import cv2
import line

faceCascade = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")
eye_cascade = cv2.CascadeClassifier("haarcascade_eye.xml")

class Camera(object):
    def __init__(self):
        if cv2.__version__.startswith('2'):
            PROP_FRAME_WIDTH = cv2.cv.CV_CAP_PROP_FRAME_WIDTH
            PROP_FRAME_HEIGHT = cv2.cv.CV_CAP_PROP_FRAME_HEIGHT
        elif cv2.__version__.startswith('3'):
            PROP_FRAME_WIDTH = cv2.CAP_PROP_FRAME_WIDTH
            PROP_FRAME_HEIGHT = cv2.CAP_PROP_FRAME_HEIGHT
        else:
            PROP_FRAME_WIDTH = cv2.CAP_PROP_FRAME_WIDTH
            PROP_FRAME_HEIGHT = cv2.CAP_PROP_FRAME_HEIGHT

        self.video = cv2.VideoCapture(0)
        # self.video = cv2.VideoCapture(1)
        # self.video.set(PROP_FRAME_WIDTH, 640)
        # self.video.set(PROP_FRAME_HEIGHT, 480)
        self.video.set(PROP_FRAME_WIDTH, 320)
        self.video.set(PROP_FRAME_HEIGHT, 240)
    
    def __del__(self):
        self.video.release()
    
    def get_frame(self):
        success, image = self.video.read()
        image = cv2.rotate(image, rotateCode = 1)
        gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
        faces = faceCascade.detectMultiScale(gray, scaleFactor = 1.1, minNeighbors = 5, minSize = (30, 30))
        print("人臉數:", len(faces))

        for (x, y, w, h) in faces:
            image = cv2.rectangle(image, (x, y), (x + w, y + h), (0, 255, 0), 3)
            face_rect = gray[y:y + h, x:x + w]
            eyes = eye_cascade.detectMultiScale(face_rect, 1.3, 8)

            for (ex, ey, ew, eh) in eyes:
                cv2.rectangle(image, (x + ex, y + ey), (x + ex + ew, y + ey + eh), (0, 255, 0), 2)
                cv2.imwrite('img/image.jpg', image)
                line.send_msg()
                print("done!")

        ret, jpeg = cv2.imencode(".jpg", image)
        return jpeg.tostring()