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

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()

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