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face tracking opencv

Grid answered on December 17, 2023 Popularity 3/10 Helpfulness 1/10

answer face tracking opencv

face tracking opencv

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#Retrieve the latest image from the webcam
rc,fullSizeBaseImage = capture.read()

#Resize the image to 320x240
baseImage = cv2.resize( fullSizeBaseImage, ( 320, 240))


#Check if a key was pressed and if it was Q, then destroy all
#opencv windows and exit the application
pressedKey = cv2.waitKey(2)
if pressedKey == ord('Q'):
cv2.destroyAllWindows()
exit(0)



#Result image is the image we will show the user, which is a
#combination of the original image from the webcam and the
#overlayed rectangle for the largest face
resultImage = baseImage.copy()


#For the face detection, we need to make use of a gray colored
#image so we will convert the baseImage to a gray-based image
gray = cv2.cvtColor(baseImage, cv2.COLOR_BGR2GRAY)
#Now use the haar cascade detector to find all faces in the
#image
faces = faceCascade.detectMultiScale(gray, 1.3, 5)


#For now, we are only interested in the 'largest' face, and we
#determine this based on the largest area of the found
#rectangle. First initialize the required variables to 0
maxArea = 0
x = 0
y = 0
w = 0
h = 0


#Loop over all faces and check if the area for this face is
#the largest so far
for (_x,_y,_w,_h) in faces:
    if  _w*_h > maxArea:
        x = _x
        y = _y
        w = _w
        h = _h
        maxArea = w*h

    #If one or more faces are found, draw a rectangle around the
    #largest face present in the picture
    if maxArea > 0 :
        cv2.rectangle(resultImage,  (x-10, y-20),
	    		    (x + w+10 , y + h+20),
		    	    rectangleColor,2)



#Since we want to show something larger on the screen than the
#original 320x240, we resize the image again
#
#Note that it would also be possible to keep the large version
#of the baseimage and make the result image a copy of this large
#base image and use the scaling factor to draw the rectangle
#at the right coordinates.
largeResult = cv2.resize(resultImage,
		     (OUTPUT_SIZE_WIDTH,OUTPUT_SIZE_HEIGHT))

#Finally, we want to show the images on the screen
cv2.imshow("base-image", baseImage)
cv2.imshow("result-image", largeResult)

Popularity 3/10 Helpfulness 1/10 Language whatever

Source: www.guidodiepen.nl

Tags: face opencv tracking whatever

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Contributed on Dec 17 2023

Grid

0 Answers Avg Quality 2/10

face tracking opencv

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