SunFounder picar-x - Page 73

SunFounder picar-x
After the code is run, the face will be checked out in the screen.
Code
import cv2
from picamera.array import PiRGBArray
from picamera import PiCamera
import time
def human_face_detect(img):
resize_img = cv2.resize(img, (320,240), interpolation=cv2.INTER_LINEAR) #
˓→In order to reduce the amount of calculation, resize the image to 320 x 240 size
gray = cv2.cvtColor(resize_img, cv2.COLOR_BGR2GRAY) # Convert to grayscale
faces = face_cascade.detectMultiScale(gray, 1.3, 2) # Detect faces on
˓→grayscale images
face_num = len(faces) # Number of detected faces
if face_num > 0:
for (x,y,w,h) in faces:
x = x
*
2 # Because the image is reduced to one-half of the original size,
˓→ the x, y, w, and h must be multiplied by 2.
y = y
*
2
w = w
*
2
h = h
*
2
cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2) # Draw a rectangle on the
˓→face
return img
with PiCamera() as camera:
print("start human face detect")
camera.resolution = (640,480)
camera.framerate = 24
rawCapture = PiRGBArray(camera, size=camera.resolution)
time.sleep(2)
for frame in camera.capture_continuous(rawCapture, format="bgr",use_video_
˓→port=True): # use_video_port=True
img = frame.array
img = human_face_detect(img)
cv2.imshow("video", img) #OpenCV image show
rawCapture.truncate(0) # Release cache
k = cv2.waitKey(1) & 0xFF
# 27 is the ESC key, which means that if you press the ESC key to exit
if k == 27:
break
print('quit ...')
cv2.destroyAllWindows()
camera.close()
How it works?
In the same path as this project (picar-x/example/) , put a file haarcascade_frontalhuman
face_default.xml. This file is a face detection model file trained in OpenCV.
This file is called by Cascade Classifier of OpenCV.
4.9. Face Detection 69