Add image resize function

skimage/transform/__init__.py

@@ -5,4 +5,4 @@ from .integral import *
 from ._geometric import (warp, warp_coords, estimate_transform,
                          SimilarityTransform, AffineTransform,
                          ProjectiveTransform, PolynomialTransform)
-from ._warps import rotate, swirl, homography
+from ._warps import resize, rotate, swirl, homography

skimage/transform/_warps.py

@@ -1,5 +1,54 @@
 import numpy as np
-from ._geometric import warp, SimilarityTransform
+from ._geometric import warp, SimilarityTransform, AffineTransform
+
+
+def resize(image, output_shape, order=1, mode='constant', cval=0.):
+    """Resize image.
+
+    Parameters
+    ----------
+    image : ndarray
+        Input image.
+    output_shape : tuple or ndarray
+        Size of the generated output image `(rows, cols)`.
+
+    Returns
+    -------
+    resized : ndarray
+        Resized version of the input.
+
+    Other parameters
+    ----------------
+    order : int
+        Order of splines used in interpolation.  See
+        `scipy.ndimage.map_coordinates` for detail.
+    mode : string
+        How to handle values outside the image borders.  See
+        `scipy.ndimage.map_coordinates` for detail.
+    cval : string
+        Used in conjunction with mode 'constant', the value outside
+        the image boundaries.
+
+    """
+
+    rows, cols = output_shape
+    orig_rows, orig_cols = image.shape[0], image.shape[1]
+
+    rscale = float(orig_rows) / rows
+    cscale = float(orig_cols) / cols
+
+    # 3 control points necessary to estimate exact AffineTransform
+    src_corners = np.array([[1, 1], [1, rows], [cols, rows]]) - 1
+    dst_corners = np.zeros(src_corners.shape, dtype=np.double)
+    # take into account that 0th pixel is at position (0.5, 0.5)
+    dst_corners[:, 0] = cscale * (src_corners[:, 0] + 0.5) - 0.5
+    dst_corners[:, 1] = rscale * (src_corners[:, 1] + 0.5) - 0.5
+
+    tform = AffineTransform()
+    tform.estimate(src_corners, dst_corners)
+
+    return warp(image, tform, output_shape=output_shape, order=order,
+                mode=mode, cval=cval)
 
 
 def rotate(image, angle, resize=False, order=1, mode='constant', cval=0.):

skimage/transform/tests/test_warps.py

@@ -2,7 +2,7 @@ from numpy.testing import assert_array_almost_equal, run_module_suite
 import numpy as np
 from scipy.ndimage import map_coordinates
 
-from skimage.transform import (warp, warp_coords, rotate,
+from skimage.transform import (warp, warp_coords, rotate, resize,
                                AffineTransform,
                                ProjectiveTransform,
                                SimilarityTransform)
@@ -81,6 +81,15 @@ def test_rotate():
     assert_array_almost_equal(x90, np.rot90(x))
 
 
+def test_resize():
+    x = np.zeros((5, 5), dtype=np.double)
+    x[1, 1] = 1
+    resized = resize(x, (10, 10), order=0)
+    ref = np.zeros((10, 10))
+    ref[2:4, 2:4] = 1
+    assert_array_almost_equal(resized, ref)
+
+
 def test_swirl():
     image = img_as_float(data.checkerboard())