Tag Archives: openCV

AI on the Edge LESSON 7: Homework Solution for Dimmable LED

April 18, 2026 admin

In Lesson 6, I gave you a homework challenge: build a dimmable LED using a potentiometer. In today’s Lesson 7, we go through the solution together step-by-step.

This lesson is all about taking analog input from a potentiometer and converting it into smooth PWM output to control the brightness of an LED. It’s a very practical project because it teaches you how to read real-world analog values and turn them into useful control signals — skills we’ll use again and again as we build smarter AI-powered projects.

In the video, I walk you through the complete working code. You’ll see how we read the potentiometer value (0 to 4095), convert that raw number into a proper brightness percentage using a bit of math (with a nice logarithmic curve so the brightness feels natural to the human eye), and then send that value to the LED using PWM. The result is a very smooth, responsive dimmer that feels professional.

Even though this seems like a simple project, it’s actually an important stepping stone. Understanding how to read sensors and smoothly control outputs is fundamental to building real AI on the Edge systems — whether you’re controlling motors, adjusting screen brightness, or varying the speed of a robot based on sensor input.

By the end of this lesson, you should have a solid understanding of how to combine the ADC (Analog to Digital Converter) with PWM output, and more importantly, how to think about mapping real-world inputs to useful outputs.

So if you did the homework, great job! If you got stuck, don’t worry — we go through the full solution together. And as always, I strongly encourage you to take the code and make it your own. Try changing the response curve, add multiple LEDs with different colors, or combine it with things we’ve learned in earlier lessons.

This is the kind of foundational hardware skill that will serve you well as we continue moving deeper into the AI on the Edge class. You’re doing great — keep going!

We are still using the schematic from our earlier project.

Fusion Hat Circuit Diagram — This is the circuit we will use moving forward in the class

In this lesson, this is the code which we came up with:

#!/usr/bin/env python3
from fusion_hat.adc import ADC
from fusion_hat.pwm import PWM
from time import sleep
import math
potPin=0
myPot = ADC(0)
redPin=5
redLED=PWM(redPin)

while True:
    potVal = myPot.read()                     # 0 to 4095
    writeVal=100**(potVal/4095)-.005
    redLED.pulse_width_percent(int(writeVal))
    print(potVal,writeVal)
    sleep(0.1)

#!/usr/bin/env python3

from fusion_hat.adc import ADC

from fusion_hat.pwm import PWM

from time import sleep

import math

potPin=0

myPot = ADC(0)

redPin=5

redLED=PWM(redPin)

while True:

potVal = myPot.read() # 0 to 4095

writeVal=100**(potVal/4095)-.005

redLED.pulse_width_percent(int(writeVal))

print(potVal,writeVal)

sleep(0.1)

OpenCV, Python, Raspberry Pi

Raspberry Pi LESSON 59: Improved Pan/Tilt Tracking Control Algorithm

April 27, 2023 admin

In this Video Lesson we show an improved control algorithm for tracking an Object of Interest in OpenCV. We develop a simple example of Proportional control, where the correction signal is proportional to the error signal. We show this is a much improved algorithm over our earlier one, which simply applied 1 degree corrections independent of the size of the error. The code we develop in this lesson is included below for your convenience.

import cv2
from picamera2 import Picamera2
import time
import numpy as np
from servo import Servo
picam2 = Picamera2()

pan=Servo(pin=13)
tilt=Servo(pin=12)

panAngle=0
tiltAngle=0

pan.set_angle(panAngle)
tilt.set_angle(tiltAngle)

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)
track=0

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)
def onTrack7(val):
    global track
    track=val
    print('Track Value',track)

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',255,255,onTrack4)
cv2.createTrackbar('Val Low','myTracker',100,255,onTrack5)
cv2.createTrackbar('Val High','myTracker',255,255,onTrack6)
cv2.createTrackbar('Train-0 Track-1','myTracker',0,1,onTrack7)


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)
        if track==1:
            error=(x+w/2)-dispW/2
            panAngle=panAngle-error/75
            if panAngle>90:
                panAngle=90
            if panAngle<-90:
                panAngle=-90
            if abs(error)>35:
                pan.set_angle(panAngle)
            tiltError=(y+h/2)-dispH/2
            tiltAngle=tiltAngle+tiltError/75
            if tiltAngle>40:
                tiltAngle=40
            if tiltAngle<-90:
                tiltAngle=-90
            if abs(tiltError)>35:
                tilt.set_angle(tiltAngle)
        
    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()

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import cv2

from picamera2 import Picamera2

import time

import numpy as np

from servo import Servo

picam2 = Picamera2()

pan=Servo(pin=13)

tilt=Servo(pin=12)

panAngle=0

tiltAngle=0

pan.set_angle(panAngle)

tilt.set_angle(tiltAngle)

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)

track=0

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)

def onTrack7(val):

global track

track=val

print('Track Value',track)

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',255,255,onTrack4)

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

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

cv2.createTrackbar('Train-0 Track-1','myTracker',0,1,onTrack7)

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)

if track==1:

error=(x+w/2)-dispW/2

panAngle=panAngle-error/75

if panAngle>90:

panAngle=90

if panAngle<-90:

panAngle=-90

if abs(error)>35:

pan.set_angle(panAngle)

tiltError=(y+h/2)-dispH/2

tiltAngle=tiltAngle+tiltError/75

if tiltAngle>40:

tiltAngle=40

if tiltAngle<-90:

tiltAngle=-90

if abs(tiltError)>35:

tilt.set_angle(tiltAngle)

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

Raspberry Pi LESSON 58: Control System for Pan/Tilt Camera Hat for RPi Camera

April 20, 2023 admin

<span data-mce-type="bookmark" style="display: inline-block; width: 0px; overflow: hidden; line-height: 0;" class="mce_SELRES_start"></span>In this video lesson, we should a simple control algorithm for a pan tilt camera to track an Object of Interest in OpenCV. We train the device to recognize an Object of Interest based on color, and then the camera is adjusted to keep the object in the center of the frame as the device moves. For your convenience, the code developed in the lesson is included belos.

import cv2
from picamera2 import Picamera2
import time
import numpy as np
from servo import Servo
picam2 = Picamera2()

pan=Servo(pin=13)
tilt=Servo(pin=12)

panAngle=0
tiltAngle=0

pan.set_angle(panAngle)
tilt.set_angle(tiltAngle)

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)
track=0

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)
def onTrack7(val):
    global track
    track=val
    print('Track Value',track)

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',255,255,onTrack4)
cv2.createTrackbar('Val Low','myTracker',100,255,onTrack5)
cv2.createTrackbar('Val High','myTracker',255,255,onTrack6)
cv2.createTrackbar('Train-0 Track-1','myTracker',0,1,onTrack7)


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)
        if track==1:
            error=(x+w/2)-dispW/2
            if error>35:
                panAngle=panAngle-1
                if panAngle<-90:
                    panAngle=-90
                pan.set_angle(panAngle)
            if error<-35:
                panAngle=panAngle+1
                if panAngle>90:
                    panAngle=90
                pan.set_angle(panAngle)
            tiltError=(y+h/2)-dispH/2
            if tiltError>35:
                tiltAngle=tiltAngle+1
                if tiltAngle>40:
                    tiltAngle=40
                tilt.set_angle(tiltAngle)
            if tiltError<-35:
                tiltAngle=tiltAngle-1
                if tiltAngle<-90:
                    tiltAngle=-90
                tilt.set_angle(tiltAngle)
        
    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()

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import cv2

from picamera2 import Picamera2

import time

import numpy as np

from servo import Servo

picam2 = Picamera2()

pan=Servo(pin=13)

tilt=Servo(pin=12)

panAngle=0

tiltAngle=0

pan.set_angle(panAngle)

tilt.set_angle(tiltAngle)

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)

track=0

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)

def onTrack7(val):

global track

track=val

print('Track Value',track)

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',255,255,onTrack4)

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

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

cv2.createTrackbar('Train-0 Track-1','myTracker',0,1,onTrack7)

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)

if track==1:

error=(x+w/2)-dispW/2

if error>35:

panAngle=panAngle-1

if panAngle<-90:

panAngle=-90

pan.set_angle(panAngle)

if error<-35:

panAngle=panAngle+1

if panAngle>90:

panAngle=90

pan.set_angle(panAngle)

tiltError=(y+h/2)-dispH/2

if tiltError>35:

tiltAngle=tiltAngle+1

if tiltAngle>40:

tiltAngle=40

tilt.set_angle(tiltAngle)

if tiltError<-35:

tiltAngle=tiltAngle-1

if tiltAngle<-90:

tiltAngle=-90

tilt.set_angle(tiltAngle)

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

Using a Pan/Tilt Camera Servo to Track an Object of Interest in OpenCV

April 13, 2023 admin

In this Video Lesson we show an initial control system that allows us to position a camera on a pan/tilt servo system to keep an object of interest in the center of the frame. The pan/tilt servo hat will continuously adjust so that the object we are tracking remains in the center of the frame. In this example we are only tracking in the ‘pan’ direction. It is left as a homework assignment for the student to extend the software to also track in the tilt direction. This should be a straightforward extension to our pan example.

import cv2
from picamera2 import Picamera2
import time
import numpy as np
from servo import Servo
picam2 = Picamera2()

pan=Servo(pin=13)
tilt=Servo(pin=12)

panAngle=0
tiltAngle=0

pan.set_angle(panAngle)
tilt.set_angle(tiltAngle)

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',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()
    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)
        error=(x+w/2)-dispW/2
        if error>30:
            panAngle=panAngle-1
            if panAngle<-90:
                panAngle=-90
            pan.set_angle(panAngle)
        if error<-30:
            panAngle=panAngle+1
            if panAngle>90:
                panAngle=90
            pan.set_angle(panAngle)
        
    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()

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import cv2

from picamera2 import Picamera2

import time

import numpy as np

from servo import Servo

picam2 = Picamera2()

pan=Servo(pin=13)

tilt=Servo(pin=12)

panAngle=0

tiltAngle=0

pan.set_angle(panAngle)

tilt.set_angle(tiltAngle)

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',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()

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)

error=(x+w/2)-dispW/2

if error>30:

panAngle=panAngle-1

if panAngle<-90:

panAngle=-90

pan.set_angle(panAngle)

if error<-30:

panAngle=panAngle+1

if panAngle>90:

panAngle=90

pan.set_angle(panAngle)

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 in OpenCV using Contours on the Raspberry Pi

March 23, 2023 admin

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()

Technology Tutorials

Tag Archives: openCV

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

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