本文整理汇总了Python中cv2.MORPH_BLACKHAT属性的典型用法代码示例。如果您正苦于以下问题：Python cv2.MORPH_BLACKHAT属性的具体用法？Python cv2.MORPH_BLACKHAT怎么用？Python cv2.MORPH_BLACKHAT使用的例子？那么恭喜您, 这里精选的属性代码示例或许可以为您提供帮助。您也可以进一步了解该属性所在类cv2的用法示例。
在下文中一共展示了cv2.MORPH_BLACKHAT属性的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: maximizeContrast
# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import MORPH_BLACKHAT [as 别名]
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 示例2: process
# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import MORPH_BLACKHAT [as 别名]
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