Artificial Intelligence, OpenCV, Raspberry Pi

Raspberry Pi LESSON 63: Object Detection on Raspberry Pi Using Tensorflow Lite

May 25, 2023 admin

In this lesson I show you how to do object detection on the Raspberry Pi using Tensorflow Lite. We will write our first program and by the end of the lesson you will have your Pi detecting objects, boxing them and labeling them in OpenCV.

The video demonstrates step-by-step how to install the tensorflow libraries.

For your convenience I have included the code below we develop in this lesson

import cv2
import time
from picamera2 import Picamera2

from tflite_support.task import core
from tflite_support.task import processor
from tflite_support.task import vision
import utils

model='efficientdet_lite0.tflite'
num_threads=4

dispW=1280
dispH=720

picam2=Picamera2()
picam2.preview_configuration.main.size=(dispW,dispH)
picam2.preview_configuration.main.format='RGB888'
picam2.preview_configuration.align()
picam2.configure("preview")
picam2.start()

webCam='/dev/video2'
cam=cv2.VideoCapture(webCam)
cam.set(cv2.CAP_PROP_FRAME_WIDTH, dispW)
cam.set(cv2.CAP_PROP_FRAME_HEIGHT, dispH)
cam.set(cv2.CAP_PROP_FPS, 30)

pos=(20,60)
font=cv2.FONT_HERSHEY_SIMPLEX
height=1.5
weight=3
myColor=(255,0,0)

fps=0

base_options=core.BaseOptions(file_name=model,use_coral=False, num_threads=num_threads)
detection_options=processor.DetectionOptions(max_results=3, score_threshold=.3)
options=vision.ObjectDetectorOptions(base_options=base_options,detection_options=detection_options)
detector=vision.ObjectDetector.create_from_options(options)
tStart=time.time()
while True:
    ret, im = cam.read()
    #im=picam2.capture_array()
    #im=cv2.flip(im,-1)
    imRGB=cv2.cvtColor(im,cv2.COLOR_BGR2RGB)
    imTensor=vision.TensorImage.create_from_array(imRGB)
    detections=detector.detect(imTensor)
    image=utils.visualize(im, detections)
    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
    tStart=time.time()
cv2.destroyAllWindows()

import cv2

import time

from picamera2 import Picamera2

from tflite_support.task import core

from tflite_support.task import processor

from tflite_support.task import vision

import utils

model='efficientdet_lite0.tflite'

num_threads=4

dispW=1280

dispH=720

picam2=Picamera2()

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

picam2.preview_configuration.main.format='RGB888'

picam2.preview_configuration.align()

picam2.configure("preview")

picam2.start()

webCam='/dev/video2'

cam=cv2.VideoCapture(webCam)

cam.set(cv2.CAP_PROP_FRAME_WIDTH, dispW)

cam.set(cv2.CAP_PROP_FRAME_HEIGHT, dispH)

cam.set(cv2.CAP_PROP_FPS, 30)

pos=(20,60)

font=cv2.FONT_HERSHEY_SIMPLEX

height=1.5

weight=3

myColor=(255,0,0)

fps=0

base_options=core.BaseOptions(file_name=model,use_coral=False, num_threads=num_threads)

detection_options=processor.DetectionOptions(max_results=3, score_threshold=.3)

options=vision.ObjectDetectorOptions(base_options=base_options,detection_options=detection_options)

detector=vision.ObjectDetector.create_from_options(options)

tStart=time.time()

while True:

ret, im = cam.read()

#im=picam2.capture_array()

#im=cv2.flip(im,-1)

imRGB=cv2.cvtColor(im,cv2.COLOR_BGR2RGB)

imTensor=vision.TensorImage.create_from_array(imRGB)

detections=detector.detect(imTensor)

image=utils.visualize(im, detections)

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

tStart=time.time()

cv2.destroyAllWindows()

OpenCV, Python, Raspberry Pi

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

May 11, 2023 admin

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, 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

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()

Technology Tutorials

Raspberry Pi LESSON 63: Object Detection on Raspberry Pi Using Tensorflow Lite

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

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

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

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

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