本文整理汇总了Python中skimage.morphology.closing方法的典型用法代码示例。如果您正苦于以下问题：Python morphology.closing方法的具体用法？Python morphology.closing怎么用？Python morphology.closing使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类skimage.morphology的用法示例。
在下文中一共展示了morphology.closing方法的5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: isolate_islands
# 需要导入模块: from skimage import morphology [as 别名]
# 或者: from skimage.morphology import closing [as 别名]
def isolate_islands(prediction, threshold):
bw = closing(prediction > threshold , square(3))
labelled = label(bw)
regions_properties = regionprops(labelled)
max_region_area = 0
select_region = 0
for region in regions_properties:
if region.area > max_region_area:
max_region_area = region.area
select_region = region
output = np.zeros(labelled.shape)
if select_region == 0:
return output
else:
output[labelled == select_region.label] = 1
return output
# input: output from bwperim -- 2D image with perimeter of the ellipse = 1 示例2: __call__
# 需要导入模块: from skimage import morphology [as 别名]
# 或者: from skimage.morphology import closing [as 别名]
def __call__(self, img_small):
m = morphology.square(self.square_size)
img_th = morphology.black_tophat(img_small, m)
img_sob = abs(filters.sobel_v(img_th))
img_closed = morphology.closing(img_sob, m)
threshold = filters.threshold_otsu(img_closed)
return img_closed > threshold 示例3: prefilter
# 需要导入模块: from skimage import morphology [as 别名]
# 或者: from skimage.morphology import closing [as 别名]
def prefilter(self, img, rec_size=20, se_size=3):
se = morphology.disk(se_size)
im1 = self.morpho_rec(img, rec_size)
im2 = self.morpho_rec2(im1, int(rec_size / 2))
im3 = morphology.closing(im2, se)
return im3 示例4: prefilter_new
# 需要导入模块: from skimage import morphology [as 别名]
# 或者: from skimage.morphology import closing [as 别名]
def prefilter_new(self, img, rec_size=20, se_size=3):
img_cc = ccore.numpy_to_image(img, copy=True)
im1 = ccore.diameter_open(img_cc, rec_size, 8)
im2 = ccore.diameter_close(im1, int(rec_size / 2), 8)
#im1 = self.morpho_rec(img, rec_size)
#im2 = self.morpho_rec2(im1, int(rec_size / 2))
se = morphology.disk(se_size)
im3 = morphology.closing(im2.toArray(), se)
return im3 示例5: closing
# 需要导入模块: from skimage import morphology [as 别名]
# 或者: from skimage.morphology import closing [as 别名]
def closing(gray_img, kernel=None):
"""Wrapper for scikit-image closing functions. Opening can remove small dark spots (i.e. pepper).
Inputs:
gray_img = input image (grayscale or binary)
kernel = optional neighborhood, expressed as an array of 1s and 0s. If None, use cross-shaped structuring element.
:param gray_img: ndarray
:param kernel = ndarray
:return filtered_img: ndarray
"""
params.device += 1
# Make sure the image is binary/grayscale
if len(np.shape(gray_img)) != 2:
fatal_error("Input image must be grayscale or binary")
# If image is binary use the faster method
if len(np.unique(gray_img)) == 2:
bool_img = morphology.binary_closing(image=gray_img, selem=kernel)
filtered_img = np.copy(bool_img.astype(np.uint8) * 255)
# Otherwise use method appropriate for grayscale images
else:
filtered_img = morphology.closing(gray_img, kernel)
if params.debug == 'print':
print_image(filtered_img, os.path.join(params.debug_outdir, str(params.device) + '_opening' + '.png'))
elif params.debug == 'plot':
plot_image(filtered_img, cmap='gray')
return filtered_img