live.py

import cv2

cap = cv2.VideoCapture("nvcamerasrc ! video/x-raw(memory:NVMM), width=(int)1280, height=(int)720,format=(string)I420, framerate=(fraction)24/1 ! nvvidconv flip-method=2 ! video/x-raw, format=(string)BGRx ! videoconvert ! video/x-raw, format=(string)BGR ! appsink")

# Create the haar cascade
faceCascade = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")
cv2.namedWindow('demo', cv2.WINDOW_AUTOSIZE)


while(True):
        # Capture frame-by-frame
        ret, frame = cap.read()

        # Our operations on the frame come here
        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
#        gray = cv2.resize(gray, (640, 360))

        # Detect faces in the image
        faces = faceCascade.detectMultiScale(
                gray,scaleFactor=1.1, minNeighbors=5, minSize = (30,30)
        )

        print("Found {0} faces!".format(len(faces)))

        # Draw a rectangle around the faces
        for (x, y, w, h) in faces:
                cv2.rectangle(gray, (x, y), (x+w, y+h), (255, 0, 0), 2)


        # Display the resulting frame
        cv2.imshow('demo', gray)
        if cv2.waitKey(1) & 0xFF == ord('q'):
                break

# When everything done, release the capture
cap.release()
cv2.destroyAllWindows()
~