Source Code for Module pyvision.point.DetectorCorner

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 33   
 34  # TODO: document module. 
 35   
 36  import unittest 
 37  import os.path   
 38   
 39  from numpy import array,ones,zeros,nonzero 
 40  from scipy.ndimage import convolve 
 41  from scipy.ndimage import gaussian_filter,maximum_filter 
 42  # TODO: At some point it would be nice to have the options of prewitt or sobel as filters. 
 43  # from scipy.ndimage import prewitt,sobel 
 44  #from numpy.linalg import det 
 45   
 46  import pyvision as pv 
 47  from pyvision.point.DetectorROI import DetectorROI 
 48  #from pyvision.types.img import Image 
 49  #from pyvision.types.Point import Point 
 50   
 51   
 52  conv2 = convolve 
 53   
 54 -class DetectorCorner(DetectorROI): 
 55 -    def __init__(self,mask = [[-1,0,1]], radius=9, sigma=0.7, k=0.04, **kwargs): 
 56          ''' 
 57          Corner Detector 
 58           
 59          mask   - first dirivitive filter 
 60          radius   - radius of the max filter 
 61          sigma    - sigma of the smoothing gaussian. 
 62          k        - not sure what this parameter means. 
 63           
 64          Passed to superclass: 
 65          n        - is the approximate number of points requested. 
 66          bin_size - the width and height of each bin in pixels. 
 67          corner_selector ('all', 'bins', or 'best') - stratagy for point selection. 
 68           
 69          When corner_selector is set to bins, the image is subdivided in to bins of 
 70          size <bin_size>X<bin_size> pixels and an equal number of points will be taken 
 71          from each of those bins.  This insures that points are found in all parts of the 
 72          image not just where the corners are strongest. 
 73           
 74          This code is based on a function originally written for matlab. 
 75           
 76          Original matlab code by:  
 77          Jingyu Yan and Marc Pollefeys 
 78          Department of Computer Science 
 79          University of North Carolina at Chapel Hill 
 80           
 81          Converted to Python by:  
 82          David Bolme 
 83          Department of Computer Science 
 84          Colorado State Univerisity 
 85          ''' 
 86          DetectorROI.__init__(self,**kwargs) 
 87           
 88          self.mask = mask 
 89          self.radius = radius 
 90          self.sigma = sigma 
 91          self.k = k 
 92           
 93 -    def _detect(self,image): 
 94          # Asssumes a two dimensional array 
 95          A = None 
 96          if isinstance(image,pv.Image): 
 97              A = image.asMatrix2D() 
 98          elif isinstance(image,array) and len(image.shape)==2: 
 99              A = image 
100          else: 
101              raise TypeError("ERROR Unknown Type (%s) - Only arrays and pyvision images supported."%type(image)) 
102       
103          mask = array(self.mask) 
104          assert len(mask.shape) == 2 
105           
106          #feature window calculation 
107          del_A_1 = conv2(A,mask)  
108          del_A_2 = conv2(A,mask.transpose()) 
109       
110       
111          del_A_1_1 = del_A_1 * del_A_1 
112          matrix_1_1 = gaussian_filter(del_A_1_1, self.sigma) 
113          del del_A_1_1 
114               
115          del_A_2_2 = del_A_2 * del_A_2 
116          matrix_2_2 = gaussian_filter(del_A_2_2, self.sigma) 
117          del del_A_2_2 
118           
119          del_A_1_2 = del_A_1 * del_A_2 
120          matrix_1_2 = gaussian_filter(del_A_1_2, self.sigma) 
121          del del_A_1_2 
122           
123          del del_A_1,del_A_2 
124           
125          dM = matrix_1_1*matrix_2_2 - matrix_1_2*matrix_1_2 
126          tM = matrix_1_1+matrix_2_2 
127           
128          del matrix_1_1 , matrix_1_2, matrix_2_2 
129           
130          R = dM-self.k*pow(tM,2) 
131           
132          footprint = ones((self.radius,self.radius)) 
133          mx = maximum_filter(R, footprint = footprint) 
134          local_maxima = (R == mx) * (R != zeros(R.shape)) # make sure to remove completly dark points 
135          del mx 
136           
137          points = nonzero(local_maxima) 
138          del local_maxima 
139           
140          points = array([points[0],points[1]]).transpose() 
141          L = [] 
142          for each in points: 
143              L.append((R[each[0],each[1]],each[0],each[1],None)) 
144           
145          del R 
146           
147          return L 
148   
149   
150   
151 -class _CornerTest(unittest.TestCase): 
152 -    def setUp(self): 
153          self.SHOW_IMAGES = False 
154       
155           
156 -    def testDetectorCorner1(self): 
157          detector = DetectorCorner() 
158          filename = os.path.join(pv.__path__[0],'data','nonface','NONFACE_1.jpg') 
159          im = pv.Image(filename,bw_annotate=True) 
160           
161          points = detector.detect(im) 
162          for _,pt,_ in points: 
163              im.annotatePoint(pt) 
164               
165          if self.SHOW_IMAGES: im.show()   
166          self.assertEquals(len(points),390) 
167   
168 -    def testDetectorCorner2(self): 
169          detector = DetectorCorner() 
170          filename = os.path.join(pv.__path__[0],'data','nonface','NONFACE_19.jpg') 
171          im = pv.Image(filename,bw_annotate=True) 
172           
173          points = detector.detect(im) 
174          for _,pt,_ in points: 
175              im.annotatePoint(pt) 
176               
177          if self.SHOW_IMAGES: im.show()   
178          self.assertEquals(len(points),390) 
179   
180 -    def testDetectorCorner3(self): 
181          detector = DetectorCorner() 
182          filename = os.path.join(pv.__path__[0],'data','nonface','NONFACE_22.jpg') 
183          im = pv.Image(filename,bw_annotate=True) 
184           
185          points = detector.detect(im) 
186          for _,pt,_ in points: 
187              im.annotatePoint(pt) 
188               
189          if self.SHOW_IMAGES: im.show()   
190          self.assertEquals(len(points),390) 
191   
192 -    def testDetectorCorner4(self): 
193          detector = DetectorCorner() 
194          filename = os.path.join(pv.__path__[0],'data','nonface','NONFACE_37.jpg') 
195          im = pv.Image(filename,bw_annotate=True) 
196           
197          points = detector.detect(im) 
198          for _,pt,_ in points: 
199              im.annotatePoint(pt) 
200               
201          if self.SHOW_IMAGES: im.show()   
202          self.assertEquals(len(points),351) 
203   
204 -    def testDetectorCorner5(self): 
205          detector = DetectorCorner(selector='best') 
206          filename = os.path.join(pv.__path__[0],'data','nonface','NONFACE_37.jpg') 
207          im = pv.Image(filename,bw_annotate=True) 
208           
209          points = detector.detect(im) 
210          for _,pt,_ in points: 
211              im.annotatePoint(pt) 
212               
213          if self.SHOW_IMAGES: im.show()   
214          self.assertEquals(len(points),250) 
215           
216 -    def testDetectorCorner6(self): 
217          detector = DetectorCorner(selector='all') 
218          filename = os.path.join(pv.__path__[0],'data','nonface','NONFACE_37.jpg') 
219          im = pv.Image(filename,bw_annotate=True) 
220           
221          points = detector.detect(im) 
222          for _,pt,_ in points: 
223              im.annotatePoint(pt) 
224               
225          if self.SHOW_IMAGES: im.show()   
226          self.assertEquals(len(points),2143) 
227