Merge pull request #346 from ahojnnes/warp-zoom

Add function to rescale images

skimage/transform/__init__.py

@@ -6,6 +6,6 @@ from ._geometric import (warp, warp_coords, estimate_transform,
                          SimilarityTransform, AffineTransform,
                          ProjectiveTransform, PolynomialTransform,
                          PiecewiseAffineTransform)
-from ._warps import swirl, homography, resize, rotate
+from ._warps import swirl, homography, resize, rotate, rescale
 from .pyramids import (pyramid_reduce, pyramid_expand,
                        pyramid_gaussian, pyramid_laplacian)

skimage/transform/_warps.py

@@ -4,7 +4,7 @@ from ._geometric import (warp, SimilarityTransform, AffineTransform,
 
 
 def resize(image, output_shape, order=1, mode='constant', cval=0.):
-    """Resize image.
+    """Resize image to match a certain size.
 
     Parameters
     ----------
@@ -35,15 +35,15 @@ def resize(image, output_shape, order=1, mode='constant', cval=0.):
     rows, cols = output_shape
     orig_rows, orig_cols = image.shape[0], image.shape[1]
 
-    rscale = float(orig_rows) / rows
-    cscale = float(orig_cols) / cols
+    row_scale = float(orig_rows) / rows
+    col_scale = 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
+    dst_corners[:, 0] = col_scale * (src_corners[:, 0] + 0.5) - 0.5
+    dst_corners[:, 1] = row_scale * (src_corners[:, 1] + 0.5) - 0.5
 
     tform = AffineTransform()
     tform.estimate(src_corners, dst_corners)
@@ -52,6 +52,49 @@ def resize(image, output_shape, order=1, mode='constant', cval=0.):
                 mode=mode, cval=cval)
 
 
+def rescale(image, scale, order=1, mode='constant', cval=0.):
+    """Scale image by a certain factor.
+
+    Parameters
+    ----------
+    image : ndarray
+        Input image.
+    scale : {float, tuple of floats}
+        Scale factors. Separate scale factors can be defined as
+        `(row_scale, col_scale)`.
+
+    Returns
+    -------
+    scaled : ndarray
+        Scaled 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.
+
+    """
+
+    try:
+        row_scale, col_scale = scale
+    except TypeError:
+        row_scale = col_scale = scale
+
+    orig_rows, orig_cols = image.shape[0], image.shape[1]
+    rows = np.round(row_scale * orig_rows)
+    cols = np.round(col_scale * orig_cols)
+    output_shape = (rows, cols)
+
+    return resize(image, output_shape, order=order, mode=mode, cval=cval)
+
+
 def rotate(image, angle, resize=False, order=1, mode='constant', cval=0.):
     """Rotate image by a certain angle around its center.
 

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, resize,
+from skimage.transform import (warp, warp_coords, rotate, resize, rescale,
                                AffineTransform,
                                ProjectiveTransform,
                                SimilarityTransform, homography)
@@ -94,6 +94,24 @@ def test_resize():
     assert_array_almost_equal(resized, ref)
 
 
+def test_scale():
+    # same scale factor
+    x = np.zeros((5, 5), dtype=np.double)
+    x[1, 1] = 1
+    scaled = rescale(x, 2, order=0)
+    ref = np.zeros((10, 10))
+    ref[2:4, 2:4] = 1
+    assert_array_almost_equal(scaled, ref)
+
+    # different scale factors
+    x = np.zeros((5, 5), dtype=np.double)
+    x[1, 1] = 1
+    scaled = rescale(x, (2, 1), order=0)
+    ref = np.zeros((10, 5))
+    ref[2:4, 1] = 1
+    assert_array_almost_equal(scaled, ref)
+
+
 def test_swirl():
     image = img_as_float(data.checkerboard())