Tag Archives: Raspberry Pi

In this video lesson we show how to use Haar Cascades in OpenCV on the Raspberry Pi to find and track faces and eyes. We show the intelligent way to find eyes, such that CPU resources are not wasted. Below we show the code for your convenience.

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)

faceCascade=cv2.CascadeClassifier('./haar/haarcascade_frontalface_default.xml')
eyeCascade=cv2.CascadeClassifier('./haar/haarcascade_eye.xml')


while True:
    tStart=time.time()
    frame= picam2.capture_array()
    frame=cv2.flip(frame,-1)
    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)
        roiGray=frameGray[y:y+h,x:x+w]
        roiColor=frame[y:y+h,x:x+w]
        eyes=eyeCascade.detectMultiScale(roiGray,1.3,5)
        for eye in eyes:
            x,y,w,h=eye
            cv2.rectangle(roiColor,(x,y),(x+w,y+h),(255,0,0),3)
    cv2.putText(frame,str(int(fps))+' FPS',pos,font,height,myColor,weight)
    cv2.imshow("Camera", frame)

    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)

faceCascade=cv2.CascadeClassifier('./haar/haarcascade_frontalface_default.xml')

eyeCascade=cv2.CascadeClassifier('./haar/haarcascade_eye.xml')

while True:

tStart=time.time()

frame= picam2.capture_array()

frame=cv2.flip(frame,-1)

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)

roiGray=frameGray[y:y+h,x:x+w]

roiColor=frame[y:y+h,x:x+w]

eyes=eyeCascade.detectMultiScale(roiGray,1.3,5)

for eye in eyes:

x,y,w,h=eye

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

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

cv2.imshow("Camera", frame)

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()

Python, Raspberry Pi

Library for Reading a 16 Button Keypad on the Raspberry Pi

October 27, 2022 admin

In this lesson we show you how to create a Python Class and Library that allows you to easily get user input on a Raspberry Pi from a 16 button keypad. This will allow very easy interaction with the keypad.

The Library Code which we develop in the video is presented below for your convenience:

class keypad:
    def __init__(self,rows=[11,13,15,29],columns=[31,33,35,37],keyLabels=[['1','2','3','A'],['4','5','6','B'],['7','8','9','C'],['*','0','#','D']],retChar='D'):
        import RPi.GPIO as GPIO
        self.rows=rows
        self.columns=columns
        self.retChar=retChar
        self.keyLabels=keyLabels
        GPIO.setmode(GPIO.BOARD)
        for i in rows:
            GPIO.setup(i,GPIO.OUT)
        for j in columns:
            GPIO.setup(j,GPIO.IN,pull_up_down=GPIO.PUD_DOWN)
    def readKeypad(self):
        from time import sleep
        import RPi.GPIO as GPIO
        keyStrokes=''
        noPress=True
        noPressOld=True
        while True:
            noPress=True
            for myRow in [0,1,2,3]:
                for myColumn in [0,1,2,3]:
                    GPIO.output(self.rows[myRow],GPIO.HIGH)
                    butVal=GPIO.input(self.columns[myColumn])
                    GPIO.output(self.rows[myRow],GPIO.LOW)
                    if butVal==1:
                        myChar=self.keyLabels[myRow][myColumn]
                        if myChar==self.retChar:
                            return keyStrokes
                        noPress=False
                    if butVal==1 and noPressOld==True and noPress==False:
                        keyStrokes=keyStrokes+myChar
            noPressOld=noPress
            sleep(.25)

class keypad:

def __init__(self,rows=[11,13,15,29],columns=[31,33,35,37],keyLabels=[['1','2','3','A'],['4','5','6','B'],['7','8','9','C'],['*','0','#','D']],retChar='D'):

import RPi.GPIO as GPIO

self.rows=rows

self.columns=columns

self.retChar=retChar

self.keyLabels=keyLabels

GPIO.setmode(GPIO.BOARD)

for i in rows:

GPIO.setup(i,GPIO.OUT)

for j in columns:

GPIO.setup(j,GPIO.IN,pull_up_down=GPIO.PUD_DOWN)

def readKeypad(self):

from time import sleep

import RPi.GPIO as GPIO

keyStrokes=''

noPress=True

noPressOld=True

while True:

noPress=True

for myRow in [0,1,2,3]:

for myColumn in [0,1,2,3]:

GPIO.output(self.rows[myRow],GPIO.HIGH)

butVal=GPIO.input(self.columns[myColumn])

GPIO.output(self.rows[myRow],GPIO.LOW)

if butVal==1:

myChar=self.keyLabels[myRow][myColumn]

if myChar==self.retChar:

return keyStrokes

noPress=False

if butVal==1 and noPressOld==True and noPress==False:

keyStrokes=keyStrokes+myChar

noPressOld=noPress

sleep(.25)

To use this code as a library, save it in the same folder as your python programs, and save it as KPLIB.py

import RPi.GPIO as GPIO
from KPLIB import keypad
myPad=keypad(retChar='A')
myString=myPad.readKeypad()
print(myString)
GPIO.cleanup()

import RPi.GPIO as GPIO

from KPLIB import keypad

myPad=keypad(retChar='A')

myString=myPad.readKeypad()

print(myString)

GPIO.cleanup()

This is a simple demo program that calls the library above, to receive input from the keypad.

Python, Raspberry Pi

Using a Photoresistor to Detect Light on the Raspberry Pi

September 29, 2022 admin

In this lesson we show how to detect light levels with a Raspberry Pi and a photoresistor. The photoresistor is connected in a voltage divider to the ADC0834 AD converter, which then connects to the Raspberry Pi. The schematic of the circuit is below:

Technology Tutorials

Tag Archives: Raspberry Pi

Raspberry Pi LESSON 61: Finding and Tracking Faces and Eyes In OpenCV

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

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

Library for Reading a 16 Button Keypad on the Raspberry Pi

Using a Photoresistor to Detect Light on the Raspberry Pi

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