self.canvas = None                      

#initialize blank canvas

        #initial position on pen

      self.x1,self.y1=0,0

        # val is used to toggle between pen and eraser mode

      self.val=1

      self.draw()                            

#Finally call the draw function

    def draw(self):

        while True:

          _, self.frame = self.cap.read()      

#read new frame

          self.frame = cv2.flip( self.frame, 1 )

#flip horizontally

   

          if self.canvas is None:

            self.canvas = np.zeros_like(self.frame)

#initialize a black canvas

           

          mask=self.CreateMask()            

#createmask

          contours=self.ContourDetect(mask)  

#detect Contours

          self.drawLine(contours)            

#draw lines

          self.display()                    

#display results

          k = cv2.waitKey(1) & 0xFF          

#wait for keyboard input

          self.takeAction(k)                

#take action based on k value

       

          if k == 27:                        

#if esc key is pressed exit

            break      

    def CreateMask(self):

      hsv = cv2.cvtColor(self.frame,

cv2.COLOR_BGR2HSV) #convert from BGR to HSV color range

      lower_range = self.penrange[0]                  

 #load  HSV lower range

      upper_range = self.penrange[1]                  

 #load  HSV upper range

      mask = cv2.inRange(hsv, lower_range,

upper_range)

#Create binary mask

      return mask

    def ContourDetect(self,mask):

        # Find Contours based on the mask created.

      contours, hierarchy = cv2.findContours(mask,

cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

      return contours

    def drawLine(self,contours):

        #if contour area is not none and is greater than 100 draw the line

      if contours and cv2.contourArea(max(contours,

key = cv2.contourArea)) > 100:  #100 is required min contour area              

          c = max(contours, key = cv2.contourArea)    

          x2,y2,w,h = cv2.boundingRect(c)

   

      if self.x1 == 0 and self.y1 == 0:  

 #this will we true only for the first time marker is detected

        self.x1,self.y1= x2,y2

      else:

                # Draw the line on the canvas

          self.canvas = cv2.line(self.canvas,

(self.x1,self.y1),(x2,y2), [255*self.val,0,0], 10)

            #New point becomes the previous point

            self.x1,self.y1= x2,y2

      else:

            # If there were no contours detected then make x1,y1 = 0 (reset)

          self.x1,self.y1 =0,0  

    def display(self):

        # Merge the canvas and the frame.

        self.frame = cv2.add(self.frame,

self.canvas)    

        cv2.imshow('frame',self.frame)

        cv2.imshow('canvas',self.canvas)

    def takeAction(self,k):

        # When c is pressed clear the entire canvas

        if k == ord('c'):

            self.canvas = None

        #press e to change between eraser mode and writing mode

        if k==ord('e'):

            self.val= int(not self.val) # toggle

val value between 0 and 1 to change marker color.

                   

if __name__ == '__main__':

    drawingCanvas()

     

cv2.destroyAllWindows()

You Can Clone This Project From here

Conclusion

I hope you enjoyed this tutorial about creating a virtual pen and eraser using OpenCV and python. If you have any questions, please comment below and I will try to get back to you as soon as possible.