write_class_knnT_write_class_knnWriteClassKnnWriteClassKnn (Operator)

Name

write_class_knnT_write_class_knnWriteClassKnnWriteClassKnn — Save the k-NN classifier in a file.

Signature

write_class_knn( : : KNNHandle, FileName : )

Description

write_class_knnwrite_class_knnWriteClassKnnWriteClassKnnWriteClassKnn writes the k-NN classifier KNNHandleKNNHandleKNNHandleKNNHandleKNNHandle to the file given by FileNameFileNameFileNameFileNamefileName. The classifier can be read again with read_class_knnread_class_knnReadClassKnnReadClassKnnReadClassKnn. Since the samples are an intrinsic component of a k-NN-classifier, the operator write_class_knnwrite_class_knnWriteClassKnnWriteClassKnnWriteClassKnn saves them within the class file. In contrast to other classifiers like SVM, there is no operator for saving the samples separately. The samples can be retrieved from a k-NN-classifier using get_sample_class_knnget_sample_class_knnGetSampleClassKnnGetSampleClassKnnGetSampleClassKnn. The default HALCON file extension for the k-NN classifier is 'gnc'.

Execution Information

Multithreading type: reentrant (runs in parallel with non-exclusive operators).
Multithreading scope: global (may be called from any thread).
Processed without parallelization.

Parameters

KNNHandleKNNHandleKNNHandleKNNHandleKNNHandle (input_control) class_knn → (handle)

Handle of the k-NN classifier.

FileNameFileNameFileNameFileNamefileName (input_control) filename.write → (string)

Name of the file in which the classifier will be written.

File extension: .gnc

Result

write_class_knnwrite_class_knnWriteClassKnnWriteClassKnnWriteClassKnn returns 2 (H_MSG_TRUE). An exception is raised if it was not possible to open file FileNameFileNameFileNameFileNamefileName.

Possible Predecessors

train_class_knntrain_class_knnTrainClassKnnTrainClassKnnTrainClassKnn, read_class_knnread_class_knnReadClassKnnReadClassKnnReadClassKnn

References

Marius Muja, David G. Lowe: “Fast Approximate Nearest Neighbors with Automatic Algorithm Configuration”; International Conference on Computer Vision Theory and Applications (VISAPP 09); 2009.

Module

Foundation

Operators