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CVBpy 14.0
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CVBpy 14.0
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Factory class for the generation of search predictors. More...
Inherits PredictorFactoryBase.
Public Member Functions | |
| int | num_classification_steps_min () |
| Minimum classification step count. More... | |
| int | sample_size_min () |
| Absolute minimum value for sample_size. More... | |
| cvb.NumberRange | scale_factor_range () |
| Acceptable scale factor range for search classifier training. More... | |
| cvb.NumberRange | scale_factor_range_default () |
| Default value for the scale factor range. More... | |
| cvb.NumberRange | singular_value_range_default () |
| Default value for the singular value range. More... | |
| None | use_settings_from_predictor (self, cvb.polimago.SearchPredictor clf) |
| Copy the predictor generation settings from a predictor. More... | |
 Public Member Functions inherited from PredictorFactoryBase | |
| int | feature_resolution_default () |
| Default value for feature resolution. More... | |
| cvb.NumberRange | feature_resolution_range () |
| Valid range of feature resolution value. More... | |
| str | format_preprocessing_code (str input) |
| Correct a preprocessing code to make sure that no invalid characters are in the code and the code does not exceed the maximum length. More... | |
| float | lambda_default () |
| Default value for lambda. More... | |
| cvb.NumberRange | lambda_range () |
| Acceptable scale factor range for search classifier training. More... | |
| int | preprocessing_max_length () |
| Maximum length of a preprocessing code (excluding the terminating zero). More... | |
| List[str] | preprocessing_valid_characters () |
| Characters that a preprocessing string may contain. More... | |
Properties | |
| angle_range = property | |
| cvb.AngleRange: Sets the range of angles to be covered during classifier training. | |
| extraction_radius = property | |
| float: The radius for extracting positive search instances. More... | |
| feature_resolution_rest = property | |
| int: The feature resolution (determines the size of the classification retina) for step 3 and up. | |
| feature_resolution_step_1_and_2 = property | |
| int: The feature resolution (determines the size of the classification retina) for search step 1 and 2. | |
| invariances = property | |
| int: The invariances to be used for generating the classifier (see cvb.polimago.InvarianceType). | |
| num_classification_steps = property | |
| int: The number of classification steps during search operation. | |
| sample_size = property | |
| int: The sample size that has been used in each training set. | |
| scale_range = property | |
| cvb.NumberRange: The range of scale factors to be covered during classifier training. More... | |
| singular_value_range = property | |
| cvb.NumberRange: The range of permissible singular values to be covered during classifier training. More... | |
| Properties inherited from PredictorFactoryBase | |
| lambda_ = property | |
| float: The regularization value to be used for generating the object. More... | |
| preprocessing = property | |
| str: Preprocessing code with which the object is to be generated. | |
Factory class for the generation of search predictors.
Instantiates a SearchPredictorFactory object.
| int num_classification_steps_min | ( | ) |
Minimum classification step count.
int Minimum classification step count.
| int sample_size_min | ( | ) |
Absolute minimum value for sample_size.
int Sample size minimum.
| cvb.NumberRange scale_factor_range | ( | ) |
Acceptable scale factor range for search classifier training.
cvb.NumberRange Acceptable range.
| cvb.NumberRange scale_factor_range_default | ( | ) |
| cvb.NumberRange singular_value_range_default | ( | ) |
| None use_settings_from_predictor | ( | self, | |
| cvb.polimago.SearchPredictor | clf | ||
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Copy the predictor generation settings from a predictor.
clf : cvb.polimago.SearchPredictor Predictor to take the settings from.
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float: The radius for extracting positive search instances.
The unit size is the size of the feature window, i.e. a value of 0.5 means that positive samples can be extracted from withing a range of +/- Feature Window Width and +/- Feature Window Height around each trained instance. Smaller values will necessitate a finer search grid but may yield better results on difficult search tasks.
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cvb.NumberRange: The range of scale factors to be covered during classifier training.
Only meaningful if the invariance type RotationScaleTranslation has been set.
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cvb.NumberRange: The range of permissible singular values to be covered during classifier training.
Only meaningful if the invariance type AffineGroup has been set.