MIN: fix unused import

doc/examples/plot_contours.py

@@ -18,7 +18,6 @@ Cubes: A High Resolution 3D Surface Construction Algorithm. Computer Graphics
 import numpy as np
 import matplotlib.pyplot as plt
 
-from skimage import data
 from skimage import measure
 
 

doc/examples/plot_denoise.py

@@ -28,7 +28,7 @@ pixels based on their spatial closeness and radiometric similarity.
 import numpy as np
 import matplotlib.pyplot as plt
 
-from skimage import data, color, img_as_float
+from skimage import data, img_as_float
 from skimage.filter import denoise_tv_chambolle, denoise_bilateral
 
 

doc/examples/plot_ssim.py

@@ -24,7 +24,7 @@ but with very different mean structural similarity indices.
 import numpy as np
 import matplotlib.pyplot as plt
 
-from skimage import data, color, io, exposure, img_as_float
+from skimage import data, img_as_float
 from skimage.measure import structural_similarity as ssim
 
 
@@ -34,6 +34,7 @@ rows, cols = img.shape
 noise = np.ones_like(img) * 0.2 * (img.max() - img.min())
 noise[np.random.random(size=noise.shape) > 0.5] *= -1
 
+
 def mse(x, y):
     return np.linalg.norm(x - y)