Load a saved training set from a file or create an empty training set. More...
Inherits object.
Public Member Functions | |
| List[cvb.minos.SearchResult] | check_consistency (self, float threshold, Optional[float] density=1.0) |
| Test all images in the parent training set for instances of this model, that might have been forgotten during the training process. More... | |
| None | save (self, str file_name) |
| Write the training set to a file. More... | |
| cvb.minos.TrainingSet | transform (self, cvb.Matrix2D transformation) |
| Generate a new training set by transforming this training set with a 2 x 2 transformation matrix. More... | |
Properties | |
| class_count = property | |
| int: The number of identifiable classes inside this training set. More... | |
| comment = property | |
| str: Comment assigned to the training set at generation time. More... | |
| correlation_threshold = property | |
| float: The correlation value under which Minos proposes generating a new model, not generating a new instance of an existing model with which the new instance correlates poorly. More... | |
| expectation_radius = property | |
| float: The radius that is searched for the best occurrence of a sample, when adding a new sample to the training set. More... | |
| extent = property | |
| cvb.Rect: Extent of the classes in the training set relative to the anchor point. More... | |
| file_name = property | |
| str: Name of the file, from which this training set was loaded (empty string if this image list was neither loaded nor saved since its construction). More... | |
| is_modified = property | |
| bool: Flag that informs about unsaved modifications to the training set. More... | |
| last_feature_window = property | |
| cvb.Rect: Feature window of the last model that has been created for the training set. More... | |
Load a saved training set from a file or create an empty training set.
If file_name argument is specified, the training set will be loaded from the file. If missing, empty training set will be created.
Instantiates a TrainingSet object.
file_name : Optional[str] Name of the file to be loaded.
| List[cvb.minos.SearchResult] check_consistency | ( | self, | |
| float | threshold, | ||
| Optional[float] | density = 1.0 |
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| ) |
Test all images in the parent training set for instances of this model, that might have been forgotten during the training process.
threshold : float Correlation threshold to be used for the consistency check.
density : Optional[float] Density to be used for the consistency check.
List[cvb.minos.SearchResult] Potentially forgotten positive samples, that may be added to the training set.
| None save | ( | self, | |
| str | file_name | ||
| ) |
Write the training set to a file.
As a side effect this function sets the is_modified flag to False, if the training set was saved successfully.
file_name : str Path to save to.
| cvb.minos.TrainingSet transform | ( | self, | |
| cvb.Matrix2D | transformation | ||
| ) |
Generate a new training set by transforming this training set with a 2 x 2 transformation matrix.
transformation : cvb.Matrix2D Matrix with which to transform the geometry of this training set.
cvb.minos.TrainingSet Transformed training set.
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int: The number of identifiable classes inside this training set.
The number of classes cannot be higher than the number of trained models. If two models have the same name, the classifier can no longer distinguish between these two models, reducing the class_count property.
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str: Comment assigned to the training set at generation time.
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float: The correlation value under which Minos proposes generating a new model, not generating a new instance of an existing model with which the new instance correlates poorly.
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float: The radius that is searched for the best occurrence of a sample, when adding a new sample to the training set.
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cvb.Rect: Extent of the classes in the training set relative to the anchor point.
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str: Name of the file, from which this training set was loaded (empty string if this image list was neither loaded nor saved since its construction).
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bool: Flag that informs about unsaved modifications to the training set.
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cvb.Rect: Feature window of the last model that has been created for the training set.