def attach(self, image_viewer):
# add widgets
self.add_widget(Slider('sigma', 0, 5))
self.add_widget(Slider('low threshold', 0, 255, value_type='int'))
self.add_widget(Slider('high threshold', 0, 255, value_type='int'))
super(CannyPlugin, self).attach(image_viewer)
def go(img):
def preprocess(img):
U = {}
V = {}
s = {}
for i in (0, 1, 2):
res = svd(img[..., i], full_matrices=False)
U[i] = np.mat(res[0])
V[i] = np.mat(res[2])
s[i] = res[1]
return U, V, s
U, V, s = preprocess(img)
def display(_, _from, _to):
res = np.zeros_like(img)
for i in (0, 1, 2):
_s = s[i].copy()
_s[:_from] = 0
_s[_to:] = 0
S = np.mat(np.diag(_s))
res[..., i] = U[i] * S * V[i]
return res
viewer = ImageViewer(img)
plugin = Plugin(image_filter=display)
plugin.name = ""
plugin += Slider('_from', 0, len(s[0]), 0, 'int', update_on='move')
plugin += Slider('_to', 0, len(s[0]), len(s[0]), 'int', update_on='move')
viewer += plugin
viewer.show()
def attach(self, image_viewer):
'''
Override the attaching of the plugin to the ImageViewer. This utilizes
nearly identical implementation to https://github.com/scikit-image/
scikit-image/blob/master/skimage/viewer/plugins/canny.py, but changes
the limits for parameter selection.
'''
image = image_viewer.image
imin, imax = skimage.dtype_limits(image, clip_negative=False)
itype = 'float' if np.issubdtype(image.dtype, np.floating) else 'int'
self.add_widget(Slider('sigma', 0, 2, update_on='release'))
self.add_widget(
Slider('low_threshold',
imin,
imax,
value_type=itype,
update_on='release'))
self.add_widget(
Slider('high_threshold',
imin,
imax,
value_type=itype,
update_on='release'))
self.add_widget(ComboBox('color', self.color_names, ptype='plugin'))
# Call parent method at end b/c it calls `filter_image`, which needs
# the values specified by the widgets. Alternatively, move call to
# parent method to beginning and add a call to `self.filter_image()`
super(CannyPlugin, self).attach(image_viewer)
def test_slider_int():
viewer = get_image_viewer()
sld = Slider('radius', 2, 10, value_type='int')
viewer.plugins[0] += sld
assert_equal(sld.val, 4)
sld.val = 6
assert_equal(sld.val, 6)
sld.editbox.setText('5')
sld._on_editbox_changed()
assert_equal(sld.val, 5)
def test_slider_int():
viewer = get_image_viewer()
sld = Slider('radius', 2, 10, value_type='int')
viewer.plugins[0] += sld
assert_equal(sld.val, 4)
sld.val = 6
assert_equal(sld.val, 6)
sld.editbox.setText('5')
sld._on_editbox_changed()
assert_equal(sld.val, 5)
def test_slider_float():
viewer = get_image_viewer()
sld = Slider('alpha', 2.1, 3.1, value=2.1, value_type='float',
orientation='vertical', update_on='move')
viewer.plugins[0] += sld
assert_equal(sld.val, 2.1)
sld.val = 2.5
assert_almost_equal(sld.val, 2.5, 2)
sld.editbox.setText('0.1')
sld._on_editbox_changed()
assert_almost_equal(sld.val, 2.5, 2)
def test_slider_float():
viewer = get_image_viewer()
sld = Slider('alpha', 2.1, 3.1, value=2.1, value_type='float',
orientation='vertical', update_on='move')
viewer.plugins[0] += sld
assert_equal(sld.val, 2.1)
sld.val = 2.5
assert_almost_equal(sld.val, 2.5, 2)
sld.editbox.setText('0.1')
sld._on_editbox_changed()
assert_almost_equal(sld.val, 2.5, 2)
def __init__(self, search_pattern):
bottom_px = 60
self.bottom_px = bottom_px
plugin = Plugin(image_filter=self.image_filter, dock="right")
self.setup_names = ['Bottom']
self.show_orig = CheckBox('show_orig', value=False, alignment='left')
plugin += self.show_orig
plugin += ComboBox('setup', self.setup_names)
plugin += Slider('bottom_px',
0,
500,
value=self.bottom_px,
value_type='int')
plugin += Button("Print", callback=self.on_print_click)
fnames = [path for path in glob.iglob(search_pattern, recursive=True)]
images, gray_images = read_images(fnames)
self.viewer = CollectionViewer(images)
self.viewer += plugin
def __init__(self, search_pattern):
blur_kernel_size = 1
cal_fnames = [
path for path in glob.iglob('camera_cal/*.jpg', recursive=True)
]
cal_images, cal_gray_images = read_images(cal_fnames)
self.objpoints, self.imgpoints, _ = get_chessboard_corners(
cal_images, cal_gray_images)
self.blur_kernel_size = blur_kernel_size
self.top_left_x = top_left_x
self.top_left_y = top_left_y
self.top_right_x = top_right_x
self.top_right_y = top_right_y
self.bottom_right_x = bottom_right_x
self.bottom_right_y = bottom_right_y
self.bottom_left_x = bottom_left_x
self.bottom_left_y = bottom_left_y
plugin = Plugin(image_filter=self.image_filter, dock="right")
self.setup_names = [
'ROI poly', "ROI Transformation", 'ROI Transformed',
"Final Transformation poly", 'Final Transformation',
'Final Transformed'
]
self.show_orig = CheckBox('show_orig', value=False, alignment='left')
plugin += self.show_orig
plugin += ComboBox('setup', self.setup_names)
plugin += Slider('blur_kernel_size',
0,
31,
value=self.blur_kernel_size,
value_type='int')
plugin += Slider('top_left_x', 0, 1, value=self.top_left_x)
plugin += Slider('top_left_y', 0, 1, value=self.top_left_y)
plugin += Slider('top_right_x', 0, 1, value=self.top_right_x)
plugin += Slider('top_right_y', 0, 1, value=self.top_right_y)
plugin += Slider('bottom_right_x', 0, 1, value=self.bottom_right_x)
plugin += Slider('bottom_right_y', 0, 1, value=self.bottom_right_y)
plugin += Slider('bottom_left_x', 0, 1, value=self.bottom_left_x)
plugin += Slider('bottom_left_y', 0, 1, value=self.bottom_left_y)
plugin += Button("Print", callback=self.on_print_click)
fnames = [path for path in glob.iglob(search_pattern, recursive=True)]
images, gray_images = read_images(fnames)
self.viewer = CollectionViewer(images)
self.viewer += plugin
def go(img):
def preprocess(img):
U = {}
V = {}
s = {}
for i in (0, 1, 2):
res = svd(img[...,i], full_matrices=False)
U[i] = np.mat(res[0])
V[i] = np.mat(res[2])
s[i] = res[1]
return U, V, s
def display(_, R, G, B):
rgb = (R, G, B)
res = np.zeros_like(img)
for i in (0, 1, 2):
_s = s[i].copy()
_s[:rgb[i]] = 0
S = np.mat(np.diag(_s))
res[...,i] = U[i]*S*V[i]
return res
def _display_all(RGB):
if RGB in cache: return cache[RGB]
cache[RGB] = display(None, RGB, RGB, RGB)
return cache[RGB]
if os.path.isfile(cache_fname):
cache = pickle.load(open(cache_fname, "rb"))
n = len(cache) - 1
img = _display_all(n)
else:
U, V, s = preprocess(img)
n = len(s[0])
cache = {}
for i in range(n + 1):
print("caching", i)
_display_all(i)
with open(cache_fname, "wb") as fh:
pickle.dump(cache, fh)
print("wrote to:", cache_fname)
def display_all(_, RGB):
return _display_all(RGB)
viewer = ImageViewer(img)
plugin = Plugin(image_filter = display_all)
plugin.name = ""
plugin += Slider('RGB', 0, n, 0, 'int', update_on='move')
viewer += plugin
viewer.show()
def go(img):
def preprocess(img):
U = {}
V = {}
s = {}
for i in (0, 1, 2):
res = svd(img[..., i], full_matrices=False)
U[i] = np.mat(res[0])
V[i] = np.mat(res[2])
s[i] = res[1]
return U, V, s
U, V, s = preprocess(img)
def display(_, R, G, B):
rgb = (R, G, B)
res = np.zeros_like(img)
for i in (0, 1, 2):
_s = s[i].copy()
_s[rgb[i]:] = 0
S = np.mat(np.diag(_s))
res[..., i] = U[i] * S * V[i]
return res
def display_all(_, RGB):
return display(_, RGB, RGB, RGB)
viewer = ImageViewer(img)
plugin = Plugin(image_filter=display)
plugin.name = ""
plugin += Slider('R', 0, len(s[0]), len(s[0]), 'int')
plugin += Slider('G', 0, len(s[0]), len(s[1]), 'int')
plugin += Slider('B', 0, len(s[0]), len(s[2]), 'int')
viewer += plugin
plugin = Plugin(image_filter=display_all)
plugin.name = ""
plugin += Slider('RGB', 0, len(s[0]), len(s[0]), 'int')
viewer += plugin
viewer.show()
def __init__(self, image, **kwargs):
super(RotatedImageViewer, self).__init__(image, **kwargs)
slider_kwds = dict(value=0,
low=0,
high=5,
update_on='release',
callback=self.update_angle,
value_type='float')
self.slider = Slider('angle', **slider_kwds)
self.layout.addWidget(self.slider)
self.origin_image = image
def viewer():
image = skimage.data.coins()
viewer = ImageViewer(image)
viewer.show()
viewer += LineProfile(viewer)
overlay, data = viewer.show()[0]
#--------------------
denoise_plugin = Plugin(
image_filter=skimage.restoration.denoise_tv_bregman)
denoise_plugin += Slider('weight', 0.01, 0.5, update_on='release')
denoise_plugin += SaveButtons()
viewer = ImageViewer(image)
viewer += denoise_plugin
denoised = viewer.show()[0][0]
def test_plugin():
img = skimage.img_as_float(data.moon())
viewer = ImageViewer(img)
def median_filter(img, radius=3):
return median(img, selem=disk(radius=radius))
plugin = Plugin(image_filter=median_filter)
viewer += plugin
plugin += Slider('radius', 1, 5)
assert_almost_equal(np.std(viewer.image), 12.556, 3)
plugin.filter_image()
assert_almost_equal(np.std(viewer.image), 12.931, 3)
plugin.show()
plugin.close()
plugin.clean_up()
img, _ = plugin.output()
assert_equal(img, viewer.image)
HH = 1. / H
HH[np.abs(HH) > K] = K
gg = np.abs(np.fft.ifft2(F * HH))
gg = gg[:M, :N]
gg = np.clip(gg, 0, clip)
gg -= gg.min()
gg /= gg.max()
return gg
viewer = ImageViewer(image)
plugin = Plugin(image_filter=apply_inverse_filter)
plugin += Slider('T', 0, 1, value=0.5, value_type='float', update_on='release')
plugin += Slider('a',
-0.1,
0.1,
value=0,
value_type='float',
update_on='release')
plugin += Slider('b',
-0.1,
0.1,
value=0,
value_type='float',
update_on='release')
plugin += Slider('K',
0,
100,
from skimage import data
from skimage.filter import canny
from skimage.viewer import ImageViewer
from skimage.viewer.widgets import Slider
from skimage.viewer.widgets.history import SaveButtons
from skimage.viewer.plugins.overlayplugin import OverlayPlugin
image = data.camera()
# You can create a UI for a filter just by passing a filter function...
plugin = OverlayPlugin(image_filter=canny)
# ... and adding widgets to adjust parameter values.
plugin += Slider('sigma', 0, 5)
plugin += Slider('low threshold', 0, 255)
plugin += Slider('high threshold', 0, 255)
# ... and we can also add buttons to save the overlay:
plugin += SaveButtons(name='Save overlay to:')
# Finally, attach the plugin to an image viewer.
viewer = ImageViewer(image)
viewer += plugin
canny_edges = viewer.show()[0][0]
from skimage import data
from skimage.filter import canny
from skimage.viewer import ImageViewer
from skimage.viewer.widgets import Slider
from skimage.viewer.widgets.history import SaveButtons
from skimage.viewer.plugins.overlayplugin import OverlayPlugin
image = data.camera()
# You can create a UI for a filter just by passing a filter function...
plugin = OverlayPlugin(image_filter=canny)
# ... and adding widgets to adjust parameter values.
plugin += Slider('sigma', 0, 5, update_on='release')
plugin += Slider('low threshold', 0, 255, update_on='release')
plugin += Slider('high threshold', 0, 255, update_on='release')
# ... and we can also add buttons to save the overlay:
plugin += SaveButtons(name='Save overlay to:')
# Finally, attach the plugin to an image viewer.
viewer = ImageViewer(image)
viewer += plugin
viewer.show()
==================================
Demo of a CollectionViewer for viewing collections of images with the
`autolevel` rank filter connected as a plugin.
"""
from skimage import data
from skimage.filters import rank
from skimage.morphology import disk
from skimage.viewer import CollectionViewer
from skimage.viewer.widgets import Slider
from skimage.viewer.plugins.base import Plugin
# Wrap autolevel function to make the disk size a filter argument.
def autolevel(image, disk_size):
return rank.autolevel(image, disk(disk_size))
img_collection = [data.camera(), data.coins(), data.text()]
plugin = Plugin(image_filter=autolevel)
plugin += Slider('disk_size', 2, 8, value_type='int')
plugin.name = "Autolevel"
viewer = CollectionViewer(img_collection)
viewer += plugin
viewer.show()
image = data.coins()
viewer = ImageViewer(image)
viewer.show()
#%%
from skimage.viewer.plugins.lineprofile import LineProfile
viewer = ImageViewer(image)
viewer += LineProfile(viewer)
overlay, data = viewer.show()[0]
#%%
from skimage.viewer.widgets import Slider
from skimage.viewer.widgets.history import SaveButtons
denoise_plugin += Slider('weight', 0.01, 0.5, update_on='release')
denoise_plugin += SaveButtons()
#%%
from skimage import data
from skimage.filter import canny
from skimage.viewer import ImageViewer
from skimage.viewer.widgets import Slider
from skimage.viewer.plugins.overlayplugin import OverlayPlugin
plugin = OverlayPlugin(image_filter=canny)
plugin += Slider('sigma', 0, 5)
plugin += Slider('low threshold', 0, 255, value_type='int')
plugin += Slider('high threshold', 0, 255, value_type='int')
viewer = ImageViewer(data.camera())
viewer += plugin
viewer.show()
canny_kwargs = dict([(k, kwargs.pop(k)) for k in canny_keys])
hough_kwargs = kwargs
edges = canny(image, **canny_kwargs)
lines = probabilistic_hough(edges, **hough_kwargs)
self._lines = lines
return edges
def display_filtered_image(self, edges):
self.overlay = edges
if hasattr(self, '_hough_lines'):
self.image_viewer.ax.collections.remove(self._hough_lines)
self._hough_lines = mcoll.LineCollection(self._lines, colors='r')
self.image_viewer.ax.add_collection(self._hough_lines)
self.image_viewer.redraw()
image = data.text()
# Note: ImageViewer must be called before Plugin b/c it starts the event loop.
viewer = ImageViewer(image)
# You can create a UI for a filter just by passing a filter function...
plugin = HoughPlugin()
plugin += Slider('sigma', 0, 5, value=1, update_on='release')
plugin += Slider('low threshold', 0, 255, update_on='release')
plugin += Slider('high threshold', 0, 255, update_on='release')
plugin += Slider('threshold', 0, 255, update_on='release')
plugin += Slider('line length', 0, 100, update_on='release')
plugin += Slider('line gap', 0, 20, update_on='release')
# Finally, attach the plugin to the image viewer.
viewer += plugin
viewer.show()
from skimage.viewer import ImageViewer
from skimage.viewer.widgets import Slider
from skimage.viewer.plugins.overlayplugin import OverlayPlugin
from skimage import data, filter
image = data.coins()
viewer = ImageViewer(image)
plugin = OverlayPlugin(image_filter=filter.canny)
plugin += Slider('sigma', 0, 5, update_on='release')
viewer += plugin
viewer.show()
from skimage import data
from skimage.filter import median_filter
from skimage.viewer import ImageViewer
from skimage.viewer.widgets import Slider, OKCancelButtons, SaveButtons
from skimage.viewer.plugins.base import Plugin
image = data.coins()
viewer = ImageViewer(image)
plugin = Plugin(image_filter=median_filter)
plugin += Slider('radius', 2, 10, value_type='int')
plugin += SaveButtons()
plugin += OKCancelButtons()
viewer += plugin
viewer.show()
def __init__(self, search_pattern):
plugin = Plugin(image_filter=self.image_filter, dock="right")
self.setup_names = [
'Sobel Thresh X', 'Sobel Thresh Y', 'Sobel Thresh X / Y',
'Magnitude Thresh', 'Gradient Direction',
'Magnitude / Gradient Direction Thresh', "2 & 2", "2 | 2"
]
self.show_orig = CheckBox('show_orig', value=False, alignment='left')
plugin += self.show_orig
plugin += ComboBox('setup', self.setup_names)
plugin += Slider('grad_ksize',
0,
31,
value=grad_ksize,
value_type='int')
plugin += Slider('grad_thresh_low',
0,
255,
value=grad_thresh_low,
value_type='int')
plugin += Slider('grad_thresh_high',
0,
255,
value=grad_thresh_high,
value_type='int')
plugin += Slider('mag_binary_ksize',
0,
31,
value=mag_binary_ksize,
value_type='int')
plugin += Slider('mag_binary_thresh_low',
0,
255,
value=mag_binary_thresh_low,
value_type='int')
plugin += Slider('mag_binary_thresh_high',
0,
255,
value=mag_binary_thresh_high,
value_type='int')
plugin += Slider('dir_binary_ksize',
0,
31,
value=dir_binary_ksize,
value_type='int')
plugin += Slider('dir_binary_thresh_low',
0,
np.pi,
value=dir_binary_thresh_low)
plugin += Slider('dir_binary_thresh_high',
0,
np.pi,
value=dir_binary_thresh_high)
fnames = [path for path in glob.iglob(search_pattern, recursive=True)]
images, gray_images = read_images(fnames)
self.viewer = CollectionViewer(images)
self.viewer += plugin
from skimage import data
from skimage.restoration import denoise_tv_chambolle
from skimage.util import img_as_float
from numpy import random, clip
from skimage.viewer import ImageViewer
from skimage.viewer.widgets import (Slider, CheckBox, OKCancelButtons,
SaveButtons)
from skimage.viewer.plugins.base import Plugin
image = img_as_float(data.chelsea())
sigma = 30 / 255.
image = image + random.normal(loc=0, scale=sigma, size=image.shape)
image = clip(image, 0, 1)
viewer = ImageViewer(image)
plugin = Plugin(image_filter=denoise_tv_chambolle)
plugin += Slider('weight', 0.01, 5, value=0.3, value_type='float')
plugin += Slider('n_iter_max', 1, 100, value=20, value_type='int')
plugin += CheckBox('multichannel', value=True)
plugin += SaveButtons()
plugin += OKCancelButtons()
viewer += plugin
viewer.show()
end_points = np.asarray(end_points)[:, ::-1]
image[draw.line(*np.ravel(end_points))] = 1
return image
def hough_lines(image, *args, **kwargs):
# Set threshold to 0.5 since we're working with a binary image (from canny)
lines = probabilistic_hough_line(image, threshold=0.5, *args, **kwargs)
image = line_image(image.shape, lines)
return image
image = data.camera()
canny_viewer = ImageViewer(image)
canny_plugin = CannyPlugin()
canny_viewer += canny_plugin
hough_plugin = OverlayPlugin(image_filter=hough_lines)
hough_plugin.name = 'Hough Lines'
hough_plugin += Slider('line length', 0, 100)
hough_plugin += Slider('line gap', 0, 20)
# Passing a plugin to a viewer connects the output of the plugin to the viewer.
hough_viewer = ImageViewer(canny_plugin)
hough_viewer += hough_plugin
# Show viewers displays both viewers since `hough_viewer` is connected to
# `canny_viewer` through `canny_plugin`
canny_viewer.show()
from skimage import data
from skimage.filter import median_filter
from skimage.viewer import ImageViewer
from skimage.viewer.widgets import Slider, OKCancelButtons, SaveButtons
from skimage.viewer.plugins.base import Plugin
image = data.coins()
viewer = ImageViewer(image)
plugin = Plugin(image_filter=median_filter)
plugin += Slider('radius', 2, 10, value_type='int', update_on='release')
plugin += SaveButtons()
plugin += OKCancelButtons()
viewer += plugin
viewer.show()
from skimage import data
from skimage.filters import rank
from skimage.filters import threshold_isodata
from skimage.morphology import disk
from skimage.viewer import CollectionViewer
from skimage.viewer.widgets import Slider
from skimage.viewer.plugins.base import Plugin
# Wrap autolevel function to make the disk size a filter argument.
def autolevel(image, nbins):
return threshold_isodata(image)
return rank.autolevel(image, nbins)
[row,:, 0]
img_collection = [data.camera(), data.coins(), data.text()]
plugin = Plugin(image_filter=autolevel)
plugin += Slider('nbins', 1, 255, value_type='int')
# plugin.name = "Autolevel"
viewer = CollectionViewer(img_collection)
viewer += plugin
viewer.show()
def __init__(self, search_pattern):
self.plugin = Plugin(image_filter=self.image_filter, dock="right")
self.setup_names = ['Yellow', 'White', 'Yellow / White']
self.color_spaces = ['LAB', 'HSV', 'HLS', 'LUV']
self.show_orig = CheckBox('show_orig', value=False, alignment='left')
self.plugin += self.show_orig
self.setup = ComboBox('setup', self.setup_names)
self.color_space = ComboBox('color_space', self.color_spaces)
self.sensity_range = Slider('sensity_range',
10,
100,
value=sensity_range,
value_type='int')
self.lower_yellow_1 = Slider('lower_yellow_1',
0,
255,
value=lower_yellow_1,
value_type='int')
self.lower_yellow_2 = Slider('lower_yellow_2',
0,
255,
value=lower_yellow_2,
value_type='int')
self.lower_yellow_3 = Slider('lower_yellow_3',
0,
255,
value=lower_yellow_3,
value_type='int')
self.upper_yellow_1 = Slider('upper_yellow_1',
0,
255,
value=upper_yellow_1,
value_type='int')
self.upper_yellow_2 = Slider('upper_yellow_2',
0,
255,
value=upper_yellow_2,
value_type='int')
self.upper_yellow_3 = Slider('upper_yellow_3',
0,
255,
value=upper_yellow_3,
value_type='int')
self.lower_white_1 = Slider('lower_white_1',
0,
255,
value=lower_white_1,
value_type='int')
self.lower_white_2 = Slider('lower_white_2',
0,
255,
value=lower_white_2,
value_type='int')
self.lower_white_3 = Slider('lower_white_3',
0,
255,
value=lower_white_3,
value_type='int')
self.upper_white_1 = Slider('upper_white_1',
0,
255,
value=upper_white_1,
value_type='int')
self.upper_white_2 = Slider('upper_white_2',
0,
255,
value=upper_white_2,
value_type='int')
self.upper_white_3 = Slider('upper_white_3',
0,
255,
value=upper_white_3,
value_type='int')
self.plugin += self.setup
self.plugin += self.color_space
# self.plugin += self.sensity_range
self.plugin += self.lower_yellow_1
self.plugin += self.lower_yellow_2
self.plugin += self.lower_yellow_3
self.plugin += self.upper_yellow_1
self.plugin += self.upper_yellow_2
self.plugin += self.upper_yellow_3
self.plugin += self.lower_white_1
self.plugin += self.lower_white_2
self.plugin += self.lower_white_3
self.plugin += self.upper_white_1
self.plugin += self.upper_white_2
self.plugin += self.upper_white_3
fnames = [path for path in glob.iglob(search_pattern, recursive=True)]
images, gray_images = read_images(fnames)
self.viewer = CollectionViewer(images)
self.viewer.connect_event('button_press_event', self.on_filter_color)
self.viewer.connect_event('key_press_event', self.on_press)
self.viewer += self.plugin
print(value)
return
# image = data.camera()
image = imread(
'/Users/zhizhao/PycharmProjects/BOFO/Devlog/test.jpg') # True means gray
# You can create a UI for a filter just by passing a filter function...
# plugin = OverlayPlugin(image_filter=canny)
plugin = Plugin()
# plugin = OverlayPlugin()
# plugin = LabelPainter()
# plugin = PlotPlugin()
# ... and adding widgets to adjust parameter values.
plugin += Slider(
'sigma', 0, 5, value_type='int', value=3, callback=printf
) # name, low=0.0, high=1.0, value=None, value_type='float','int',orientation='horizontal'/'vertical'
# plugin += Button('name',callback=printf) # name, callback
# plugin += ComboBox('Combo', ['123', '312', 'rqr']) # name, items, ptype='kwarg', callback=None
plugin += Text('text', text='printtext') # name=None, text=''
# plugin += SaveButtons()
plugin += CheckBox(
'check', value=False, alignment='left'
) # name, value=False, alignment='center'/'left'/'right', ptype='kwarg',callback=None
# ... and we can also add buttons to save the overlay:
# plugin += SaveButtons(name='Save overlay to:')
# Finally, attach the plugin to an image viewer.
viewer = ImageViewer(image)
viewer += plugin
viewer.show()[0][0]
from skimage.viewer.plugins.canny import CannyPlugin
def line_image(shape, lines):
image = np.zeros(shape, dtype=bool)
for end_points in lines:
end_points = np.asarray(end_points)[:, ::-1]
image[draw.line(*np.ravel(end_points))] = 1
return image
def hough_lines(image, *args, **kwargs):
lines = probabilistic_hough_line(image, threshold=0.5, *args, **kwargs)
image = line_image(image.shape, lines)
return image
image = data.camera()
canny_viewer = ImageViewer(image)
canny_plugin = CannyPlugin()
canny_viewer += canny_plugin
hough_plugin = OverlayPlugin(image_filter=hough_lines)
hough_plugin += Slider('line length', 0, 100, value=100, update_on='move')
hough_plugin += Slider('line gap', 0, 20, value=0, update_on='move')
hough_viewer = ImageViewer(canny_plugin)
hough_viewer += hough_plugin
canny_viewer.show()
