Hi !

In my post series I already wrote about how to detect faces. We can do this with a camera and OpenCV. However, a drone can also be moved on command, so let’s write some lines to detect a face, and calculate the orientation and distance of the detected face from the center camera of the camera.

In order to do this, 1st let’s draw a grid in the camera frame, and once a face is detected, let’s show the distance and orientation from the center.

Let’s start with a Grid. The idea is to create a 3×3 grid in the camera frame, and use the center cell as reference for the detected objects. The code to create a 3×3 grid is this one:

def displayGrid(frame):
    # Add a 3x3 Grid
    cv2.line(frame, (int(camera_Width/2)-centerZone, 0)     , (int(camera_Width/2)-centerZone, camera_Heigth)    , lineColor, lineThickness)
    cv2.line(frame, (int(camera_Width/2)+centerZone, 0)     , (int(camera_Width/2)+centerZone, camera_Heigth)    , lineColor, lineThickness)
    cv2.line(frame, (0, int(camera_Heigth / 2) - centerZone), (camera_Width, int(camera_Heigth / 2) - centerZone), lineColor, lineThickness)
    cv2.line(frame, (0, int(camera_Heigth / 2) + centerZone), (camera_Width, int(camera_Heigth / 2) + centerZone), lineColor, lineThickness)

# Camera Settings
camera_Width  = 1024 # 1280 # 640
camera_Heigth = 780  # 960  # 480
centerZone    = 100

# GridLine color green and thickness
lineColor = (0, 255, 0) 
lineThickness = 2

We use the line() function on OpenCV, and do some calculations to get the starting and endpoint for the 4 lines for the grid: 2 vertical lines and 2 horizontal lines. For this demo, I’ll implement this in my main webcam.

Based on my face detection samples and other samples in GitHub (see references), now I’ll calculate the position of the detected face (with x, y, h, w) from the center of the camera:

def calculatePositionForDetectedFace(frame, x, y, h , w):
    # calculate direction and relative position of the face
    cx = int(x + (w / 2))  # Center X of the Face
    cy = int(y + (h / 2))  # Center Y of the Face

    if (cx <int(camera_Width/2) - centerZone):
        cv2.putText  (frame, " LEFT " , (20, 50), cv2.FONT_HERSHEY_COMPLEX, 1 , colorGreen, 2)
        dir = 1
    elif (cx > int(camera_Width / 2) + centerZone):
        cv2.putText(frame, " RIGHT ", (20, 50), cv2.FONT_HERSHEY_COMPLEX,1,colorGreen, 3)
        dir = 2
    elif (cy < int(camera_Heigth / 2) - centerZone):
        cv2.putText(frame, " UP ", (20, 50), cv2.FONT_HERSHEY_COMPLEX,1,colorGreen, 3)
        dir = 3
    elif (cy > int(camera_Heigth / 2) + centerZone):
        cv2.putText(frame, " DOWN ", (20, 50), cv2.FONT_HERSHEY_COMPLEX, 1,colorGreen, 3)
        dir = 4
    else: dir=0

    # display detected face frame, line from center and direction to go
    cv2.line     (frame, (int(camera_Width/2),int(camera_Heigth/2)), (cx,cy), colorRed, messageThickness)
    cv2.rectangle(frame, (x, y), (x + w, y + h), colorBlue, messageThickness)
    cv2.putText  (frame, str(int(x)) + " " + str(int(y)), (x - 20, y - 45), cv2.FONT_HERSHEY_COMPLEX,0.7, colorRed, messageThickness)

The output is similar to this one

And now with the base code completed, it’s time to add this logic to the drone samples !

Bonus: the complete code.

	# Bruno Capuano 2020
	# display the camera feed using OpenCV
	# display a 3×3 Grid
	# detect faces using openCV and haar cascades
	# calculate the relative position for the face from the center of the camera
	import os
	import time
	import cv2
	def displayGrid(frame):
	# Add a 3×3 Grid
	cv2.line(frame, (int(camera_Width/2)–centerZone, 0) , (int(camera_Width/2)–centerZone, camera_Heigth) , lineColor, lineThickness)
	cv2.line(frame, (int(camera_Width/2)+centerZone, 0) , (int(camera_Width/2)+centerZone, camera_Heigth) , lineColor, lineThickness)
	cv2.line(frame, (0, int(camera_Heigth / 2) – centerZone), (camera_Width, int(camera_Heigth / 2) – centerZone), lineColor, lineThickness)
	cv2.line(frame, (0, int(camera_Heigth / 2) + centerZone), (camera_Width, int(camera_Heigth / 2) + centerZone), lineColor, lineThickness)
	def calculatePositionForDetectedFace(frame, x, y, h , w):
	# calculate direction and relative position of the face
	cx = int(x + (w / 2)) # Center X of the Face
	cy = int(y + (h / 2)) # Center Y of the Face
	if (cx <int(camera_Width/2) – centerZone):
	cv2.putText (frame, " LEFT " , (20, 50), cv2.FONT_HERSHEY_COMPLEX, 1 , colorGreen, 2)
	dir = 1
	elif (cx > int(camera_Width / 2) + centerZone):
	cv2.putText(frame, " RIGHT ", (20, 50), cv2.FONT_HERSHEY_COMPLEX,1,colorGreen, 3)
	dir = 2
	elif (cy < int(camera_Heigth / 2) – centerZone):
	cv2.putText(frame, " UP ", (20, 50), cv2.FONT_HERSHEY_COMPLEX,1,colorGreen, 3)
	dir = 3
	elif (cy > int(camera_Heigth / 2) + centerZone):
	cv2.putText(frame, " DOWN ", (20, 50), cv2.FONT_HERSHEY_COMPLEX, 1,colorGreen, 3)
	dir = 4
	else: dir=0
	# display detected face frame, line from center and direction to go
	cv2.line (frame, (int(camera_Width/2),int(camera_Heigth/2)), (cx,cy), colorRed, messageThickness)
	cv2.rectangle(frame, (x, y), (x + w, y + h), colorBlue, messageThickness)
	cv2.putText (frame, str(int(x)) + " " + str(int(y)), (x – 20, y – 45), cv2.FONT_HERSHEY_COMPLEX,0.7, colorRed, messageThickness)
	# Camera Settings
	camera_Width = 1024 # 1280 # 640
	camera_Heigth = 780 # 960 # 480
	centerZone = 100
	# GridLine color green and thickness
	lineColor = (0, 255, 0)
	lineThickness = 2
	# message color and thickness
	colorBlue = (255, 0, 0)
	colorGreen = (0, 255, 0)
	colorRed = (0, 0, 255) #red
	messageThickness = 2
	dsize = (camera_Width, camera_Heigth)
	video_capture = cv2.VideoCapture(1)
	time.sleep(2.0)
	# enable face and smile detection
	face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
	i = 0
	while True:
	i = i + 1
	ret, frameOrig = video_capture.read()
	frame = cv2.resize(frameOrig, dsize)
	gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
	displayGrid(frame)
	# detect faces
	faces = face_cascade.detectMultiScale(gray, 1.3, 5)
	for (x, y, w, h) in faces:
	# display face in grid
	calculatePositionForDetectedFace(frame, x, y, h , w)
	cv2.imshow('@ElBruno – Follow Faces', frame)
	if cv2.waitKey(1) & 0xFF == ord('q'):
	break
	video_capture.release()
	cv2.destroyAllWindows()

view raw WebCamFaceDetectedAndCenterofCam.py hosted with ❤ by GitHub

References

• How To Install OpenCV Win/Mac [0] | OpenCV Python Tutorials for Beginners 2020 https://www.youtube.com/watch?v=vDOkUHNdmKs