write_class_knnT_write_class_knnWriteClassKnnWriteClassKnnwrite_class_knn(算子)
名称
write_class_knnT_write_class_knnWriteClassKnnWriteClassKnnwrite_class_knn — 将 k-NN 分类器保存在文件中。
签名
描述
write_class_knnwrite_class_knnWriteClassKnnWriteClassKnnWriteClassKnnwrite_class_knn writes the k-NN classifier KNNHandleKNNHandleKNNHandleKNNHandleKNNHandleknnhandle
to the file given by FileNameFileNameFileNameFileNamefileNamefile_name. The classifier can be read again
with read_class_knnread_class_knnReadClassKnnReadClassKnnReadClassKnnread_class_knn。Since the samples are an intrinsic
component of a k-NN-classifier, the operator
write_class_knnwrite_class_knnWriteClassKnnWriteClassKnnWriteClassKnnwrite_class_knn 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_knnGetSampleClassKnnGetSampleClassKnnGetSampleClassKnnget_sample_class_knn。The default HALCON file extension for the k-NN classifier is 'gnc'.
执行信息
- 多线程类型:可重入(与非独占算子并行运行)。
- 多线程作用域:全局(可从任何线程调用)。
- 未采用并行化处理。
参数
KNNHandleKNNHandleKNNHandleKNNHandleKNNHandleknnhandle (输入控制) class_knn → HClassKnn, HTupleHHandleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)
k-NN 分类器的句柄。
FileNameFileNameFileNameFileNamefileNamefile_name (输入控制) filename.write → HTuplestrHTupleHtuple (string) (string) (HString) (char*)
Name of the file in which the classifier will be written.
文件扩展名:
.gnc
结果
write_class_knnwrite_class_knnWriteClassKnnWriteClassKnnWriteClassKnnwrite_class_knn 返回 2 (H_MSG_TRUE)。
An exception is raised if it was not possible to open file
FileNameFileNameFileNameFileNamefileNamefile_name。
可能的前趋
train_class_knntrain_class_knnTrainClassKnnTrainClassKnnTrainClassKnntrain_class_knn,
read_class_knnread_class_knnReadClassKnnReadClassKnnReadClassKnnread_class_knn
另见
create_class_knncreate_class_knnCreateClassKnnCreateClassKnnCreateClassKnncreate_class_knn,
read_class_knnread_class_knnReadClassKnnReadClassKnnReadClassKnnread_class_knn
参考文献
Marius Muja, David G. Lowe: “Fast Approximate Nearest Neighbors with
Automatic Algorithm Configuration”;
International Conference on Computer Vision Theory
and Applications (VISAPP 09); 2009.
模块
基础