Operator Reference

create_class_lut_gmmT_create_class_lut_gmmCreateClassLutGmmCreateClassLutGmmcreate_class_lut_gmm (Operator)

create_class_lut_gmmT_create_class_lut_gmmCreateClassLutGmmCreateClassLutGmmcreate_class_lut_gmm — Create a look-up table using a gaussian mixture model to classify byte images.

Signature

create_class_lut_gmm( : : GMMHandle, GenParamName, GenParamValue : ClassLUTHandle)

Herror T_create_class_lut_gmm(const Htuple GMMHandle, const Htuple GenParamName, const Htuple GenParamValue, Htuple* ClassLUTHandle)

void CreateClassLutGmm(const HTuple& GMMHandle, const HTuple& GenParamName, const HTuple& GenParamValue, HTuple* ClassLUTHandle)

HClassLUT HClassGmm::CreateClassLutGmm(const HTuple& GenParamName, const HTuple& GenParamValue) const

void HClassLUT::HClassLUT(const HClassGmm& GMMHandle, const HTuple& GenParamName, const HTuple& GenParamValue)

void HClassLUT::CreateClassLutGmm(const HClassGmm& GMMHandle, const HTuple& GenParamName, const HTuple& GenParamValue)

def create_class_lut_gmm(gmmhandle: HHandle, gen_param_name: Sequence[str], gen_param_value: Sequence[Union[str, int, float]]) -> HHandle

Description

create_class_lut_gmmcreate_class_lut_gmmCreateClassLutGmmCreateClassLutGmmcreate_class_lut_gmm generates a look-up table (LUT) ClassLUTHandleClassLUTHandleClassLUTHandleclassLUTHandleclass_luthandle using the data of a trained gaussian mixture model (GMM) GMMHandleGMMHandleGMMHandleGMMHandlegmmhandle to classify multi-channel byte images. By using this GMM-based LUT classifier the operator classify_image_class_gmmclassify_image_class_gmmClassifyImageClassGmmClassifyImageClassGmmclassify_image_class_gmm of the subsequent classification can be replaced by the operator classify_image_class_lutclassify_image_class_lutClassifyImageClassLutClassifyImageClassLutclassify_image_class_lut. The classification gets a major speed-up, because the estimation of the class in every image point is no longer necessary since every possible response of the GMM is stored in the LUT. For the generation of the LUT, the parameters NumDimNumDimNumDimnumDimnum_dim, PreprocessingPreprocessingPreprocessingpreprocessingpreprocessing, and NumComponentsNumComponentsNumComponentsnumComponentsnum_components defined in the earlier called operator create_class_gmmcreate_class_gmmCreateClassGmmCreateClassGmmcreate_class_gmm are important. In NumDimNumDimNumDimnumDimnum_dim, the number of image channels the images must have to be classified is defined. By using the PreprocessingPreprocessingPreprocessingpreprocessingpreprocessing (see create_class_gmmcreate_class_gmmCreateClassGmmCreateClassGmmcreate_class_gmm) the number of image channels can be transformed to NumComponentsNumComponentsNumComponentsnumComponentsnum_components. NumComponentsNumComponentsNumComponentsnumComponentsnum_components defines the length of the feature vector, which the classifier classify_class_gmmclassify_class_gmmClassifyClassGmmClassifyClassGmmclassify_class_gmm handles internally. Because of performance and disk space, the LUT is restricted to be maximal 3-dimensional. Since it replaces the operator classify_class_gmmclassify_class_gmmClassifyClassGmmClassifyClassGmmclassify_class_gmm, NumComponentsNumComponentsNumComponentsnumComponentsnum_components <= 3 must hold. If there is no preprocessing that reduces the number of image channels (NumDimNumDimNumDimnumDimnum_dim = NumComponentsNumComponentsNumComponentsnumComponentsnum_components), all possible pixel values, which can occur in a byte image, are classified with classify_class_gmmclassify_class_gmmClassifyClassGmmClassifyClassGmmclassify_class_gmm. The returned classes are stored in the LUT. If there is a preprocessing that reduces the number of image channels (NumDimNumDimNumDimnumDimnum_dim > NumComponentsNumComponentsNumComponentsnumComponentsnum_components), the preprocessing parameters of the GMM are stored in a separate structure of the LUT. To create the LUT, all transformed pixel values are classified with classify_class_gmmclassify_class_gmmClassifyClassGmmClassifyClassGmmclassify_class_gmm. The returned classes are stored in the LUT. Because of the discretization of the LUT, the accuracy of the LUT classifier could become lower than the accuracy of classify_image_class_gmmclassify_image_class_gmmClassifyImageClassGmmClassifyImageClassGmmclassify_image_class_gmm. With 'bit_depth'"bit_depth""bit_depth""bit_depth""bit_depth" and 'class_selection'"class_selection""class_selection""class_selection""class_selection" the accuracy of the classification, the required storage, and the runtime needed to create the LUT can be controlled.

The following parameters of the GMM-based LUT classifier can be set with GenParamNameGenParamNameGenParamNamegenParamNamegen_param_name and GenParamValueGenParamValueGenParamValuegenParamValuegen_param_value:

'bit_depth'"bit_depth""bit_depth""bit_depth""bit_depth":

Number of bits used from the pixels. It controls the storage requirement of the LUT classifier and is bounded by the bit depth of the image ('bit_depth'"bit_depth""bit_depth""bit_depth""bit_depth" <= 8). If the bit depth of the LUT is smaller ('bit_depth'"bit_depth""bit_depth""bit_depth""bit_depth" < 8), the classes of multiple pixel combinations will be mapped to the same LUT entry, which can result in a lower accuracy for the classification. One of these clusters contains pixel combinations, where NumComponentsNumComponentsNumComponentsnumComponentsnum_components denotes the dimension of the LUT, which is specified in create_class_gmmcreate_class_gmmCreateClassGmmCreateClassGmmcreate_class_gmm. For example, for 'bit_depth'"bit_depth""bit_depth""bit_depth""bit_depth" = 7, NumComponentsNumComponentsNumComponentsnumComponentsnum_components = 3, the classes of 8 pixel combinations are mapped in the same LUT entry. The LUT requires at most bytes of storage. For example, for NumComponentsNumComponentsNumComponentsnumComponentsnum_components = 3, 'bit_depth'"bit_depth""bit_depth""bit_depth""bit_depth" = 8 and NumClassesNumClassesNumClassesnumClassesnum_classes < 16 (specified in create_class_gmmcreate_class_gmmCreateClassGmmCreateClassGmmcreate_class_gmm), the LUT requires 8 MB of storage with internal storage optimization. If NumClassesNumClassesNumClassesnumClassesnum_classes = 1, the LUT requires only 2 MB of storage by using the full bit depth of the LUT. The runtime for the classification in classify_image_class_lutclassify_image_class_lutClassifyImageClassLutClassifyImageClassLutclassify_image_class_lut becomes minimal if the LUT fits into the cache. Suggested values: 6,7,8

Default: 8

Restriction: 'bit_depth'"bit_depth""bit_depth""bit_depth""bit_depth" >= 1, 'bit_depth'"bit_depth""bit_depth""bit_depth""bit_depth" <= 8.

'class_selection'"class_selection""class_selection""class_selection""class_selection":

Method for the class selection for the LUT. Can be modified to control the accuracy and the runtime needed to create the LUT classifier. The value in 'class_selection'"class_selection""class_selection""class_selection""class_selection" is ignored if the bit depth of the LUT is maximal, thus 'bit_depth'"bit_depth""bit_depth""bit_depth""bit_depth" = 8 holds. If the bit depth of the LUT is smaller ('bit_depth'"bit_depth""bit_depth""bit_depth""bit_depth" < 8), the classes of multiple pixel combinations will be mapped to the same LUT entry. One of these clusters contains pixel combinations, where NumComponentsNumComponentsNumComponentsnumComponentsnum_components denotes the dimension of the LUT, which is specified in create_class_gmmcreate_class_gmmCreateClassGmmCreateClassGmmcreate_class_gmm. By choosing 'class_selection'"class_selection""class_selection""class_selection""class_selection" = 'best'"best""best""best""best", the class that appears most often in the cluster is stored in the LUT. For 'class_selection'"class_selection""class_selection""class_selection""class_selection" = 'fast'"fast""fast""fast""fast", only one pixel of the cluster, i.e., the pixel with the smallest value (component-wise), is classified. The returned class is stored in the LUT. In this case, the accuracy of the subsequent classification could become lower. On the other hand, the runtime needed to create the LUT can be reduced, which is proportional to the maximal needed storage of the LUT, which is defined with .

List of values: 'fast'"fast""fast""fast""fast", 'best'"best""best""best""best"

Default: 'fast'"fast""fast""fast""fast"

'rejection_threshold'"rejection_threshold""rejection_threshold""rejection_threshold""rejection_threshold":

Threshold for the rejection of uncertain classified points of the GMM. The parameter represents a threshold on the K-sigma probability measure returned by the classification (see classify_class_gmmclassify_class_gmmClassifyClassGmmClassifyClassGmmclassify_class_gmm and evaluate_class_gmmevaluate_class_gmmEvaluateClassGmmEvaluateClassGmmevaluate_class_gmm). All pixels having a probability below 'rejection_threshold'"rejection_threshold""rejection_threshold""rejection_threshold""rejection_threshold" are not assigned to any class.

Default: 0.0001

Restriction: 'rejection_threshold'"rejection_threshold""rejection_threshold""rejection_threshold""rejection_threshold" >= 0, 'rejection_threshold'"rejection_threshold""rejection_threshold""rejection_threshold""rejection_threshold" <= 1.

Execution Information

  • Multithreading type: reentrant (runs in parallel with non-exclusive operators).
  • Multithreading scope: global (may be called from any thread).
  • Automatically parallelized on internal data level.

This operator returns a handle. Note that the state of an instance of this handle type may be changed by specific operators even though the handle is used as an input parameter by those operators.

Parameters

GMMHandleGMMHandleGMMHandleGMMHandlegmmhandle (input_control)  class_gmm HClassGmm, HTupleHHandleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)

GMM handle.

GenParamNameGenParamNameGenParamNamegenParamNamegen_param_name (input_control)  attribute.name-array HTupleSequence[str]HTupleHtuple (string) (string) (HString) (char*)

Names of the generic parameters that can be adjusted for the LUT classifier creation.

Default: []

Suggested values: 'bit_depth'"bit_depth""bit_depth""bit_depth""bit_depth", 'class_selection'"class_selection""class_selection""class_selection""class_selection", 'rejection_threshold'"rejection_threshold""rejection_threshold""rejection_threshold""rejection_threshold"

GenParamValueGenParamValueGenParamValuegenParamValuegen_param_value (input_control)  attribute.value-array HTupleSequence[Union[str, int, float]]HTupleHtuple (string / integer / real) (string / int / long / double) (HString / Hlong / double) (char* / Hlong / double)

Values of the generic parameters that can be adjusted for the LUT classifier creation.

Default: []

Suggested values: 8, 7, 6, 'fast'"fast""fast""fast""fast", 'best'"best""best""best""best"

ClassLUTHandleClassLUTHandleClassLUTHandleclassLUTHandleclass_luthandle (output_control)  class_lut HClassLUT, HTupleHHandleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)

Handle of the LUT classifier.

Result

If the parameters are valid, the operator create_class_lut_gmmcreate_class_lut_gmmCreateClassLutGmmCreateClassLutGmmcreate_class_lut_gmm returns the value 2 ( H_MSG_TRUE) . If necessary an exception is raised.

Possible Predecessors

train_class_gmmtrain_class_gmmTrainClassGmmTrainClassGmmtrain_class_gmm, read_class_gmmread_class_gmmReadClassGmmReadClassGmmread_class_gmm

Possible Successors

classify_image_class_lutclassify_image_class_lutClassifyImageClassLutClassifyImageClassLutclassify_image_class_lut

Alternatives

create_class_lut_knncreate_class_lut_knnCreateClassLutKnnCreateClassLutKnncreate_class_lut_knn, create_class_lut_mlpcreate_class_lut_mlpCreateClassLutMlpCreateClassLutMlpcreate_class_lut_mlp, create_class_lut_svmcreate_class_lut_svmCreateClassLutSvmCreateClassLutSvmcreate_class_lut_svm

See also

classify_image_class_lutclassify_image_class_lutClassifyImageClassLutClassifyImageClassLutclassify_image_class_lut, clear_class_lutclear_class_lutClearClassLutClearClassLutclear_class_lut

Module

Foundation