In this video lesson we show how to track an object of interest based on color in OpenCV. We show how to create masks, contours, and then how to box the contour of the object of interest. We also show a convenient way to train the system for finding the Object of Interest. For your convenience, the code is included below.

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('Val High',valHigh)

cv2.namedWindow('myTracker')

cv2.createTrackbar('Hue Low','myTracker',10,179,onTrack1)
cv2.createTrackbar('Hue High','myTracker',20,179,onTrack2)
cv2.createTrackbar('Sat Low','myTracker',100,255,onTrack3)
cv2.createTrackbar('Sat High','myTracker',2555,255,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()
    frame=cv2.flip(frame,-1)
    frameHSV=cv2.cvtColor(frame,cv2.COLOR_BGR2HSV)
    cv2.putText(frame,str(int(fps))+' FPS',pos,font,height,myColor,weight)
    lowerBound=np.array([hueLow,satLow,valLow])
    upperBound=np.array([hueHigh,satHigh,valHigh])
    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)))
    
    contours,junk=cv2.findContours(myMask,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
    if len(contours)>0:
        contours=sorted(contours,key=lambda x:cv2.contourArea(x),reverse=True)
        #cv2.drawContours(frame,contours,-1,(255,0,0),3)
        contour=contours[0]
        x,y,w,h=cv2.boundingRect(contour)
        cv2.rectangle(frame,(x,y),(x+w,y+h),(0,0,255),3)
    
    cv2.imshow("Camera", frame)
    cv2.imshow('Mask',myMaskSmall)
    cv2.imshow('My Object',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('Val High',valHigh)

cv2.namedWindow('myTracker')

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

cv2.createTrackbar('Hue High','myTracker',20,179,onTrack2)

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

cv2.createTrackbar('Sat High','myTracker',2555,255,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()

frame=cv2.flip(frame,-1)

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

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

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

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

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)))

contours,junk=cv2.findContours(myMask,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)

if len(contours)>0:

contours=sorted(contours,key=lambda x:cv2.contourArea(x),reverse=True)

#cv2.drawContours(frame,contours,-1,(255,0,0),3)

contour=contours[0]

x,y,w,h=cv2.boundingRect(contour)

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

cv2.imshow("Camera", frame)

cv2.imshow('Mask',myMaskSmall)

cv2.imshow('My Object',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

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

March 17, 2023 admin

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()

Uncategorized

Calculating Frames Per Second (FPS) In OpenCV and Overlay on Frame

January 26, 2023 admin

In this lesson we show how to instrument our code to calculate the Frames Per Second (FPS) we are achieving with our camera and OpenCV. We show how to display the FPS as an overlay on our video frame.

import cv2
from picamera2 import Picamera2
import time
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)
while True:
    tStart=time.time()
    im= picam2.capture_array()
    cv2.putText(im,str(int(fps))+' FPS',pos,font,height,myColor,weight)
    cv2.imshow("Camera", im)
    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

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)

while True:

tStart=time.time()

im= picam2.capture_array()

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

cv2.imshow("Camera", im)

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()

Python, Raspberry Pi

Raspberry Pi LESSON 38: Motion Detection Alarm with Multiple Alarms

December 1, 2022 admin

In this video lesson we show how to create an Alarm System based on a Raspberry Pi, with user input from a keypad, and user prompts on an I2C LCD Display. From the earlier lessons in this series, you must install the LCD1602 Library, and you must install the keypad library. We include the code that we develop in this lesson below for your convenience:

import RPi.GPIO as GPIO
GPIO.setmode(GPIO.BOARD)
PIRpin=12
GPIO.setup(PIRpin,GPIO.IN)
import LCD1602
import KPLIB
from time import sleep
import threading
myPad=KPLIB.keypad(retChar='D')
LCD1602.init(0x27,1)
myString=''
pwd='1234'

from pygame import mixer
mixer.init()
mixer.music.load('al1.mp3')

def readKP():
    global myString
    while myString != '*':
        myString=myPad.readKeypad()
        sleep(.5)
readThread=threading.Thread(target=readKP,)
readThread.daemon=True
readThread.start()
while myString != '*':
    CMD=myString
    if CMD=='A'+pwd:
        LCD1602.write(0,0,'Armed          ')
        moveVal=GPIO.input(PIRpin)
        if moveVal==1:
            LCD1602.write(0,1,'Intruder Alert')
            mixer.music.play()
            sleep(10)
        if moveVal==0:
            LCD1602.write(0,1,'All Clear      ')
    if CMD=='B'+pwd:
        LCD1602.write(0,0,'UnArmed        ')
        LCD1602.write(0,1,'               ')
    if CMD=='C'+pwd:
        LCD1602.write(0,0,'Password?      ')
        LCD1602.write(0,1,'               ')
        while myString=='C'+pwd:
            pass
        pwd=myString
        LCD1602.write(0,0,pwd+'         ')
        sleep(2)
        LCD1602.write(0,0,'               ')
        LCD1602.clear()
    if CMD=='CA1'+pwd:
        myString='A'+pwd
        mixer.music.load('al1.mp3')
    if CMD=='CA2'+pwd:
        myString='A'+pwd
        mixer.music.load('al2.mp3')
    if CMD=='CA3'+pwd:
        myString='A'+pwd
        mixer.music.load('al3.wav')
    if CMD=='CA4'+pwd:
        myString='A'+pwd
        mixer.music.load('al4.wav')
    if CMD=='CA5'+pwd:
        myString='A'+pwd
        mixer.music.load('al5.mp3')
sleep(1)
GPIO.cleanup()
LCD1602.clear()
print('GPIO Good to Go')

import RPi.GPIO as GPIO

GPIO.setmode(GPIO.BOARD)

PIRpin=12

GPIO.setup(PIRpin,GPIO.IN)

import LCD1602

import KPLIB

from time import sleep

import threading

myPad=KPLIB.keypad(retChar='D')

LCD1602.init(0x27,1)

myString=''

pwd='1234'

from pygame import mixer

mixer.init()

mixer.music.load('al1.mp3')

def readKP():

global myString

while myString != '*':

myString=myPad.readKeypad()

sleep(.5)

readThread=threading.Thread(target=readKP,)

readThread.daemon=True

readThread.start()

while myString != '*':

CMD=myString

if CMD=='A'+pwd:

LCD1602.write(0,0,'Armed ')

moveVal=GPIO.input(PIRpin)

if moveVal==1:

LCD1602.write(0,1,'Intruder Alert')

mixer.music.play()

sleep(10)

if moveVal==0:

LCD1602.write(0,1,'All Clear ')

if CMD=='B'+pwd:

LCD1602.write(0,0,'UnArmed ')

LCD1602.write(0,1,' ')

if CMD=='C'+pwd:

LCD1602.write(0,0,'Password? ')

LCD1602.write(0,1,' ')

while myString=='C'+pwd:

pass

pwd=myString

LCD1602.write(0,0,pwd+' ')

sleep(2)

LCD1602.write(0,0,' ')

LCD1602.clear()

if CMD=='CA1'+pwd:

myString='A'+pwd

mixer.music.load('al1.mp3')

if CMD=='CA2'+pwd:

myString='A'+pwd

mixer.music.load('al2.mp3')

if CMD=='CA3'+pwd:

myString='A'+pwd

mixer.music.load('al3.wav')

if CMD=='CA4'+pwd:

myString='A'+pwd

mixer.music.load('al4.wav')

if CMD=='CA5'+pwd:

myString='A'+pwd

mixer.music.load('al5.mp3')

sleep(1)

GPIO.cleanup()

LCD1602.clear()

print('GPIO Good to Go')

Technology Tutorials

Tracking an Object of Interest in OpenCV using Contours on the Raspberry Pi

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

Calculating Frames Per Second (FPS) In OpenCV and Overlay on Frame

Using the Raspberry Pi Camera on Bullseye OS and OpenCV

Raspberry Pi LESSON 38: Motion Detection Alarm with Multiple Alarms

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