CODEWITHSUNDEEP
pythonpython-2.7opencvraspberry-pi
Th3Gam3rz
Th3Gam3rz

Reputation: 191

Using a Pi Camera Module with OpenCV Python

I currently have some code which captures a still image from the Pi Camera Module and then identifies faces using the haarcascade xml file provided with OpenCV for Python. The code that I am using is the code shown towards the end of this blog post: http://rpihome.blogspot.co.uk/2015/03/face-detection-with-raspberry-pi.html, however it is slightly modified (fully working).

The only problem is that it currently only recognises faces on still images. Is there any way to make it so that I can continuously stream from the Pi Camera directly to OpenCV and then process the faces and display boxes around faces live in a window instead of saving a single frame to a file? I have tried several different tutorials online, but they all seem to not work for me.

Upvotes: 3

Views: 11403

Answers (1)

derricw
derricw

Reputation: 7036

Haven't tried it, but this should work.

from picamera.array import PiRGBArray
from picamera import PiCamera
import cv2
import time

camera = PiCamera()
camera.resolution = (320, 240)
camera.framerate = 30
rawCapture = PiRGBArray(camera, size=(320, 240))

display_window = cv2.namedWindow("Faces")

face_cascade = cv2.CascadeClassifier('path_to_my_face_cascade.xml')

time.sleep(1)

for frame in camera.capture_continuous(rawCapture, format="bgr", use_video_port=True):

    image = frame.array

    #FACE DETECTION STUFF
    gray = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
    faces = face_cascade.detectMultiScale(gray, 1.1, 5)
    for (x,y,w,h) in faces:
        cv2.rectangle(image,(x,y),(x+w,y+h),(255,0,0),2)

    #DISPLAY TO WINDOW
    cv2.imshow("Faces", image)
    key = cv2.waitKey(1)

    rawCapture.truncate(0)

    if key == 27:
        camera.close()
        cv2.destroyAllWindows()
        break

Take a look at the documentation for picamera here.

Upvotes: 3

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