classify_image_class_mlpT_classify_image_class_mlpClassifyImageClassMlpClassifyImageClassMlpclassify_image_class_mlp (Operator)

Name

classify_image_class_mlpT_classify_image_class_mlpClassifyImageClassMlpClassifyImageClassMlpclassify_image_class_mlp — Classify an image with a multilayer perceptron.

Signature

Description

classify_image_class_mlpclassify_image_class_mlpClassifyImageClassMlpClassifyImageClassMlpClassifyImageClassMlpclassify_image_class_mlp performs a pixel classification with the multilayer perceptron (MLP) MLPHandleMLPHandleMLPHandleMLPHandleMLPHandlemlphandle on the multichannel image ImageImageImageImageimageimage. Before calling classify_image_class_mlpclassify_image_class_mlpClassifyImageClassMlpClassifyImageClassMlpClassifyImageClassMlpclassify_image_class_mlp the MLP must be trained with train_class_mlptrain_class_mlpTrainClassMlpTrainClassMlpTrainClassMlptrain_class_mlp. ImageImageImageImageimageimage must have NumInputNumInputNumInputNumInputnumInputnum_input channels, as specified with create_class_mlpcreate_class_mlpCreateClassMlpCreateClassMlpCreateClassMlpcreate_class_mlp. On output, ClassRegionsClassRegionsClassRegionsClassRegionsclassRegionsclass_regions contains NumOutputNumOutputNumOutputNumOutputnumOutputnum_output regions as the result of the classification. Note that the order of the regions that are returned in ClassRegionsClassRegionsClassRegionsClassRegionsclassRegionsclass_regions corresponds to the order of the classes as defined by the training regions in add_samples_image_class_mlpadd_samples_image_class_mlpAddSamplesImageClassMlpAddSamplesImageClassMlpAddSamplesImageClassMlpadd_samples_image_class_mlp. The parameter RejectionThresholdRejectionThresholdRejectionThresholdRejectionThresholdrejectionThresholdrejection_threshold can be used to reject pixels that have an uncertain classification. RejectionThresholdRejectionThresholdRejectionThresholdRejectionThresholdrejectionThresholdrejection_threshold represents a threshold on the probability measure returned by the classification (see classify_class_mlpclassify_class_mlpClassifyClassMlpClassifyClassMlpClassifyClassMlpclassify_class_mlp and evaluate_class_mlpevaluate_class_mlpEvaluateClassMlpEvaluateClassMlpEvaluateClassMlpevaluate_class_mlp). All pixels having a probability below RejectionThresholdRejectionThresholdRejectionThresholdRejectionThresholdrejectionThresholdrejection_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 RejectionThresholdRejectionThresholdRejectionThresholdRejectionThresholdrejectionThresholdrejection_threshold is used, by adding samples for the rejection class with add_samples_image_class_mlpadd_samples_image_class_mlpAddSamplesImageClassMlpAddSamplesImageClassMlpAddSamplesImageClassMlpadd_samples_image_class_mlp and by re-training the MLP with train_class_mlptrain_class_mlpTrainClassMlpTrainClassMlpTrainClassMlptrain_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

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_mlpClassifyImageClassMlpClassifyImageClassMlpClassifyImageClassMlpclassify_image_class_mlp returns the value 2 (H_MSG_TRUE). If necessary an exception is raised.

Possible Predecessors

train_class_mlptrain_class_mlpTrainClassMlpTrainClassMlpTrainClassMlptrain_class_mlp, read_class_mlpread_class_mlpReadClassMlpReadClassMlpReadClassMlpread_class_mlp

Alternatives

classify_image_class_gmmclassify_image_class_gmmClassifyImageClassGmmClassifyImageClassGmmClassifyImageClassGmmclassify_image_class_gmm, classify_image_class_knnclassify_image_class_knnClassifyImageClassKnnClassifyImageClassKnnClassifyImageClassKnnclassify_image_class_knn, classify_image_class_svmclassify_image_class_svmClassifyImageClassSvmClassifyImageClassSvmClassifyImageClassSvmclassify_image_class_svm, classify_image_class_lutclassify_image_class_lutClassifyImageClassLutClassifyImageClassLutClassifyImageClassLutclassify_image_class_lut, class_ndim_normclass_ndim_normClassNdimNormClassNdimNormClassNdimNormclass_ndim_norm, class_2dim_supclass_2dim_supClass2dimSupClass2dimSupClass2dimSupclass_2dim_sup

See also

add_samples_image_class_mlpadd_samples_image_class_mlpAddSamplesImageClassMlpAddSamplesImageClassMlpAddSamplesImageClassMlpadd_samples_image_class_mlp, create_class_mlpcreate_class_mlpCreateClassMlpCreateClassMlpCreateClassMlpcreate_class_mlp

Module

Foundation