Source Code for Module pyvision.point.PointLocator

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  3  # Copyright (c) 2006-2008 David S. Bolme 
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 33   
 34  ''' 
 35  This module contains a methods for finding eyes in a face image. 
 36  The images passed to these methods are cropped images that have 
 37  come from a face detector. 
 38  ''' 
 39   
 40  from pyvision.types.Point import Point 
 41  from pyvision.vector import SVM 
 42  from pyvision.vector.RidgeRegression import KernelRidgeRegression 
 43       
 44       
 45 -class SVMLocator: 
 46       
 47 -    def __init__(self,svm_type=SVM.TYPE_NU_SVR,**kwargs): 
 48          self.x_svm = SVM.SVM(svm_type=svm_type,**kwargs) 
 49          self.y_svm = SVM.SVM(svm_type=svm_type,**kwargs) 
 50          self.x_sum = 0.0 
 51          self.y_sum = 0.0 
 52          self.point_count = 0 
 53       
 54 -    def addTraining(self,image,location): 
 55          ''' 
 56          Pass in an image that is roughly centered on the feature, 
 57          and a true location of that feature in the image. 
 58          ''' 
 59          self.x_svm.addTraining(location.X(),image) 
 60          self.y_svm.addTraining(location.Y(),image) 
 61   
 62          self.x_sum += location.X() 
 63          self.y_sum += location.Y() 
 64          self.point_count += 1 
 65           
 66 -    def train(self,**kwargs): 
 67          # compute the mean location 
 68          self.x_svm.train(**kwargs) 
 69          self.y_svm.train(**kwargs) 
 70           
 71          cx = self.x_sum/self.point_count 
 72          cy = self.y_sum/self.point_count 
 73           
 74          self.mean = Point(cx,cy)     
 75       
 76 -    def predict(self,image): 
 77          x = self.x_svm.predict(image) 
 78          y = self.y_svm.predict(image) 
 79   
 80          return Point(x,y) 
 81           
 82       
 83       
 84 -class KRRLocator: 
 85       
 86 -    def __init__(self,**kwargs): 
 87          self.x_krr = KernelRidgeRegression(**kwargs) 
 88          self.y_krr = KernelRidgeRegression(**kwargs) 
 89          self.x_sum = 0.0 
 90          self.y_sum = 0.0 
 91          self.point_count = 0 
 92       
 93 -    def addTraining(self,image,location): 
 94          ''' 
 95          Pass in an image that is roughly centered on the feature, 
 96          and a true location of that feature in the image. 
 97          ''' 
 98          self.x_krr.addTraining(location.X(),image) 
 99          self.y_krr.addTraining(location.Y(),image) 
100   
101          self.x_sum += location.X() 
102          self.y_sum += location.Y() 
103          self.point_count += 1 
104           
105 -    def train(self,**kwargs): 
106          # compute the mean location 
107          self.x_krr.train(**kwargs) 
108          self.y_krr.train(**kwargs) 
109           
110          cx = self.x_sum/self.point_count 
111          cy = self.y_sum/self.point_count 
112           
113          self.mean = Point(cx,cy)     
114       
115 -    def predict(self,image): 
116          x = self.x_krr.predict(image) 
117          y = self.y_krr.predict(image) 
118   
119          return Point(x,y) 
120