How to run a command once when a face was detected in OpenCV-CodePudding

I am trying to make it so when a face was detected, it would run a python command once instead of spamming it, for example print()

try:
    import cv2

    cap = cv2.VideoCapture(0)
    pTime = 0
    cascPath=os.path.dirname(cv2.__file__) "/data/haarcascade_frontalface_default.xml"
    faceCascade = cv2.CascadeClassifier(cascPath)

    face_detected = True

    while True:
        success, img = cap.read()
        img = cv2.flip(img, 1)
        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
        imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
        cTime = time.time() 
        fps = 1 / (cTime - pTime)
        pTime = cTime
        face_count = 0

        cv2.putText(img, f'FPS:{int(fps)}', (20, 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)

        faces = faceCascade.detectMultiScale(
            gray,
            scaleFactor=1.1,
            minNeighbors=5,
            minSize=(30, 30),
            flags=cv2.CASCADE_SCALE_IMAGE
        )
        for (x, y, w, h) in faces:
            cv2.rectangle(img, (x, y), (x w, y h), (0, 255, 0), 2)
            face_count = face_count 1
                
            cv2.putText(img, 'Face num ' str(face_count), (x-10, y-10),
                        cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
            cv2.putText(img, f'Faces Detected: {face_count}', (20, 70), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)

      
        if face_count > 0: # If one or more faces were detected
            print("a face was detected")
        elif face_count == 0: # If no faces were detected
            print("the face magically disappeared")

        cv2.imshow("Face Recognition", img)
        if cv2.waitKey(1) & 0xFF == ord(' '):
            cv2.destroyAllWindows()
            break

except KeyboardInterrupt:
    print("[KeyboardInterrupt] Exiting...")
    time.sleep(2)
    exit()

how can i make while the face is detected, it prints only once instead of spamming (without using something like \r)

CodePudding user response：

You need to introduce state and react only when it changes.

Without copy-pasting your entire code, I'll just show you the idea.

# the state variable
seeing_faces = False

while True:
    frame = get_frame()
    faces = detect_faces(frame)
    there_are_faces_now = (len(faces) > 0)

    # compare state to current detection, different? state CHANGES
    if there_are_faces_now and not seeing_faces:
        print("NOW I see faces")
    elif seeing_faces and not there_are_faces_now:
        print("no longer seeing faces")
    else:
        # no change

    # update state
    seeing_faces = there_are_faces_now

CodePudding user response：

You can track the number of detected faces every frame and execute the command you want when the number of faces increases:

try:
    import cv2

    cap = cv2.VideoCapture(0)
    pTime = 0
    cascPath=os.path.dirname(cv2.__file__) "/data/haarcascade_frontalface_default.xml"
    faceCascade = cv2.CascadeClassifier(cascPath)

    face_detected = True
    currentFaces = 0

    while True:
        success, img = cap.read()
        img = cv2.flip(img, 1)
        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
        imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
        cTime = time.time() 
        fps = 1 / (cTime - pTime)
        pTime = cTime
        face_count = 0

        cv2.putText(img, f'FPS:{int(fps)}', (20, 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)

        faces = faceCascade.detectMultiScale(
            gray,
            scaleFactor=1.1,
            minNeighbors=5,
            minSize=(30, 30),
            flags=cv2.CASCADE_SCALE_IMAGE
        )
        for (x, y, w, h) in faces:
            cv2.rectangle(img, (x, y), (x w, y h), (0, 255, 0), 2)
            face_count = face_count 1
                
            cv2.putText(img, 'Face num ' str(face_count), (x-10, y-10),
                        cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
            cv2.putText(img, f'Faces Detected: {face_count}', (20, 70), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)

        print(f"Faces Detected: {face_count}", end="\r")
      
        #if face_count > 0: # If one or more faces were detected
        #    print("a face was detected")
        #elif face_count == 0: # If no faces were detected
        #    print("the face magically disappeared")
        if face_count > currentFaces:
            print("Command to execute, face detected")
        currentFaces = face_count

        cv2.imshow("Face Recognition", img)
        if cv2.waitKey(1) & 0xFF == ord(' '):
            cv2.destroyAllWindows()
            break

except KeyboardInterrupt:
    print("[KeyboardInterrupt] Exiting...")
    time.sleep(2)
    exit()