title: Create mask from skimage contour
body: <p>I have an image that I found contours on with <code>skimage.measure.find_contours()</code> but now I want to create a mask for the pixels fully outside the largest closed contour. Any idea how to do this? </p>
  
  <p>Modifying the example in the documentation: </p>
  
  <pre><code>import numpy as np
  import matplotlib.pyplot as plt
  from skimage import measure
  
  # Construct some test data
  x, y = np.ogrid[-np.pi:np.pi:100j, -np.pi:np.pi:100j]
  r = np.sin(np.exp((np.sin(x)**2 + np.cos(y)**2)))
  
  # Find contours at a constant value of 0.8
  contours = measure.find_contours(r, 0.8)
  
  # Select the largest contiguous contour
  contour = sorted(contours, key=lambda x: len(x))[-1]
  
  # Display the image and plot the contour
  fig, ax = plt.subplots()
  ax.imshow(r, interpolation='nearest', cmap=plt.cm.gray)
  X, Y = ax.get_xlim(), ax.get_ylim()
  ax.step(contour.T[1], contour.T[0], linewidth=2, c='r')
  ax.set_xlim(X), ax.set_ylim(Y)
  plt.show()
  </code></pre>
  
  <p>Here is the contour in red:</p>
  
  <p><a href="https://i.stack.imgur.com/O2Ldt.png" rel="noreferrer"><img src="https://i.stack.imgur.com/O2Ldt.png" alt="enter image description here"></a></p>
  
  <p>But if you zoom in, notice the contour is not at the resolution of the pixels.</p>
  
  <p><a href="https://i.stack.imgur.com/o1IYn.png" rel="noreferrer"><img src="https://i.stack.imgur.com/o1IYn.png" alt="enter image description here"></a></p>
  
  <p>How can I create an image of the same dimensions as the original with the pixels fully outside (i.e. not crossed by the contour line) masked? E.g.</p>
  
  <pre><code>from numpy import ma
  masked_image = ma.array(r.copy(), mask=False)
  masked_image.mask[pixels_outside_contour] = True
  </code></pre>
  
  <p>Thanks!</p>