Python cv2 模块，COLOR_BGR2HLS 实例源码

def test_detect():
    dev = AndroidDeviceMinicap()
    dev._adb.start_minitouch()
    time.sleep(3)

    d = SceneDetector('txxscene')
    old, new = None, None
    while True:
        # time.sleep(0.3)
        screen = dev.screenshot_cv2()
        h, w = screen.shape[:2]
        img = cv2.resize(screen, (w/2, h/2))

        # find hsv
        hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
        hls = cv2.cvtColor(img, cv2.COLOR_BGR2HLS)
        _, _, V = cv2.split(hsv)
        V[V<150] = 0
        cv2.imshow('V', V)
        _, _, L = cv2.split(hls)
        L[L<150] = 0
        cv2.imshow('H', L)

        tic = time.clock()
        new = str(d.detect(img))
        t = time.clock() - tic
        if new != old:
            print 'change to', new
            print 'cost time', t
        old = new

        for _, r in d.current_scene:
            x, y, x1, y1 = r
            cv2.rectangle(img, (x,y), (x1,y1), (0,255,0) ,2)
        cv2.imshow('test', img)
        cv2.waitKey(1)

def test_detect():
    dev = AndroidDeviceMinicap()
    dev._adb.start_minitouch()
    time.sleep(3)

    d = SceneDetector('txxscene')
    old, new = None, None
    while True:
        # time.sleep(0.3)
        screen = dev.screenshot_cv2()
        h, w = screen.shape[:2]
        img = cv2.resize(screen, (w/2, h/2))

        # find hsv
        hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
        hls = cv2.cvtColor(img, cv2.COLOR_BGR2HLS)
        _, _, V = cv2.split(hsv)
        V[V<150] = 0
        cv2.imshow('V', V)
        _, _, L = cv2.split(hls)
        L[L<150] = 0
        cv2.imshow('H', L)

        tic = time.clock()
        new = str(d.detect(img))
        t = time.clock() - tic
        if new != old:
            print 'change to', new
            print 'cost time', t
        old = new

        for _, r in d.current_scene:
            x, y, x1, y1 = r
            cv2.rectangle(img, (x,y), (x1,y1), (0,255,0) ,2)
        cv2.imshow('test', img)
        cv2.waitKey(1)

def __hsl_threshold(input, hue, sat, lum):
        """Segment an image based on hue, saturation, and luminance ranges.
        Args:
            input: A BGR numpy.ndarray.
            hue: A list of two numbers the are the min and max hue.
            sat: A list of two numbers the are the min and max saturation.
            lum: A list of two numbers the are the min and max luminance.
        Returns:
            A black and white numpy.ndarray.
        """
        out = cv2.cvtColor(input, cv2.COLOR_BGR2HLS)
        return cv2.inRange(out, (hue[0], lum[0], sat[0]),  (hue[1], lum[1], sat[1]))

def __hsl_threshold(input, hue, sat, lum):
        """Segment an image based on hue, saturation, and luminance ranges.
        Args:
            input: A BGR numpy.ndarray.
            hue: A list of two numbers the are the min and max hue.
            sat: A list of two numbers the are the min and max saturation.
            lum: A list of two numbers the are the min and max luminance.
        Returns:
            A black and white numpy.ndarray.
        """
        out = cv2.cvtColor(input, cv2.COLOR_BGR2HLS)
        return cv2.inRange(out, (hue[0], lum[0], sat[0]),  (hue[1], lum[1], sat[1]))

def __hsl_threshold(input, hue, sat, lum):
        """Segment an image based on hue, saturation, and luminance ranges.
        Args:
            input: A BGR numpy.ndarray.
            hue: A list of two numbers the are the min and max hue.
            sat: A list of two numbers the are the min and max saturation.
            lum: A list of two numbers the are the min and max luminance.
        Returns:
            A black and white numpy.ndarray.
        """
        out = cv2.cvtColor(input, cv2.COLOR_BGR2HLS)
        return cv2.inRange(out, (hue[0], lum[0], sat[0]),  (hue[1], lum[1], sat[1]))

def __hsl_threshold(input, hue, sat, lum):
        """Segment an image based on hue, saturation, and luminance ranges.
        Args:
            input: A BGR numpy.ndarray.
            hue: A list of two numbers the are the min and max hue.
            sat: A list of two numbers the are the min and max saturation.
            lum: A list of two numbers the are the min and max luminance.
        Returns:
            A black and white numpy.ndarray.
        """
        out = cv2.cvtColor(input, cv2.COLOR_BGR2HLS)
        return cv2.inRange(out, (hue[0], lum[0], sat[0]),  (hue[1], lum[1], sat[1]))

def hls(img, op=None):
    return cv.cvtColor(img, cv.COLOR_BGR2HLS)

def hsl_threshold(image, hue=(0, 122), sat=(126, 225), lum=(83, 255)):
        # HSL threshold to highlight just the tape ([hue, sat, lum]).
        hls_min = np.array([hue[0], sat[0], lum[0]])
        hls_max = np.array([hue[1], sat[1], lum[1]])
        image = cv2.cvtColor(image, cv2.COLOR_BGR2HLS)
        image = cv2.inRange(image, hls_min, hls_max)
        return image