Learner object that creates a classifier from an image list. More...
Inherits object.
Public Member Functions | |
cvb.minos.Classifier | learn (self, cvb.minos.TrainingSet training_set) |
Learn a new classifier from the training_set using the parameters stored in the properties of this object. More... | |
Properties | |
contrast_trigger = property | |
int: Minimum contrast a Minos feature must achieve, before it is eligible to become part of the classifier. More... | |
contrast_trigger_default = property | |
int: Default value for the contrast_trigger. | |
ensemble_size = property | |
int: Maximum size of the Ensembles of similar instance images to be used for pair feature calculation. More... | |
ensemble_size_default = property | |
int: Default value for the ensemble_size. | |
indifference_radius = property | |
int: Minimum distance to be assumed between a (labeled) positive sample and a counter sample in a training set image. | |
indifference_radius_default = property | |
int: Default value for the indifference_radius. | |
min_pair_features = property | |
int: Minimum number of features to extract for each model when building a classifier. | |
min_pair_features_default = property | |
int: Default value for the min_pair_features. | |
negative_density = property | |
float: Scan density with which to extract counter samples from the training set images. More... | |
negative_density_default = property | |
float: Default value for the negative_density. | |
polydromy = property | |
int: Polydromy value controlling the complexity of the feature search tree in the classifier. More... | |
polydromy_default = property | |
int: Default value for the polydromy. | |
Learner object that creates a classifier from an image list.
Instantiates a ClassifierFactory object.
cvb.minos.Classifier learn | ( | self, | |
cvb.minos.TrainingSet | training_set | ||
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Learn a new classifier from the training_set using the parameters stored in the properties of this object.
training_set : cvb.minos.TrainingSet Training set from which to learn.
cvb.minos.Classifier Newly learned classifier object.
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static |
int: Minimum contrast a Minos feature must achieve, before it is eligible to become part of the classifier.
Lower values will lead to a classifier that is more sensitive in low-contrast situation but might also increase the number of false positive results that need to be filtered out for example by means of their quality measure.
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int: Maximum size of the Ensembles of similar instance images to be used for pair feature calculation.
Valid ensemble sizes must be greater than 0, the default value is 15.
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float: Scan density with which to extract counter samples from the training set images.
Higher densities will lead to a classifier, that is potentially more robust versus false positive detections, but will also result in increased learning times.
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int: Polydromy value controlling the complexity of the feature search tree in the classifier.
Valid polydromy values must be greater than 0, the default value is 2.