Tag Archives: openCV

In this video lesson we introduce the concept of using OpenCV and Mediapipe to create gesture based arcade games in Python. In this lesson we suggest creating a gesture based version of the classic Pong arcade game. We show enough to get started, and your homework is to complete the game.

import cv2
print(cv2.__version__)

class mpHands:
    import mediapipe as mp
    def __init__(self,maxHands=2,tol1=.5,tol2=.5):
        self.hands=self.mp.solutions.hands.Hands(False,maxHands,tol1,tol2)
    def Marks(self,frame):
        myHands=[]
        frameRGB=cv2.cvtColor(frame,cv2.COLOR_BGR2RGB)
        results=self.hands.process(frameRGB)
        if results.multi_hand_landmarks != None:
            for handLandMarks in results.multi_hand_landmarks:
                myHand=[]
                for landMark in handLandMarks.landmark:
                    myHand.append((int(landMark.x*width),int(landMark.y*height)))
                myHands.append(myHand)
        return myHands

width=1280
height=720
cam=cv2.VideoCapture(4,cv2.CAP_DSHOW)
cam.set(cv2.CAP_PROP_FRAME_WIDTH, width)
cam.set(cv2.CAP_PROP_FRAME_HEIGHT,height)
cam.set(cv2.CAP_PROP_FPS, 30)
cam.set(cv2.CAP_PROP_FOURCC,cv2.VideoWriter_fourcc(*'MJPG'))
findHands=mpHands(2)
paddleWidth=125
paddleHeight=25
paddleColor=(0,255,0)
while True:
    ignore,  frame = cam.read()
    frame=cv2.resize(frame,(width,height))
    handData=findHands.Marks(frame)
    for hand in handData:
        cv2.rectangle(frame,(int(hand[8][0]-paddleWidth/2),0),(int(hand[8][0]+paddleWidth/2),paddleHeight),paddleColor,-1)
    cv2.imshow('my WEBcam', frame)
    cv2.moveWindow('my WEBcam',0,0)
    if cv2.waitKey(1) & 0xff ==ord('q'):
        break
cam.release()

import cv2

print(cv2.__version__)

class mpHands:

import mediapipe as mp

def __init__(self,maxHands=2,tol1=.5,tol2=.5):

self.hands=self.mp.solutions.hands.Hands(False,maxHands,tol1,tol2)

def Marks(self,frame):

myHands=[]

frameRGB=cv2.cvtColor(frame,cv2.COLOR_BGR2RGB)

results=self.hands.process(frameRGB)

if results.multi_hand_landmarks != None:

for handLandMarks in results.multi_hand_landmarks:

myHand=[]

for landMark in handLandMarks.landmark:

myHand.append((int(landMark.x*width),int(landMark.y*height)))

myHands.append(myHand)

return myHands

width=1280

height=720

cam=cv2.VideoCapture(4,cv2.CAP_DSHOW)

cam.set(cv2.CAP_PROP_FRAME_WIDTH, width)

cam.set(cv2.CAP_PROP_FRAME_HEIGHT,height)

cam.set(cv2.CAP_PROP_FPS, 30)

cam.set(cv2.CAP_PROP_FOURCC,cv2.VideoWriter_fourcc(*'MJPG'))

findHands=mpHands(2)

paddleWidth=125

paddleHeight=25

paddleColor=(0,255,0)

while True:

ignore, frame = cam.read()

frame=cv2.resize(frame,(width,height))

handData=findHands.Marks(frame)

for hand in handData:

cv2.rectangle(frame,(int(hand[8][0]-paddleWidth/2),0),(int(hand[8][0]+paddleWidth/2),paddleHeight),paddleColor,-1)

cv2.imshow('my WEBcam', frame)

cv2.moveWindow('my WEBcam',0,0)

if cv2.waitKey(1) & 0xff ==ord('q'):

break

cam.release()

OpenCV, Python

AI for Everyone LESSON 15: Face Detection using OpenCV

October 12, 2021 admin

In this video lesson we show a simple method to detect faces in a WEB cam frame using openCV and Haar Cascades. We use pretrained models to find, box and track faces in a frame. Enjoy!

import cv2
print(cv2.__version__)
width=640
height=360
cam=cv2.VideoCapture(0,cv2.CAP_DSHOW)
cam.set(cv2.CAP_PROP_FRAME_WIDTH, width)
cam.set(cv2.CAP_PROP_FRAME_HEIGHT,height)
cam.set(cv2.CAP_PROP_FPS, 30)
cam.set(cv2.CAP_PROP_FOURCC,cv2.VideoWriter_fourcc(*'MJPG'))

faceCascade=cv2.CascadeClassifier('C:\Users\Valued Customer\Documents\Python\haar\haarcascade_frontalface_default.xml')

while True:
    ignore,  frame = cam.read()
    frameGray=cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
    faces=faceCascade.detectMultiScale(frameGray,1.3,5)
    for face in faces:
        x,y,w,h=face
        cv2.rectangle(frame,(x,y),(x+w,y+h),(255,0,0),3)
    cv2.imshow('my WEBcam', frame)
    cv2.moveWindow('my WEBcam',0,0)
    if cv2.waitKey(1) & 0xff ==ord('q'):
        break
cam.release()

import cv2

print(cv2.__version__)

width=640

height=360

cam=cv2.VideoCapture(0,cv2.CAP_DSHOW)

cam.set(cv2.CAP_PROP_FRAME_WIDTH, width)

cam.set(cv2.CAP_PROP_FRAME_HEIGHT,height)

cam.set(cv2.CAP_PROP_FPS, 30)

cam.set(cv2.CAP_PROP_FOURCC,cv2.VideoWriter_fourcc(*'MJPG'))

faceCascade=cv2.CascadeClassifier('C:\Users\Valued Customer\Documents\Python\haar\haarcascade_frontalface_default.xml')

while True:

ignore, frame = cam.read()

frameGray=cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)

faces=faceCascade.detectMultiScale(frameGray,1.3,5)

for face in faces:

x,y,w,h=face

cv2.rectangle(frame,(x,y),(x+w,y+h),(255,0,0),3)

cv2.imshow('my WEBcam', frame)

cv2.moveWindow('my WEBcam',0,0)

if cv2.waitKey(1) & 0xff ==ord('q'):

break

cam.release()

OpenCV, Python

Tracking Two Colors in OpenCV

September 30, 2021 admin

In this video lesson we show how you can track two different colored objects at the same time in OpenCV. It is the homework solution to the homework we assigned in the last lesson. It will also serve as the starting code for future lessons

import numpy as np
import cv2
print(cv2.__version__)
hueLow=90
hueHigh=100

hueLow2=90
hueHigh2=100

satLow=20
satHigh=200
valLow=20
valHigh=200
def onTrack1(val):
    global hueLow
    hueLow=val
    print('Low Hue: ',val)
def onTrack2(val):
    global hueHigh
    hueHigh=val
    print('High Hue: ',val)
def onTrack3(val):
    global satLow
    satLow=val
    print('Low Sat: ',val)
def onTrack4(val):
    global satHigh
    satHigh=val
    print('High Sat: ',val)
def onTrack5(val):
    global valLow
    valLow=val
    print('Low Val: ',val)
def onTrack6(val):
    global valHigh
    valHigh=val
    print('High Val: ',val)


def onTrack7(val):
    global hueLow2
    hueLow2=val
    print('Low Hue2: ',val)
def onTrack8(val):
    global hueHigh2
    hueHigh2=val
    print('High Hue2: ',val)


width=960
height=540
cam=cv2.VideoCapture(0)
cam.set(cv2.CAP_PROP_FOURCC, cv2.VideoWriter_fourcc(*'MJPG')) 
cam.set(cv2.CAP_PROP_FRAME_WIDTH, width)
cam.set(cv2.CAP_PROP_FRAME_HEIGHT, height)
cv2.namedWindow('myTracker')
cv2.moveWindow('myTracker',width,0)
cv2.resizeWindow('myTracker',400,500)
cv2.createTrackbar('Hue Low','myTracker',15,180,onTrack1)
cv2.createTrackbar('Hue High','myTracker',30,180,onTrack2)

cv2.createTrackbar('Hue Low2','myTracker',50,180,onTrack7)
cv2.createTrackbar('Hue High2','myTracker',60,180,onTrack8)

cv2.createTrackbar('Sat Low','myTracker',10,255,onTrack3)
cv2.createTrackbar('Sat High','myTracker',255,255,onTrack4)
cv2.createTrackbar('Val Low','myTracker',10,255,onTrack5)
cv2.createTrackbar('Val High','myTracker',255,255,onTrack6)


while True:
    ignore,  frame = cam.read()
    frameHSV=cv2.cvtColor(frame,cv2.COLOR_BGR2HSV)

    lowerBound=np.array([hueLow,satLow,valLow])
    upperBound=np.array([hueHigh,satHigh,valHigh])

    lowerBound2=np.array([hueLow2,satLow,valLow])
    upperBound2=np.array([hueHigh2,satHigh,valHigh])

    myMask=cv2.inRange(frameHSV,lowerBound,upperBound)
    myMask2=cv2.inRange(frameHSV,lowerBound2,upperBound2)

    myMask=myMask | myMask2
    #myMask=cv2.add(myMask,myMask2)
    #myMask=np.logical_or(myMask,myMask2)

    #myMask=cv2.bitwise_not(myMask)
    myMaskSmall=cv2.resize(myMask,(int(width/2),int(height/2)))
    mySelection=cv2.bitwise_and(frame,frame, mask=myMask)
    mySelection=cv2.resize(mySelection,(int(width/2),int(height/2)))
    cv2.imshow('My Selection', mySelection)
    cv2.moveWindow('My Selection',int(width/2),height)

    cv2.imshow('My Mask', myMaskSmall)
    cv2.moveWindow('My Mask',0,height)
    cv2.imshow('my WEBcam',frame)
    cv2.moveWindow('my WEBcam',0,0)
    if cv2.waitKey(1) & 0xff ==ord('q'):
        break
cam.release()

100

101

import numpy as np

import cv2

print(cv2.__version__)

hueLow=90

hueHigh=100

hueLow2=90

hueHigh2=100

satLow=20

satHigh=200

valLow=20

valHigh=200

def onTrack1(val):

global hueLow

hueLow=val

print('Low Hue: ',val)

def onTrack2(val):

global hueHigh

hueHigh=val

print('High Hue: ',val)

def onTrack3(val):

global satLow

satLow=val

print('Low Sat: ',val)

def onTrack4(val):

global satHigh

satHigh=val

print('High Sat: ',val)

def onTrack5(val):

global valLow

valLow=val

print('Low Val: ',val)

def onTrack6(val):

global valHigh

valHigh=val

print('High Val: ',val)

def onTrack7(val):

global hueLow2

hueLow2=val

print('Low Hue2: ',val)

def onTrack8(val):

global hueHigh2

hueHigh2=val

print('High Hue2: ',val)

width=960

height=540

cam=cv2.VideoCapture(0)

cam.set(cv2.CAP_PROP_FOURCC, cv2.VideoWriter_fourcc(*'MJPG'))

cam.set(cv2.CAP_PROP_FRAME_WIDTH, width)

cam.set(cv2.CAP_PROP_FRAME_HEIGHT, height)

cv2.namedWindow('myTracker')

cv2.moveWindow('myTracker',width,0)

cv2.resizeWindow('myTracker',400,500)

cv2.createTrackbar('Hue Low','myTracker',15,180,onTrack1)

cv2.createTrackbar('Hue High','myTracker',30,180,onTrack2)

cv2.createTrackbar('Hue Low2','myTracker',50,180,onTrack7)

cv2.createTrackbar('Hue High2','myTracker',60,180,onTrack8)

cv2.createTrackbar('Sat Low','myTracker',10,255,onTrack3)

cv2.createTrackbar('Sat High','myTracker',255,255,onTrack4)

cv2.createTrackbar('Val Low','myTracker',10,255,onTrack5)

cv2.createTrackbar('Val High','myTracker',255,255,onTrack6)

while True:

ignore, frame = cam.read()

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

lowerBound=np.array([hueLow,satLow,valLow])

upperBound=np.array([hueHigh,satHigh,valHigh])

lowerBound2=np.array([hueLow2,satLow,valLow])

upperBound2=np.array([hueHigh2,satHigh,valHigh])

myMask=cv2.inRange(frameHSV,lowerBound,upperBound)

myMask2=cv2.inRange(frameHSV,lowerBound2,upperBound2)

myMask=myMask | myMask2

#myMask=cv2.add(myMask,myMask2)

#myMask=np.logical_or(myMask,myMask2)

#myMask=cv2.bitwise_not(myMask)

myMaskSmall=cv2.resize(myMask,(int(width/2),int(height/2)))

mySelection=cv2.bitwise_and(frame,frame, mask=myMask)

mySelection=cv2.resize(mySelection,(int(width/2),int(height/2)))

cv2.imshow('My Selection', mySelection)

cv2.moveWindow('My Selection',int(width/2),height)

cv2.imshow('My Mask', myMaskSmall)

cv2.moveWindow('My Mask',0,height)

cv2.imshow('my WEBcam',frame)

cv2.moveWindow('my WEBcam',0,0)

if cv2.waitKey(1) & 0xff ==ord('q'):

break

cam.release()

OpenCV, Python, Tutorial

Putting Text, Rectangles and Circles on Images in OpenCV for Windows

August 24, 2021 admin

In the video lesson above we show how to add text, rectangles and circles to video frames using OpenCV. Below we include the code with we developed in this lesson. Enjoy!

import cv2
print(cv2.__version__)
width=640
height=360
myRadius=30
myColor=(0,0,0)
myThick=2
fontH=2
fontT=2
myText='Paul is Boss'
myFont=cv2.FONT_HERSHEY_DUPLEX
upperLeft=(250,140)
lowerRight=(390,220)
lineW=4
cam=cv2.VideoCapture(1,cv2.CAP_DSHOW)
cam.set(cv2.CAP_PROP_FRAME_WIDTH, width)
cam.set(cv2.CAP_PROP_FRAME_HEIGHT,height)
cam.set(cv2.CAP_PROP_FPS, 30)
cam.set(cv2.CAP_PROP_FOURCC,cv2.VideoWriter_fourcc(*'MJPG'))
while True:
    ignore,  frame = cam.read()
    frame[140:220,250:390]=(255,0,0)
    cv2.rectangle(frame,upperLeft,lowerRight,(0,255,0),lineW)
    cv2.circle(frame,(int(width/2),int(height/2)),myRadius,myColor,myThick)
    cv2.putText(frame,myText,(120,60),myFont,fontH,(0,0,255),fontT)
    cv2.imshow('my WEBcam', frame)
    cv2.moveWindow('my WEBcam',0,0)
    if cv2.waitKey(1) & 0xff ==ord('q'):
        break
cam.release()

import cv2

print(cv2.__version__)

width=640

height=360

myRadius=30

myColor=(0,0,0)

myThick=2

fontH=2

fontT=2

myText='Paul is Boss'

myFont=cv2.FONT_HERSHEY_DUPLEX

upperLeft=(250,140)

lowerRight=(390,220)

lineW=4

cam=cv2.VideoCapture(1,cv2.CAP_DSHOW)

cam.set(cv2.CAP_PROP_FRAME_WIDTH, width)

cam.set(cv2.CAP_PROP_FRAME_HEIGHT,height)

cam.set(cv2.CAP_PROP_FPS, 30)

cam.set(cv2.CAP_PROP_FOURCC,cv2.VideoWriter_fourcc(*'MJPG'))

while True:

ignore, frame = cam.read()

frame[140:220,250:390]=(255,0,0)

cv2.rectangle(frame,upperLeft,lowerRight,(0,255,0),lineW)

cv2.circle(frame,(int(width/2),int(height/2)),myRadius,myColor,myThick)

cv2.putText(frame,myText,(120,60),myFont,fontH,(0,0,255),fontT)

cv2.imshow('my WEBcam', frame)

cv2.moveWindow('my WEBcam',0,0)

if cv2.waitKey(1) & 0xff ==ord('q'):

break

cam.release()

Python

Faster Launch of WEBcam and Smoother Video in OpenCV on Windows

August 12, 2021 admin

This is the code we developed in Video Lesson #6 showing how to launch a webcam quicker and with less delay in OpenCV running on windows. The video above explains the code step by step, but for your convenience, I include the code below.

import cv2
print(cv2.__version__)
width=1280
height=720
cam=cv2.VideoCapture(1,cv2.CAP_DSHOW)
cam.set(cv2.CAP_PROP_FRAME_WIDTH, width)
cam.set(cv2.CAP_PROP_FRAME_HEIGHT,height)
cam.set(cv2.CAP_PROP_FPS, 30)
cam.set(cv2.CAP_PROP_FOURCC,cv2.VideoWriter_fourcc(*'MJPG'))
while True:
    ignore,  frame = cam.read()
    cv2.imshow('my WEBcam', frame)
    cv2.moveWindow('my WEBcam',0,0)
    if cv2.waitKey(1) & 0xff ==ord('q'):
        break
cam.release()

import cv2

print(cv2.__version__)

width=1280

height=720

cam=cv2.VideoCapture(1,cv2.CAP_DSHOW)

cam.set(cv2.CAP_PROP_FRAME_WIDTH, width)

cam.set(cv2.CAP_PROP_FRAME_HEIGHT,height)

cam.set(cv2.CAP_PROP_FPS, 30)

cam.set(cv2.CAP_PROP_FOURCC,cv2.VideoWriter_fourcc(*'MJPG'))

while True:

ignore, frame = cam.read()

cv2.imshow('my WEBcam', frame)

cv2.moveWindow('my WEBcam',0,0)

if cv2.waitKey(1) & 0xff ==ord('q'):

break

cam.release()

Technology Tutorials

Tag Archives: openCV

AI for Everyone: Developing a Gesture Based Arcade Game Based on Mediapipe and Python

AI for Everyone LESSON 15: Face Detection using OpenCV

Tracking Two Colors in OpenCV

Putting Text, Rectangles and Circles on Images in OpenCV for Windows

Faster Launch of WEBcam and Smoother Video in OpenCV on Windows

Making The World a Better Place One High Tech Project at a Time. Enjoy!