Merged the trunk r8595:8668 (except iOS and new gpu functionality)

samples/python2/common.py

@@ -190,3 +190,7 @@ def mosaic(w, imgs):
     imgs = it.chain([img0], imgs)
     rows = grouper(w, imgs, pad)
     return np.vstack(map(np.hstack, rows))
+
+def getsize(img):
+    h, w = img.shape[:2]
+    return w, h

samples/python2/find_obj.py

@@ -76,8 +76,8 @@ if __name__ == '__main__':
     img2 = cv2.imread(fn2, 0)
 
     surf = cv2.SURF(1000)
-    kp1, desc1 = surf.detect(img1, None, False)
-    kp2, desc2 = surf.detect(img2, None, False)
+    kp1, desc1 = surf.detectAndCompute(img1, None)
+    kp2, desc2 = surf.detectAndCompute(img2, None)
     desc1.shape = (-1, surf.descriptorSize())
     desc2.shape = (-1, surf.descriptorSize())
     print 'img1 - %d features, img2 - %d features' % (len(kp1), len(kp2))

samples/python2/lappyr.py

@@ -0,0 +1,64 @@
+''' An example of Laplacian Pyramid construction and merging.
+
+Level : Intermediate
+
+Usage : python lappyr.py [<video source>]
+
+References:
+  http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.54.299
+
+Alexander Mordvintsev 6/10/12
+'''
+
+import numpy as np
+import cv2
+import video
+from common import nothing, getsize
+
+def build_lappyr(img, leveln=6, dtype=np.int16):
+    img = dtype(img)
+    levels = []
+    for i in xrange(leveln-1):
+        next_img = cv2.pyrDown(img)
+        img1 = cv2.pyrUp(next_img, dstsize=getsize(img))
+        levels.append(img-img1)
+        img = next_img
+    levels.append(img)
+    return levels
+
+def merge_lappyr(levels):
+    img = levels[-1]
+    for lev_img in levels[-2::-1]:
+        img = cv2.pyrUp(img, dstsize=getsize(lev_img))
+        img += lev_img
+    return np.uint8(np.clip(img, 0, 255))
+
+
+if __name__ == '__main__':
+    import sys
+    print __doc__
+
+    try: fn = sys.argv[1]
+    except: fn = 0
+    cap = video.create_capture(fn)
+
+    leveln = 6
+    cv2.namedWindow('level control')
+    for i in xrange(leveln):
+        cv2.createTrackbar('%d'%i, 'level control', 5, 50, nothing)
+
+    while True:
+        ret, frame = cap.read()
+
+        pyr = build_lappyr(frame, leveln)
+        for i in xrange(leveln):
+            v = cv2.getTrackbarPos('%d'%i, 'level control') / 5
+            pyr[i] *= v
+        res = merge_lappyr(pyr)
+
+        cv2.imshow('laplacian pyramid filter', res)
+        
+        if cv2.waitKey(1) == 27:
+            break
+
+

samples/python2/letter_recog.py

@@ -88,7 +88,7 @@ class SVM(LetterStatModel):
         self.model.train(samples, responses, params = params)
 
     def predict(self, samples):
-        return np.float32( [self.model.predict(s) for s in samples] )
+        return self.model.predict_all(samples).ravel()
 
 
 class MLP(LetterStatModel):