Tag Archives: openCV

In this video lesson we show how you can track an object of interest in OpenCV on the Raspberry Pi. We do this by tracking color in the HSV color space. We dial in our object of interest using trackbars. For your convenience, the code below is what we developed in our video.

import cv2
from picamera2 import Picamera2
import time
import numpy as np
picam2 = Picamera2()
dispW=1280
dispH=720
picam2.preview_configuration.main.size = (dispW,dispH)
picam2.preview_configuration.main.format = "RGB888"
picam2.preview_configuration.controls.FrameRate=30
picam2.preview_configuration.align()
picam2.configure("preview")
picam2.start()
fps=0
pos=(30,60)
font=cv2.FONT_HERSHEY_SIMPLEX
height=1.5
weight=3
myColor=(0,0,255)

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


cv2.namedWindow('myTracker')

cv2.createTrackbar('Hue Low','myTracker',10,179,onTrack1)
cv2.createTrackbar('Hue High','myTracker',30,179,onTrack2)
cv2.createTrackbar('Sat Low','myTracker',100,255,onTrack3)
cv2.createTrackbar('Sat High','myTracker',255,255,onTrack4)
cv2.createTrackbar('Val Low','myTracker',100,255,onTrack5)
cv2.createTrackbar('Val High','myTracker',255,255,onTrack6)

while True:
    tStart=time.time()
    frame= picam2.capture_array()
    cv2.putText(frame,str(int(fps))+' FPS',pos,font,height,myColor,weight)
    lowerBound=np.array([hueLow,satLow,valLow])
    upperBound=np.array([hueHigh,satHigh,valHigh])
    frameHSV=cv2.cvtColor(frame,cv2.COLOR_BGR2HSV)
    myMask=cv2.inRange(frameHSV,lowerBound,upperBound)
    myMaskSmall=cv2.resize(myMask,(int(dispW/2),int(dispH/2)))
    myObject=cv2.bitwise_and(frame, frame, mask=myMask)
    myObjectSmall=cv2.resize(myObject,(int(dispW/2),int(dispH/2)))
    cv2.imshow("Camera", frame)
    cv2.imshow('my Mask',myMaskSmall)
    cv2.imshow('My Objest',myObjectSmall)
    if cv2.waitKey(1)==ord('q'):
        break
    tEnd=time.time()
    loopTime=tEnd-tStart
    fps=.9*fps + .1*(1/loopTime)
cv2.destroyAllWindows()

import cv2

from picamera2 import Picamera2

import time

import numpy as np

picam2 = Picamera2()

dispW=1280

dispH=720

picam2.preview_configuration.main.size = (dispW,dispH)

picam2.preview_configuration.main.format = "RGB888"

picam2.preview_configuration.controls.FrameRate=30

picam2.preview_configuration.align()

picam2.configure("preview")

picam2.start()

fps=0

pos=(30,60)

font=cv2.FONT_HERSHEY_SIMPLEX

height=1.5

weight=3

myColor=(0,0,255)

def onTrack1(val):

global hueLow

hueLow=val

print('Hue Low',hueLow)

def onTrack2(val):

global hueHigh

hueHigh=val

print('Hue High',hueHigh)

def onTrack3(val):

global satLow

satLow=val

print('Sat Low',satLow)

def onTrack4(val):

global satHigh

satHigh=val

print('Sat High',satHigh)

def onTrack5(val):

global valLow

valLow=val

print('Val Low',valLow)

def onTrack6(val):

global valHigh

valHigh=val

print('Hue Low',valHigh)

cv2.namedWindow('myTracker')

cv2.createTrackbar('Hue Low','myTracker',10,179,onTrack1)

cv2.createTrackbar('Hue High','myTracker',30,179,onTrack2)

cv2.createTrackbar('Sat Low','myTracker',100,255,onTrack3)

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

cv2.createTrackbar('Val Low','myTracker',100,255,onTrack5)

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

while True:

tStart=time.time()

frame= picam2.capture_array()

cv2.putText(frame,str(int(fps))+' FPS',pos,font,height,myColor,weight)

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

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

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

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

myMaskSmall=cv2.resize(myMask,(int(dispW/2),int(dispH/2)))

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

myObjectSmall=cv2.resize(myObject,(int(dispW/2),int(dispH/2)))

cv2.imshow("Camera", frame)

cv2.imshow('my Mask',myMaskSmall)

cv2.imshow('My Objest',myObjectSmall)

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

break

tEnd=time.time()

loopTime=tEnd-tStart

fps=.9*fps + .1*(1/loopTime)

cv2.destroyAllWindows()

OpenCV, Raspberry Pi

Using the Raspberry Pi Camera on Bullseye OS and OpenCV

January 12, 2023 admin

pip install opencv-python==4.6.0.66

1	pip install opencv-python==4.6.0.66

Then the following code will allow you to grab a frame and show a frame in a window. Looking this sequence creates a live video preview on your Raspberry Pi Screen.

import cv2
from picamera2 import Picamera2
picam2 = Picamera2()
picam2.preview_configuration.main.size = (1280,720)
picam2.preview_configuration.main.format = "RGB888"
picam2.preview_configuration.align()
picam2.configure("preview")
picam2.start()
while True:
    im= picam2.capture_array()
    cv2.imshow("Camera", im)
    if cv2.waitKey(1)==ord('q'):
        break
cv2.destroyAllWindows()

import cv2

from picamera2 import Picamera2

picam2 = Picamera2()

picam2.preview_configuration.main.size = (1280,720)

picam2.preview_configuration.main.format = "RGB888"

picam2.preview_configuration.align()

picam2.configure("preview")

picam2.start()

while True:

im= picam2.capture_array()

cv2.imshow("Camera", im)

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

break

cv2.destroyAllWindows()

Artificial Intelligence, OpenCV

AI for Everyone LESSON 29: Control of Real World Objects with Gesture Recognition in Mediapipe

February 24, 2022 admin

In this video lesson we show you how you can control objects in the real world using OpenCV, Python, Mediapipa and our old friend, the Arduino. On the Python side, we recognize hand gestures, and then we pass the recognized gesture to Arduino and Arduino lights LED in response to what hand signal is seen. This is a simple example, but a very powerful method. Instead of LED, you could operate servos, stepper motors or relays to control any manner of different devices. For your convenience, this is the code we used on the Arduino side:

String cmd;
int LED1=9;
int LED2=6;
int LED3=5;
int LED4=3;
int LED5=10;
void setup() {
  pinMode(LED1,OUTPUT);
  pinMode(LED2,OUTPUT);
  pinMode(LED3,OUTPUT);
   pinMode(LED4,OUTPUT);
   pinMode(LED5,OUTPUT);
 Serial.begin(115200);

}
void loop() {
 while (Serial.available()==0){
 
 }
 cmd = Serial.readStringUntil('\r');
if (cmd=="One"){
  digitalWrite(LED1,HIGH);
  digitalWrite(LED2,LOW);
  digitalWrite(LED3,LOW);
  digitalWrite(LED4,LOW);
  digitalWrite(LED5,LOW);
}
if (cmd=="Two"){
  digitalWrite(LED1,HIGH);
  digitalWrite(LED2,HIGH);
  digitalWrite(LED3,LOW);
  digitalWrite(LED4,LOW);
  digitalWrite(LED5,LOW);
}
 if (cmd=="Three"){
  digitalWrite(LED1,HIGH);
  digitalWrite(LED2,HIGH);
  digitalWrite(LED3,HIGH);
  digitalWrite(LED4,LOW);
  digitalWrite(LED5,LOW);
 }
 if (cmd=="Four"){
  digitalWrite(LED1,HIGH);
  digitalWrite(LED2,HIGH);
  digitalWrite(LED3,HIGH);
  digitalWrite(LED4,HIGH);
  digitalWrite(LED5,LOW);
 }
 if (cmd=="Five"){
  digitalWrite(LED1,HIGH);
  digitalWrite(LED2,HIGH);
  digitalWrite(LED3,HIGH);
  digitalWrite(LED4,HIGH);
  digitalWrite(LED5,HIGH);

 }

 if (cmd=="Pinky"){
  digitalWrite(LED1,LOW);
  digitalWrite(LED2,LOW);
  digitalWrite(LED3,LOW);
  digitalWrite(LED4,HIGH);
  digitalWrite(LED5,LOW);

 }
  if (cmd=="Thumb"){
  digitalWrite(LED1,LOW);
  digitalWrite(LED2,LOW);
  digitalWrite(LED3,LOW);
  digitalWrite(LED4,LOW);
  digitalWrite(LED5,HIGH);

 }
  if (cmd=="Inside"){
  digitalWrite(LED1,LOW);
  digitalWrite(LED2,HIGH);
  digitalWrite(LED3,HIGH);
  digitalWrite(LED4,LOW);
  digitalWrite(LED5,LOW);

 }
   if (cmd=="Outside"){
  digitalWrite(LED1,HIGH);
  digitalWrite(LED2,LOW);
  digitalWrite(LED3,LOW);
  digitalWrite(LED4,HIGH);
  digitalWrite(LED5,LOW);

 }
    if (cmd=="Unknown"){
  digitalWrite(LED1,LOW);
  digitalWrite(LED2,LOW);
  digitalWrite(LED3,LOW);
  digitalWrite(LED4,LOW);
  digitalWrite(LED5,LOW);

 }
}

String cmd;

int LED1=9;

int LED2=6;

int LED3=5;

int LED4=3;

int LED5=10;

void setup() {

pinMode(LED1,OUTPUT);

pinMode(LED2,OUTPUT);

pinMode(LED3,OUTPUT);

pinMode(LED4,OUTPUT);

pinMode(LED5,OUTPUT);

Serial.begin(115200);

}

void loop() {

while (Serial.available()==0){

}

cmd = Serial.readStringUntil('\r');

if (cmd=="One"){

digitalWrite(LED1,HIGH);

digitalWrite(LED2,LOW);

digitalWrite(LED3,LOW);

digitalWrite(LED4,LOW);

digitalWrite(LED5,LOW);

}

if (cmd=="Two"){

digitalWrite(LED1,HIGH);

digitalWrite(LED2,HIGH);

digitalWrite(LED3,LOW);

digitalWrite(LED4,LOW);

digitalWrite(LED5,LOW);

}

if (cmd=="Three"){

digitalWrite(LED1,HIGH);

digitalWrite(LED2,HIGH);

digitalWrite(LED3,HIGH);

digitalWrite(LED4,LOW);

digitalWrite(LED5,LOW);

}

if (cmd=="Four"){

digitalWrite(LED1,HIGH);

digitalWrite(LED2,HIGH);

digitalWrite(LED3,HIGH);

digitalWrite(LED4,HIGH);

digitalWrite(LED5,LOW);

}

if (cmd=="Five"){

digitalWrite(LED1,HIGH);

digitalWrite(LED2,HIGH);

digitalWrite(LED3,HIGH);

digitalWrite(LED4,HIGH);

digitalWrite(LED5,HIGH);

}

if (cmd=="Pinky"){

digitalWrite(LED1,LOW);

digitalWrite(LED2,LOW);

digitalWrite(LED3,LOW);

digitalWrite(LED4,HIGH);

digitalWrite(LED5,LOW);

}

if (cmd=="Thumb"){

digitalWrite(LED1,LOW);

digitalWrite(LED2,LOW);

digitalWrite(LED3,LOW);

digitalWrite(LED4,LOW);

digitalWrite(LED5,HIGH);

}

if (cmd=="Inside"){

digitalWrite(LED1,LOW);

digitalWrite(LED2,HIGH);

digitalWrite(LED3,HIGH);

digitalWrite(LED4,LOW);

digitalWrite(LED5,LOW);

}

if (cmd=="Outside"){

digitalWrite(LED1,HIGH);

digitalWrite(LED2,LOW);

digitalWrite(LED3,LOW);

digitalWrite(LED4,HIGH);

digitalWrite(LED5,LOW);

}

if (cmd=="Unknown"){

digitalWrite(LED1,LOW);

digitalWrite(LED2,LOW);

digitalWrite(LED3,LOW);

digitalWrite(LED4,LOW);

digitalWrite(LED5,LOW);

}

And on the python side, we used the following code.

import time
import cv2
print(cv2.__version__)
import numpy as np
import pickle
import serial

arduinoData = serial.Serial('COM3',115200)

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
def findDistances(handData):
    distMatrix=np.zeros([len(handData),len(handData)],dtype='float')
    palmSize=((handData[0][0]-handData[9][0])**2+(handData[0][1]-handData[9][1])**2)**(1./2.)
    for row in range(0,len(handData)):
        for column in range(0,len(handData)):
            distMatrix[row][column]=(((handData[row][0]-handData[column][0])**2+(handData[row][1]-handData[column][1])**2)**(1./2.))/palmSize
    return distMatrix

def findError(gestureMatrix,unknownMatrix,keyPoints):
    error=0
    for row in keyPoints:
        for column in keyPoints:
            error=error+abs(gestureMatrix[row][column]-unknownMatrix[row][column])
    print(error)
    return error
def findGesture(unknownGesture,knownGestures,keyPoints,gestNames,tol):
    errorArray=[]
    for i in range(0,len(gestNames),1):
        error=findError(knownGestures[i],unknownGesture,keyPoints)
        errorArray.append(error)
    errorMin=errorArray[0]
    minIndex=0
    for i in range(0,len(errorArray),1):
        if errorArray[i]<errorMin:
            errorMin=errorArray[i]
            minIndex=i
    if errorMin<tol:
        gesture=gestNames[minIndex]
    if errorMin>=tol:
        gesture='Unknown'
    return gesture

width=1280
height=720
cam=cv2.VideoCapture(3,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(1)
time.sleep(5)
keyPoints=[0,4,5,9,13,17,8,12,16,20]

train=int(input('Enter 1 to Train, Enter 0 to Recognize '))
if train==1:
    trainCnt=0
    knownGestures=[]
    numGest=int(input('How Many Gestures Do You Want? '))
    gestNames=[]
    for i in range(0,numGest,1):
        prompt='Name of Gesture #'+str(i+1)+' '
        name=input(prompt)
        gestNames.append(name)
    print(gestNames)
    trainName=input('Filename for training data? (Press Enter for Default) ')
    if trainName=='':
        trainName='default'
    trainName=trainName+'.pkl'
if train==0:
    trainName=input('What Training Data Do You Want to Use? (Press Enter for Default) ')
    if trainName=='':
        trainName='default'
    trainName=trainName+'.pkl'
    with open(trainName,'rb') as f:
        gestNames=pickle.load(f)
        knownGestures=pickle.load(f)

tol=10

while True:
    ignore,  frame = cam.read()
    frame=cv2.resize(frame,(width,height))
    handData=findHands.Marks(frame)
    if train==1:
        if handData!=[]:
            print('Please Show Gesture ',gestNames[trainCnt],': Press t when Ready')
            if cv2.waitKey(1) & 0xff==ord('t'):
                knownGesture=findDistances(handData[0])
                knownGestures.append(knownGesture)
                trainCnt=trainCnt+1
                if trainCnt==numGest:
                    train=0
                    with open(trainName,'wb') as f:
                        pickle.dump(gestNames,f)
                        pickle.dump(knownGestures,f)
    if train == 0:
        if handData!=[]:
            unknownGesture=findDistances(handData[0])
            myGesture=findGesture(unknownGesture,knownGestures,keyPoints,gestNames,tol)
            #error=findError(knownGesture,unknownGesture,keyPoints)
            cv2.putText(frame,myGesture,(100,175),cv2.FONT_HERSHEY_SIMPLEX,3,(255,0,0),8)
            myGesture=myGesture+'\r'
            arduinoData.write(myGesture.encode())
    for hand in handData:
        for ind in keyPoints:
            cv2.circle(frame,hand[ind],25,(255,0,255),3)
    cv2.imshow('my WEBcam', frame)
    cv2.moveWindow('my WEBcam',0,0)
    if cv2.waitKey(1) & 0xff ==ord('q'):
        break
cam.release()

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import time

import cv2

print(cv2.__version__)

import numpy as np

import pickle

import serial

arduinoData = serial.Serial('COM3',115200)

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

def findDistances(handData):

distMatrix=np.zeros([len(handData),len(handData)],dtype='float')

palmSize=((handData[0][0]-handData[9][0])**2+(handData[0][1]-handData[9][1])**2)**(1./2.)

for row in range(0,len(handData)):

for column in range(0,len(handData)):

distMatrix[row][column]=(((handData[row][0]-handData[column][0])**2+(handData[row][1]-handData[column][1])**2)**(1./2.))/palmSize

return distMatrix

def findError(gestureMatrix,unknownMatrix,keyPoints):

error=0

for row in keyPoints:

for column in keyPoints:

error=error+abs(gestureMatrix[row][column]-unknownMatrix[row][column])

print(error)

return error

def findGesture(unknownGesture,knownGestures,keyPoints,gestNames,tol):

errorArray=[]

for i in range(0,len(gestNames),1):

error=findError(knownGestures[i],unknownGesture,keyPoints)

errorArray.append(error)

errorMin=errorArray[0]

minIndex=0

for i in range(0,len(errorArray),1):

if errorArray[i]<errorMin:

errorMin=errorArray[i]

minIndex=i

if errorMin<tol:

gesture=gestNames[minIndex]

if errorMin>=tol:

gesture='Unknown'

return gesture

width=1280

height=720

cam=cv2.VideoCapture(3,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(1)

time.sleep(5)

keyPoints=[0,4,5,9,13,17,8,12,16,20]

train=int(input('Enter 1 to Train, Enter 0 to Recognize '))

if train==1:

trainCnt=0

knownGestures=[]

numGest=int(input('How Many Gestures Do You Want? '))

gestNames=[]

for i in range(0,numGest,1):

prompt='Name of Gesture #'+str(i+1)+' '

name=input(prompt)

gestNames.append(name)

print(gestNames)

trainName=input('Filename for training data? (Press Enter for Default) ')

if trainName=='':

trainName='default'

trainName=trainName+'.pkl'

if train==0:

trainName=input('What Training Data Do You Want to Use? (Press Enter for Default) ')

if trainName=='':

trainName='default'

trainName=trainName+'.pkl'

with open(trainName,'rb') as f:

gestNames=pickle.load(f)

knownGestures=pickle.load(f)

tol=10

while True:

ignore, frame = cam.read()

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

handData=findHands.Marks(frame)

if train==1:

if handData!=[]:

print('Please Show Gesture ',gestNames[trainCnt],': Press t when Ready')

if cv2.waitKey(1) & 0xff==ord('t'):

knownGesture=findDistances(handData[0])

knownGestures.append(knownGesture)

trainCnt=trainCnt+1

if trainCnt==numGest:

train=0

with open(trainName,'wb') as f:

pickle.dump(gestNames,f)

pickle.dump(knownGestures,f)

if train == 0:

if handData!=[]:

unknownGesture=findDistances(handData[0])

myGesture=findGesture(unknownGesture,knownGestures,keyPoints,gestNames,tol)

#error=findError(knownGesture,unknownGesture,keyPoints)

cv2.putText(frame,myGesture,(100,175),cv2.FONT_HERSHEY_SIMPLEX,3,(255,0,0),8)

myGesture=myGesture+'\r'

arduinoData.write(myGesture.encode())

for hand in handData:

for ind in keyPoints:

cv2.circle(frame,hand[ind],25,(255,0,255),3)

cv2.imshow('my WEBcam', frame)

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

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

break

cam.release()

Artificial Intelligence, OpenCV, Python

AI For Everyone: Parsing Pose and Hand Data Landmarks from Mediapipe

November 25, 2021 admin

In this video lesson we show you how to create simple Python classes to parse the data from mediapipe hand Landmarks and pose estimation. With these two classes, it is very easy to parse the most important data generated by mediapipe.

import cv2
print(cv2.__version__)

class mpPose:
    import mediapipe as mp
    def __init__(self,still=False,upperBody=False, smoothData=True, tol1=.5, tol2=.5):
        self.myPose=self.mp.solutions.pose.Pose(still,upperBody,smoothData,tol1,tol2)
    def Marks(self,frame):
        frameRGB=cv2.cvtColor(frame,cv2.COLOR_BGR2RGB)
        results=self.myPose.process(frameRGB)
        poseLandmarks=[]
        if results.pose_landmarks:
            for lm in results.pose_landmarks.landmark:            poseLandmarks.append((int(lm.x*width),int(lm.y*height)))
        return poseLandmarks

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)
findPose=mpPose()
while True:
    ignore,  frame = cam.read()
    frame=cv2.resize(frame,(width,height))
    handData=findHands.Marks(frame)
    for hand in handData:
        for ind in [0,5,6,7,8]:
            cv2.circle(frame,hand[ind],25,(255,0,255),3)
    poseData=findPose.Marks(frame)
    if len(poseData)!=0:
        cv2.circle(frame,poseData[0],5,(0,255,0),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__)

class mpPose:

import mediapipe as mp

def __init__(self,still=False,upperBody=False, smoothData=True, tol1=.5, tol2=.5):

self.myPose=self.mp.solutions.pose.Pose(still,upperBody,smoothData,tol1,tol2)

def Marks(self,frame):

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

results=self.myPose.process(frameRGB)

poseLandmarks=[]

if results.pose_landmarks:

for lm in results.pose_landmarks.landmark: poseLandmarks.append((int(lm.x*width),int(lm.y*height)))

return poseLandmarks

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)

findPose=mpPose()

while True:

ignore, frame = cam.read()

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

handData=findHands.Marks(frame)

for hand in handData:

for ind in [0,5,6,7,8]:

cv2.circle(frame,hand[ind],25,(255,0,255),3)

poseData=findPose.Marks(frame)

if len(poseData)!=0:

cv2.circle(frame,poseData[0],5,(0,255,0),3)

cv2.imshow('my WEBcam', frame)

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

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

break

cam.release()

Artificial Intelligence, OpenCV, Python

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

November 11, 2021 admin

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()

Technology Tutorials

Tag Archives: openCV

Tracking an Object of Interest Based on Color in OpenCV on Raspberry Pi

Using the Raspberry Pi Camera on Bullseye OS and OpenCV

AI for Everyone LESSON 29: Control of Real World Objects with Gesture Recognition in Mediapipe

AI For Everyone: Parsing Pose and Hand Data Landmarks from Mediapipe

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

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