Python cv2.MORPH_BLACKHAT Examples

The following are 2 code examples of cv2.MORPH_BLACKHAT(). 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: Preprocess.py    From ALPR-Indonesia with MIT License 7 votes vote down vote up 
def maximizeContrast(imgGrayscale):

    height, width = imgGrayscale.shape

    imgTopHat = np.zeros((height, width, 1), np.uint8)
    imgBlackHat = np.zeros((height, width, 1), np.uint8)

    structuringElement = cv2.getStructuringElement(cv2.MORPH_RECT, (3, 3))

    imgTopHat = cv2.morphologyEx(imgGrayscale, cv2.MORPH_TOPHAT, structuringElement)
    imgBlackHat = cv2.morphologyEx(imgGrayscale, cv2.MORPH_BLACKHAT, structuringElement)

    imgGrayscalePlusTopHat = cv2.add(imgGrayscale, imgTopHat)
    imgGrayscalePlusTopHatMinusBlackHat = cv2.subtract(imgGrayscalePlusTopHat, imgBlackHat)

    return imgGrayscalePlusTopHatMinusBlackHat
# end function
Example #2
Source File: FilterCvQtContainer.py    From bjtu_BinocularCameraRecord with MIT License 4 votes vote down vote up 
def process(self, cv_before, name):

        k = self.k[0]
        kernel = np.ones((k, k), np.uint8)

        if name == 'Invert':
            cv_before = cv2.cvtColor(cv_before, cv2.COLOR_RGB2GRAY)
            cv_after = cv2.bitwise_not(cv_before)
        elif name == 'Histogram Equalization':
            cv_before = cv2.cvtColor(cv_before, cv2.COLOR_RGB2GRAY)
            clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8, 8))
            cv_after = clahe.apply(cv_before)
        elif name == 'Threshold':
            cv_before = cv2.cvtColor(cv_before, cv2.COLOR_RGB2GRAY)
            ret, cv_after = cv2.threshold(
                cv_before, k, 255, cv2.THRESH_BINARY)
        elif name == 'Gaussian Threshold':
            cv_before = cv2.cvtColor(cv_before, cv2.COLOR_RGB2GRAY)
            cv_after = cv2.adaptiveThreshold(cv_before, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C,
                                             cv2.THRESH_BINARY, k, 2)
        elif name == 'HSV':
            cv_before = cv2.cvtColor(cv_before, cv2.COLOR_RGB2HSV)
            lower_color = np.array([k - 35, 0, 0])
            upper_color = np.array([k + 35, 255, 255])
            cv_after = cv2.inRange(cv_before, lower_color, upper_color)
        elif name == 'LAB':
            cv_before = cv2.cvtColor(cv_before, cv2.COLOR_RGB2LAB)
            L, a, b = cv2.split(cv_before)
            ret, cv_after = cv2.threshold(L, k, 255, cv2.THRESH_BINARY)
        elif name == 'Erosion':
            cv_before = cv2.cvtColor(cv_before, cv2.COLOR_RGB2GRAY)
            cv_after = cv2.erode(cv_before, kernel, iterations=1)
        elif name == 'Dilation':
            cv_before = cv2.cvtColor(cv_before, cv2.COLOR_RGB2GRAY)
            cv_after = cv2.dilate(cv_before, kernel, iterations=1)
        elif name == 'Opening':
            cv_before = cv2.cvtColor(cv_before, cv2.COLOR_RGB2GRAY)
            cv_after = cv2.morphologyEx(
                cv_before, cv2.MORPH_OPEN, kernel)
        elif name == 'Closing':
            cv_before = cv2.cvtColor(cv_before, cv2.COLOR_RGB2GRAY)
            cv_after = cv2.morphologyEx(
                cv_before, cv2.MORPH_CLOSE, kernel)
        elif name == 'Top Hat':
            cv_before = cv2.cvtColor(cv_before, cv2.COLOR_RGB2GRAY)
            cv_after = cv2.morphologyEx(
                cv_before, cv2.MORPH_TOPHAT, kernel)
        elif name == 'Black Hat':
            cv_before = cv2.cvtColor(cv_before, cv2.COLOR_RGB2GRAY)
            cv_after = cv2.morphologyEx(
                cv_before, cv2.MORPH_BLACKHAT, kernel)
        elif name == 'Canny':
            cv_before = cv2.cvtColor(cv_before, cv2.COLOR_RGB2GRAY)
            cv_after = cv2.Canny(cv_before, 100, k)
        elif name == 'Laplacian':
            cv_before = cv2.cvtColor(cv_before, cv2.COLOR_RGB2GRAY)
            cv_after = cv2.Laplacian(cv_before, cv2.CV_64F)
            cv_after = np.absolute(cv_after)
            cv_after = np.uint8(cv_after)

        return cv_after