add_samples_image_class_gmmT_add_samples_image_class_gmmAddSamplesImageClassGmmAddSamplesImageClassGmmadd_samples_image_class_gmm (算子名称)
名称
add_samples_image_class_gmmT_add_samples_image_class_gmmAddSamplesImageClassGmmAddSamplesImageClassGmmadd_samples_image_class_gmm — Add training samples from an image to the training data of a
Gaussian Mixture Model.
参数签名
描述
add_samples_image_class_gmmadd_samples_image_class_gmmAddSamplesImageClassGmmAddSamplesImageClassGmmAddSamplesImageClassGmmadd_samples_image_class_gmm adds training samples from the
ImageImageImageImageimageimage to the Gaussian Mixture Model (GMM) given by
GMMHandleGMMHandleGMMHandleGMMHandleGMMHandlegmmhandle. add_samples_image_class_gmmadd_samples_image_class_gmmAddSamplesImageClassGmmAddSamplesImageClassGmmAddSamplesImageClassGmmadd_samples_image_class_gmm is used to
store the training samples before a classifier to be used for the
pixel classification of multichannel images with
classify_image_class_gmmclassify_image_class_gmmClassifyImageClassGmmClassifyImageClassGmmClassifyImageClassGmmclassify_image_class_gmm is trained.
add_samples_image_class_gmmadd_samples_image_class_gmmAddSamplesImageClassGmmAddSamplesImageClassGmmAddSamplesImageClassGmmadd_samples_image_class_gmm works analogously to
add_sample_class_gmmadd_sample_class_gmmAddSampleClassGmmAddSampleClassGmmAddSampleClassGmmadd_sample_class_gmm. The ImageImageImageImageimageimage must have a number
of channels equal to NumDimNumDimNumDimNumDimnumDimnum_dim, as specified with
create_class_gmmcreate_class_gmmCreateClassGmmCreateClassGmmCreateClassGmmcreate_class_gmm. The training regions for the
NumClassesNumClassesNumClassesNumClassesnumClassesnum_classes pixel classes are passed in
ClassRegionsClassRegionsClassRegionsClassRegionsclassRegionsclass_regions. Hence, ClassRegionsClassRegionsClassRegionsClassRegionsclassRegionsclass_regions must be a tuple
containing NumClassesNumClassesNumClassesNumClassesnumClassesnum_classes regions. The order of the regions
in ClassRegionsClassRegionsClassRegionsClassRegionsclassRegionsclass_regions determines the class of the pixels. If
there are no samples for a particular class in ImageImageImageImageimageimage an
empty region must be passed at the position of the class in
ClassRegionsClassRegionsClassRegionsClassRegionsclassRegionsclass_regions. With this mechanism it is possible to use
multiple images to add training samples for all relevant classes to
the GMM by calling add_samples_image_class_gmmadd_samples_image_class_gmmAddSamplesImageClassGmmAddSamplesImageClassGmmAddSamplesImageClassGmmadd_samples_image_class_gmm multiple
times with the different images and suitably chosen regions. The
regions in ClassRegionsClassRegionsClassRegionsClassRegionsclassRegionsclass_regions should contain representative
training samples for the respective classes. Hence, they need not
cover the entire image. The regions in ClassRegionsClassRegionsClassRegionsClassRegionsclassRegionsclass_regions should
not overlap each other, because this would lead to the fact that in
the training data the samples from the overlapping areas would be
assigned to multiple classes, which may lead to a lower
classification performance. Image data of integer type can be
particularly badly suited for modeling with a
GMM. RandomizeRandomizeRandomizeRandomizerandomizerandomize can be used to overcome this problem, as
explained in add_sample_class_gmmadd_sample_class_gmmAddSampleClassGmmAddSampleClassGmmAddSampleClassGmmadd_sample_class_gmm.
运行信息
- 多线程类型:可重入(与非独占操作符并行运行)。
- 多线程作用域:全局(可以从任何线程调用)。
- 未经并行化处理。
This operator modifies the state of the following input parameter:
During execution of this operator, access to the value of this parameter must be synchronized if it is used across multiple threads.
参数表
ImageImageImageImageimageimage (input_object) (multichannel-)image → objectHImageHObjectHImageHobject (byte / cyclic / direction / int1 / int2 / uint2 / int4 / real)
Training image.
ClassRegionsClassRegionsClassRegionsClassRegionsclassRegionsclass_regions (input_object) region-array → objectHRegionHObjectHRegionHobject
Regions of the classes to be trained.
GMMHandleGMMHandleGMMHandleGMMHandleGMMHandlegmmhandle (input_control, state is modified) class_gmm → HClassGmm, HTupleHHandleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)
GMM handle.
RandomizeRandomizeRandomizeRandomizerandomizerandomize (input_control) real → HTuplefloatHTupleHtuple (real) (double) (double) (double)
Standard deviation of the Gaussian noise added
to the training data.
Default:
0.0
Suggested values:
0.0, 1.5, 2.0
Restriction:
Randomize >= 0.0
结果
如果参数均有效，算子
add_samples_image_class_gmmadd_samples_image_class_gmmAddSamplesImageClassGmmAddSamplesImageClassGmmAddSamplesImageClassGmmadd_samples_image_class_gmm 返回值 2 (
H_MSG_TRUE)
. If
necessary an exception is raised.
可能的前置算子
create_class_gmmcreate_class_gmmCreateClassGmmCreateClassGmmCreateClassGmmcreate_class_gmm
可能的后置算子
train_class_gmmtrain_class_gmmTrainClassGmmTrainClassGmmTrainClassGmmtrain_class_gmm,
write_samples_class_gmmwrite_samples_class_gmmWriteSamplesClassGmmWriteSamplesClassGmmWriteSamplesClassGmmwrite_samples_class_gmm
可替代算子
read_samples_class_gmmread_samples_class_gmmReadSamplesClassGmmReadSamplesClassGmmReadSamplesClassGmmread_samples_class_gmm
参考其它
classify_image_class_gmmclassify_image_class_gmmClassifyImageClassGmmClassifyImageClassGmmClassifyImageClassGmmclassify_image_class_gmm,
add_sample_class_gmmadd_sample_class_gmmAddSampleClassGmmAddSampleClassGmmAddSampleClassGmmadd_sample_class_gmm,
clear_samples_class_gmmclear_samples_class_gmmClearSamplesClassGmmClearSamplesClassGmmClearSamplesClassGmmclear_samples_class_gmm,
get_sample_num_class_gmmget_sample_num_class_gmmGetSampleNumClassGmmGetSampleNumClassGmmGetSampleNumClassGmmget_sample_num_class_gmm,
get_sample_class_gmmget_sample_class_gmmGetSampleClassGmmGetSampleClassGmmGetSampleClassGmmget_sample_class_gmm
模块
Foundation