class KRRLocator:
def __init__(self,**kwargs):
self.x_krr = KernelRidgeRegression(**kwargs)
self.y_krr = KernelRidgeRegression(**kwargs)
self.x_sum = 0.0
self.y_sum = 0.0
self.point_count = 0
def addTraining(self,image,location):
'''
Pass in an image that is roughly centered on the feature,
and a true location of that feature in the image.
'''
self.x_krr.addTraining(location.X(),image)
self.y_krr.addTraining(location.Y(),image)
self.x_sum += location.X()
self.y_sum += location.Y()
self.point_count += 1
def train(self,**kwargs):
# compute the mean location
self.x_krr.train(**kwargs)
self.y_krr.train(**kwargs)
cx = self.x_sum/self.point_count
cy = self.y_sum/self.point_count
self.mean = Point(cx,cy)
def predict(self,image):
x = self.x_krr.predict(image)
y = self.y_krr.predict(image)
return Point(x,y)
def __init__(self,**kwargs):
self.x_krr = KernelRidgeRegression(**kwargs)
self.y_krr = KernelRidgeRegression(**kwargs)
self.x_sum = 0.0
self.y_sum = 0.0
self.point_count = 0
