Python cv2.MORPH_BLACKHAT Examples
The following are 2
code examples of cv2.MORPH_BLACKHAT().
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Example #1
Source File: Preprocess.py From ALPR-Indonesia with MIT License | 7 votes |
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 |
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