Python cv2.COLOR_BGR2HLS Examples

The following are 11 code examples of cv2.COLOR_BGR2HLS(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module cv2 , or try the search function .
Example #1
Source File: transforms.py    From dmc-net with MIT License 6 votes vote down vote up 
def color_aug(img, random_h=36, random_l=50, random_s=50):
    img = cv2.cvtColor(img, cv2.COLOR_BGR2HLS).astype(float)

    h = (random.random() * 2 - 1.0) * random_h
    l = (random.random() * 2 - 1.0) * random_l
    s = (random.random() * 2 - 1.0) * random_s

    img[..., 0] += h
    img[..., 0] = np.minimum(img[..., 0], 180)

    img[..., 1] += l
    img[..., 1] = np.minimum(img[..., 1], 255)

    img[..., 2] += s
    img[..., 2] = np.minimum(img[..., 2], 255)

    img = np.maximum(img, 0)
    img = cv2.cvtColor(img.astype(np.uint8), cv2.COLOR_HLS2BGR)
    return img
Example #2
Source File: transforms.py    From dmc-net with MIT License 6 votes vote down vote up 
def color_aug(img, random_h=36, random_l=50, random_s=50):
    img = cv2.cvtColor(img, cv2.COLOR_BGR2HLS).astype(float)

    h = (random.random() * 2 - 1.0) * random_h
    l = (random.random() * 2 - 1.0) * random_l
    s = (random.random() * 2 - 1.0) * random_s

    img[..., 0] += h
    img[..., 0] = np.minimum(img[..., 0], 180)

    img[..., 1] += l
    img[..., 1] = np.minimum(img[..., 1], 255)

    img[..., 2] += s
    img[..., 2] = np.minimum(img[..., 2], 255)

    img = np.maximum(img, 0)
    img = cv2.cvtColor(img.astype(np.uint8), cv2.COLOR_HLS2BGR)
    return img
Example #3
Source File: lane.py    From vehicle-detection with GNU General Public License v3.0 6 votes vote down vote up 
def find_edges(img, s_thresh=s_thresh, sx_thresh=sx_thresh, dir_thresh=dir_thresh):

    img = np.copy(img)
    # Convert to HSV color space and threshold the s channel
    hls = cv2.cvtColor(img, cv2.COLOR_BGR2HLS).astype(np.float)
    s_channel = hls[:,:,2]
    s_binary = threshold_col_channel(s_channel, thresh=s_thresh)

    # Sobel x
    sxbinary = abs_sobel_thresh(img, orient='x', sobel_kernel=3, thresh=sx_thresh)
    # mag_binary = mag_thresh(img, sobel_kernel=3, thresh=m_thresh)
    # # gradient direction
    dir_binary = dir_threshold(img, sobel_kernel=3, thresh=dir_thresh)
    #
    # # output mask
    combined_binary = np.zeros_like(s_channel)
    combined_binary[(( (sxbinary == 1) & (dir_binary==1) ) | ( (s_binary == 1) & (dir_binary==1) ))] = 1

    # add more weights for the s channel
    c_bi = np.zeros_like(s_channel)
    c_bi[( (sxbinary == 1) & (s_binary==1) )] = 2

    ave_binary = (combined_binary + c_bi)

    return ave_binary
Example #4
Source File: transforms.py    From pytorch-coviar with GNU Lesser General Public License v2.1 6 votes vote down vote up 
def color_aug(img, random_h=36, random_l=50, random_s=50):
    img = cv2.cvtColor(img, cv2.COLOR_BGR2HLS).astype(float)

    h = (random.random() * 2 - 1.0) * random_h
    l = (random.random() * 2 - 1.0) * random_l
    s = (random.random() * 2 - 1.0) * random_s

    img[..., 0] += h
    img[..., 0] = np.minimum(img[..., 0], 180)

    img[..., 1] += l
    img[..., 1] = np.minimum(img[..., 1], 255)

    img[..., 2] += s
    img[..., 2] = np.minimum(img[..., 2], 255)

    img = np.maximum(img, 0)
    img = cv2.cvtColor(img.astype(np.uint8), cv2.COLOR_HLS2BGR)
    return img
Example #5
Source File: lane.py    From Vehicle-and-Speed-Identification with MIT License 6 votes vote down vote up 
def find_edges(img, s_thresh=s_thresh, sx_thresh=sx_thresh, dir_thresh=dir_thresh):

    img = np.copy(img)
    # Convert to HSV color space and threshold the s channel
    hls = cv2.cvtColor(img, cv2.COLOR_BGR2HLS).astype(np.float)
    s_channel = hls[:,:,2]
    s_binary = threshold_col_channel(s_channel, thresh=s_thresh)

    # Sobel x
    sxbinary = abs_sobel_thresh(img, orient='x', sobel_kernel=3, thresh=sx_thresh)
    # mag_binary = mag_thresh(img, sobel_kernel=3, thresh=m_thresh)
    # # gradient direction
    dir_binary = dir_threshold(img, sobel_kernel=3, thresh=dir_thresh)
    #
    # # output mask
    combined_binary = np.zeros_like(s_channel)
    combined_binary[(( (sxbinary == 1) & (dir_binary==1) ) | ( (s_binary == 1) & (dir_binary==1) ))] = 1

    # add more weights for the s channel
    c_bi = np.zeros_like(s_channel)
    c_bi[( (sxbinary == 1) & (s_binary==1) )] = 2

    ave_binary = (combined_binary + c_bi)

    return ave_binary
Example #6
Source File: lane.py    From driving-lane-departure-warning with GNU General Public License v3.0 6 votes vote down vote up 
def find_edges(img, s_thresh=s_thresh, sx_thresh=sx_thresh, dir_thresh=dir_thresh):

    img = np.copy(img)
    # Convert to HSV color space and threshold the s channel
    hls = cv2.cvtColor(img, cv2.COLOR_BGR2HLS).astype(np.float)
    s_channel = hls[:,:,2]
    s_binary = threshold_col_channel(s_channel, thresh=s_thresh)

    # Sobel x
    sxbinary = abs_sobel_thresh(img, orient='x', sobel_kernel=3, thresh=sx_thresh)
    # mag_binary = mag_thresh(img, sobel_kernel=3, thresh=m_thresh)
    # # gradient direction
    dir_binary = dir_threshold(img, sobel_kernel=3, thresh=dir_thresh)
    #
    # # output mask
    combined_binary = np.zeros_like(s_channel)
    combined_binary[(( (sxbinary == 1) & (dir_binary==1) ) | ( (s_binary == 1) & (dir_binary==1) ))] = 1

    # add more weights for the s channel
    c_bi = np.zeros_like(s_channel)
    c_bi[( (sxbinary == 1) & (s_binary==1) )] = 2

    ave_binary = (combined_binary + c_bi)

    return ave_binary
Example #7
Source File: test_weather.py    From imgaug with MIT License 5 votes vote down vote up 
def test_from_colorspace(self):
        # test BGR colorspace
        aug = iaa.FastSnowyLandscape(
            lightness_threshold=100,
            lightness_multiplier=2.0,
            from_colorspace="BGR")
        image = np.arange(0, 6*6*3).reshape((6, 6, 3)).astype(np.uint8)
        image_hls = cv2.cvtColor(image, cv2.COLOR_BGR2HLS)
        mask = (image_hls[..., 1] < 100)
        expected = np.copy(image_hls).astype(np.float32)
        expected[..., 1][mask] *= 2.0
        expected = np.clip(np.round(expected), 0, 255).astype(np.uint8)
        expected = cv2.cvtColor(expected, cv2.COLOR_HLS2BGR)
        observed = aug.augment_image(image)
        assert np.array_equal(observed, expected)
Example #8
Source File: test_scene_detector.py    From ATX with Apache License 2.0 5 votes vote down vote up 
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)
Example #9
Source File: main.py    From BeautyCamera with MIT License 5 votes vote down vote up 
def change_saturation(self):
        if self.raw_image is None:
            return 0

        value = self.ui.horizontalSlider.value()
        img_hsv = cv2.cvtColor(self.current_img, cv2.COLOR_BGR2HLS)
        if value > 2:
            img_hsv[:, :, 2] = np.log(img_hsv[:, :, 2] /255* (value - 1)+1) / np.log(value + 1) * 255
        if value < 0:
            img_hsv[:, :, 2] = np.uint8(img_hsv[:, :, 2] / np.log(- value + np.e))
        self.current_img = cv2.cvtColor(img_hsv, cv2.COLOR_HLS2BGR)

# 明度调节
Example #10
Source File: main.py    From BeautyCamera with MIT License 5 votes vote down vote up 
def change_darker(self):
        if self.raw_image is None:
            return 0
        value = self.ui.horizontalSlider_4.value()
        img_hsv = cv2.cvtColor(self.current_img, cv2.COLOR_BGR2HLS)
        if value > 3:
            img_hsv[:, :, 1] = np.log(img_hsv[:, :, 1] /255* (value - 1)+1) / np.log(value + 1) * 255
        if value < 0:
            img_hsv[:, :, 1] = np.uint8(img_hsv[:, :, 1] / np.log(- value + np.e))
        self.last_image = self.current_img
        self.current_img = cv2.cvtColor(img_hsv, cv2.COLOR_HLS2BGR)

# 人脸识别
Example #11
Source File: inference_utils.py    From rpg_e2vid with GNU General Public License v3.0 5 votes vote down vote up 
def upsample_color_image(grayscale_highres, color_lowres_bgr, colorspace='LAB'):
    """
    Generate a high res color image from a high res grayscale image, and a low res color image,
    using the trick described in:
    http://www.planetary.org/blogs/emily-lakdawalla/2013/04231204-image-processing-colorizing-images.html
    """
    assert(len(grayscale_highres.shape) == 2)
    assert(len(color_lowres_bgr.shape) == 3 and color_lowres_bgr.shape[2] == 3)

    if colorspace == 'LAB':
        # convert color image to LAB space
        lab = cv2.cvtColor(src=color_lowres_bgr, code=cv2.COLOR_BGR2LAB)
        # replace lightness channel with the highres image
        lab[:, :, 0] = grayscale_highres
        # convert back to BGR
        color_highres_bgr = cv2.cvtColor(src=lab, code=cv2.COLOR_LAB2BGR)
    elif colorspace == 'HSV':
        # convert color image to HSV space
        hsv = cv2.cvtColor(src=color_lowres_bgr, code=cv2.COLOR_BGR2HSV)
        # replace value channel with the highres image
        hsv[:, :, 2] = grayscale_highres
        # convert back to BGR
        color_highres_bgr = cv2.cvtColor(src=hsv, code=cv2.COLOR_HSV2BGR)
    elif colorspace == 'HLS':
        # convert color image to HLS space
        hls = cv2.cvtColor(src=color_lowres_bgr, code=cv2.COLOR_BGR2HLS)
        # replace lightness channel with the highres image
        hls[:, :, 1] = grayscale_highres
        # convert back to BGR
        color_highres_bgr = cv2.cvtColor(src=hls, code=cv2.COLOR_HLS2BGR)

    return color_highres_bgr