Add example of connected viewers/plugins

viewer_examples/plugins/probabilistic_hough.py

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+import numpy as np
+
+from skimage import data
+from skimage import draw
+from skimage.transform import probabilistic_hough_line
+
+from skimage.viewer import ImageViewer
+from skimage.viewer.widgets import Slider
+from skimage.viewer.plugins.overlayplugin import OverlayPlugin
+from skimage.viewer.plugins.canny import CannyPlugin
+
+
+def line_image(shape, lines):
+    image = np.zeros(shape, dtype=bool)
+    for end_points in lines:
+        # hough lines returns (x, y) points, draw.line wants (row, columns)
+        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 += Slider('line length', 0, 100, update_on='release')
+hough_plugin += Slider('line gap', 0, 20, update_on='release')
+
+# 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()