Operator Reference

HALCON Operator Reference / Segmentation / Classification
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classify_image_class_mlpT_classify_image_class_mlpClassifyImageClassMlpClassifyImageClassMlpclassify_image_class_mlp (Operator)

classify_image_class_mlpT_classify_image_class_mlpClassifyImageClassMlpClassifyImageClassMlpclassify_image_class_mlp — Classify an image with a multilayer perceptron.

Signature

classify_image_class_mlp(Image : ClassRegions : MLPHandle, RejectionThreshold : )

Herror T_classify_image_class_mlp(const Hobject Image, Hobject* ClassRegions, const Htuple MLPHandle, const Htuple RejectionThreshold)

void ClassifyImageClassMlp(const HObject& Image, HObject* ClassRegions, const HTuple& MLPHandle, const HTuple& RejectionThreshold)

HRegion HImage::ClassifyImageClassMlp(const HClassMlp& MLPHandle, double RejectionThreshold) const

HRegion HClassMlp::ClassifyImageClassMlp(const HImage& Image, double RejectionThreshold) const

static void HOperatorSet.ClassifyImageClassMlp(HObject image, out HObject classRegions, HTuple MLPHandle, HTuple rejectionThreshold)

HRegion HImage.ClassifyImageClassMlp(HClassMlp MLPHandle, double rejectionThreshold)

HRegion HClassMlp.ClassifyImageClassMlp(HImage image, double rejectionThreshold)

def classify_image_class_mlp(image: HObject, mlphandle: HHandle, rejection_threshold: float) -> HObject

Description

classify_image_class_mlpclassify_image_class_mlpClassifyImageClassMlpClassifyImageClassMlpclassify_image_class_mlp performs a pixel classification with the multilayer perceptron (MLP) MLPHandleMLPHandleMLPHandleMLPHandlemlphandle on the multichannel image ImageImageImageimageimage. Before calling classify_image_class_mlpclassify_image_class_mlpClassifyImageClassMlpClassifyImageClassMlpclassify_image_class_mlp the MLP must be trained with train_class_mlptrain_class_mlpTrainClassMlpTrainClassMlptrain_class_mlp. ImageImageImageimageimage must have NumInputNumInputNumInputnumInputnum_input channels, as specified with create_class_mlpcreate_class_mlpCreateClassMlpCreateClassMlpcreate_class_mlp. On output, ClassRegionsClassRegionsClassRegionsclassRegionsclass_regions contains NumOutputNumOutputNumOutputnumOutputnum_output regions as the result of the classification. Note that the order of the regions that are returned in ClassRegionsClassRegionsClassRegionsclassRegionsclass_regions corresponds to the order of the classes as defined by the training regions in add_samples_image_class_mlpadd_samples_image_class_mlpAddSamplesImageClassMlpAddSamplesImageClassMlpadd_samples_image_class_mlp. The parameter RejectionThresholdRejectionThresholdRejectionThresholdrejectionThresholdrejection_threshold can be used to reject pixels that have an uncertain classification. RejectionThresholdRejectionThresholdRejectionThresholdrejectionThresholdrejection_threshold represents a threshold on the probability measure returned by the classification (see classify_class_mlpclassify_class_mlpClassifyClassMlpClassifyClassMlpclassify_class_mlp and evaluate_class_mlpevaluate_class_mlpEvaluateClassMlpEvaluateClassMlpevaluate_class_mlp). All pixels having a probability below RejectionThresholdRejectionThresholdRejectionThresholdrejectionThresholdrejection_threshold are not assigned to any class. Because an MLP typically assigns pixels that lie outside the convex hull of the training data in the feature space to one of the classes with high probability (confidence), it is useful in many cases to explicitly train a rejection class, even if RejectionThresholdRejectionThresholdRejectionThresholdrejectionThresholdrejection_threshold is used, by adding samples for the rejection class with add_samples_image_class_mlpadd_samples_image_class_mlpAddSamplesImageClassMlpAddSamplesImageClassMlpadd_samples_image_class_mlp and by re-training the MLP with train_class_mlptrain_class_mlpTrainClassMlpTrainClassMlptrain_class_mlp.

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.

Parameters

ImageImageImageimageimage (input_object)  (multichannel-)image → objectHImageHObjectHObjectHobject (byte / cyclic / direction / int1 / int2 / uint2 / int4 / real)

Input image.

ClassRegionsClassRegionsClassRegionsclassRegionsclass_regions (output_object)  region-array → objectHRegionHObjectHObjectHobject *

Segmented classes.

MLPHandleMLPHandleMLPHandleMLPHandlemlphandle (input_control)  class_mlp → HClassMlp, HTupleHHandleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)

MLP handle.

RejectionThresholdRejectionThresholdRejectionThresholdrejectionThresholdrejection_threshold (input_control)  real → HTuplefloatHTupleHtuple (real) (double) (double) (double)

Threshold for the rejection of the classification.

Default: 0.5

Suggested values: 0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0

Restriction: RejectionThreshold >= 0.0 && RejectionThreshold <= 1.0

Example (HDevelop)

read_image (Image, 'ic')
gen_rectangle1 (Board, 80, 320, 110, 350)
gen_rectangle1 (Capacitor, 359, 263, 371, 302)
gen_rectangle1 (Resistor, 200, 252, 290, 256)
gen_rectangle1 (IC, 180, 135, 216, 165)
concat_obj (Board, Capacitor, Classes)
concat_obj (Classes, Resistor, Classes)
concat_obj (Classes, IC, Classes)
create_class_mlp (3, 3, 4, 'softmax', 'principal_components', 3, 42, \
                  MLPHandle)
add_samples_image_class_mlp (Image, Classes, MLPHandle)
get_sample_num_class_mlp (MLPHandle, NumSamples)
train_class_mlp (MLPHandle, 200, 1, 0.01, Error, ErrorLog)
classify_image_class_mlp (Image, ClassRegions, MLPHandle, 0.5)
dev_display (ClassRegions)

Result

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

Possible Predecessors

train_class_mlptrain_class_mlpTrainClassMlpTrainClassMlptrain_class_mlp, read_class_mlpread_class_mlpReadClassMlpReadClassMlpread_class_mlp

Alternatives

classify_image_class_gmmclassify_image_class_gmmClassifyImageClassGmmClassifyImageClassGmmclassify_image_class_gmm, classify_image_class_knnclassify_image_class_knnClassifyImageClassKnnClassifyImageClassKnnclassify_image_class_knn, classify_image_class_svmclassify_image_class_svmClassifyImageClassSvmClassifyImageClassSvmclassify_image_class_svm, classify_image_class_lutclassify_image_class_lutClassifyImageClassLutClassifyImageClassLutclassify_image_class_lut, class_ndim_normclass_ndim_normClassNdimNormClassNdimNormclass_ndim_norm, class_2dim_supclass_2dim_supClass2dimSupClass2dimSupclass_2dim_sup

See also

add_samples_image_class_mlpadd_samples_image_class_mlpAddSamplesImageClassMlpAddSamplesImageClassMlpadd_samples_image_class_mlp, create_class_mlpcreate_class_mlpCreateClassMlpCreateClassMlpcreate_class_mlp

Module

Foundation

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