Make ch3_panorama at least 8x as fast.

PCV/geometry/warp.py

@@ -4,6 +4,7 @@
 from numpy import *
 
 from PCV.geometry import homography
+from PCV.tools import imtools
 
 
 def image_in_image(im1,im2,tp):
@@ -103,50 +104,30 @@ def panorama(H,fromim,toim,padding=2400,delta=2400):
 
     # check if images are grayscale or color
     is_color = len(fromim.shape) == 3
+
+    if is_color:
+        toim_zeros = zeros((toim.shape[0], padding, 3))
+    else:
+        toim_zeros = zeros((toim.shape[0], padding))
 
-    # homography transformation for geometric_transform()
-    def transf(p):
-        p2 = dot(H,[p[0],p[1],1])
-        return (p2[0]/p2[2],p2[1]/p2[2])
-
-    if H[1,2]<0: # fromim is to the right
+    if H[0,2]<0: # fromim is to the right
         print 'warp - right'
-        # transform fromim
-        if is_color:
-            # pad the destination image with zeros to the right
-            toim_t = hstack((toim,zeros((toim.shape[0],padding,3))))
-            fromim_t = zeros((toim.shape[0],toim.shape[1]+padding,toim.shape[2]))
-            for col in range(3):
-                fromim_t[:,:,col] = ndimage.geometric_transform(fromim[:,:,col],
-                                        transf,(toim.shape[0],toim.shape[1]+padding))
-        else:
-            # pad the destination image with zeros to the right
-            toim_t = hstack((toim,zeros((toim.shape[0],padding))))
-            fromim_t = ndimage.geometric_transform(fromim,transf,
-                                    (toim.shape[0],toim.shape[1]+padding)) 
+        toim_t = hstack((toim, toim_zeros))
     else:
         print 'warp - left'
         # add translation to compensate for padding to the left
-        H_delta = array([[1,0,0],[0,1,-delta],[0,0,1]])
+        H_delta = array([[1,0,-delta],[0,1,0],[0,0,1]])
         H = dot(H,H_delta)
-        # transform fromim
-        if is_color:
-            # pad the destination image with zeros to the left
-            toim_t = hstack((zeros((toim.shape[0],padding,3)),toim))
-            fromim_t = zeros((toim.shape[0],toim.shape[1]+padding,toim.shape[2]))
-            for col in range(3):
-                fromim_t[:,:,col] = ndimage.geometric_transform(fromim[:,:,col],
-                                            transf,(toim.shape[0],toim.shape[1]+padding))
-        else:
-            # pad the destination image with zeros to the left
-            toim_t = hstack((zeros((toim.shape[0],padding)),toim))
-            fromim_t = ndimage.geometric_transform(fromim,
-                                    transf,(toim.shape[0],toim.shape[1]+padding))
+        toim_t = hstack((toim_zeros, toim))
 
+    fromim_t = imtools.Htransform(fromim, H, (toim_t.shape[0], toim_t.shape[1]))
+
     # blend and return (put fromim above toim)
     if is_color:
-        # all non black pixels
-        alpha = ((fromim_t[:,:,0] * fromim_t[:,:,1] * fromim_t[:,:,2] ) > 0)
+        # Three separate checks instead of a * b * c > 0 because of uint8 overflow.
+        alpha = ((fromim_t[:, :, 0] > 0) *
+                 (fromim_t[:, :, 1] > 0) *
+                 (fromim_t[:, :, 2] > 0))
         for col in range(3):
             toim_t[:,:,col] = fromim_t[:,:,col]*alpha + toim_t[:,:,col]*(1-alpha)
     else:

PCV/tools/imtools.py

@@ -48,6 +48,14 @@ def imresize(im,sz):
     return array(pil_im.resize(sz))
 
 
+def Htransform(im, H, out_size):
+  """    Applies a homography transform to im."""
+  pil_im = Image.fromarray(im)
+  pil_size = out_size[1], out_size[0]
+  return array(pil_im.transform(
+    pil_size, Image.PERSPECTIVE, H.reshape(9)[0:8] / H[2,2], Image.LINEAR))
+
+
 def histeq(im,nbr_bins=256):
     """    Histogram equalization of a grayscale image. """
 

examples/ch3_panorama.py

@@ -40,9 +40,6 @@ def convert_points(j):
     ndx2 = [int(matches[j][i]) for i in ndx]
     tp = homography.make_homog(l[j][ndx2,:2].T) 
 
-    # switch x and y - TODO this should move elsewhere
-    fp = vstack([fp[1],fp[0],fp[2]])
-    tp = vstack([tp[1],tp[0],tp[2]])
     return fp,tp
 
 
@@ -69,13 +66,13 @@ def convert_points(j):
 im2 = array(Image.open(imname[2]), "uint8")
 im_12 = warp.panorama(H_12,im1,im2,delta,delta)
 
-im1 = array(Image.open(imname[0]), "f")
+im1 = array(Image.open(imname[0]), "uint8")
 im_02 = warp.panorama(dot(H_12,H_01),im1,im_12,delta,delta)
 
-im1 = array(Image.open(imname[3]), "f")
+im1 = array(Image.open(imname[3]), "uint8")
 im_32 = warp.panorama(H_32,im1,im_02,delta,delta)
 
-im1 = array(Image.open(imname[4]), "f")
+im1 = array(Image.open(imname[4]), "uint8")
 im_42 = warp.panorama(dot(H_32,H_43),im1,im_32,delta,2*delta)