classify_image_class_svmT_classify_image_class_svmClassifyImageClassSvmClassifyImageClassSvmclassify_image_class_svm (算子名称)
名称
classify_image_class_svmT_classify_image_class_svmClassifyImageClassSvmClassifyImageClassSvmclassify_image_class_svm — Classify an image with a support vector machine.
参数签名
def classify_image_class_svm(image: HObject, svmhandle: HHandle) -> HObject
描述
classify_image_class_svmclassify_image_class_svmClassifyImageClassSvmClassifyImageClassSvmClassifyImageClassSvmclassify_image_class_svm performs a pixel classification
with the support vector machine (SVM) SVMHandleSVMHandleSVMHandleSVMHandleSVMHandlesvmhandle on the
multichannel image ImageImageImageImageimageimage. Before calling
classify_image_class_svmclassify_image_class_svmClassifyImageClassSvmClassifyImageClassSvmClassifyImageClassSvmclassify_image_class_svm the SVM must be trained with
train_class_svmtrain_class_svmTrainClassSvmTrainClassSvmTrainClassSvmtrain_class_svm. ImageImageImageImageimageimage must have
NumFeaturesNumFeaturesNumFeaturesNumFeaturesnumFeaturesnum_features channels, as specified with
create_class_svmcreate_class_svmCreateClassSvmCreateClassSvmCreateClassSvmcreate_class_svm. On output, ClassRegionsClassRegionsClassRegionsClassRegionsclassRegionsclass_regions contains
NumClassesNumClassesNumClassesNumClassesnumClassesnum_classes 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_svmadd_samples_image_class_svmAddSamplesImageClassSvmAddSamplesImageClassSvmAddSamplesImageClassSvmadd_samples_image_class_svm.
To prevent that the SVM assigns pixels that lie outside the
convex hull of the training data in the feature space to one of the
classes, it is useful in many cases to explicitly train a rejection
class by adding samples for the rejection class with
add_samples_image_class_svmadd_samples_image_class_svmAddSamplesImageClassSvmAddSamplesImageClassSvmAddSamplesImageClassSvmadd_samples_image_class_svm and by re-training the SVM with
train_class_svmtrain_class_svmTrainClassSvmTrainClassSvmTrainClassSvmtrain_class_svm.
An alternative for explicitly defining a rejection class is to use an SVM in
the mode 'novelty-detection'"novelty-detection""novelty-detection""novelty-detection""novelty-detection""novelty-detection". Please refer to the description in
create_class_svmcreate_class_svmCreateClassSvmCreateClassSvmCreateClassSvmcreate_class_svm and add_samples_image_class_svmadd_samples_image_class_svmAddSamplesImageClassSvmAddSamplesImageClassSvmAddSamplesImageClassSvmadd_samples_image_class_svm.
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)。
- Automatically parallelized on internal data level.
参数表
ImageImageImageImageimageimage (input_object) (multichannel-)image → objectHImageHObjectHImageHobject (byte / cyclic / direction / int1 / int2 / uint2 / int4 / real)
Input image.
ClassRegionsClassRegionsClassRegionsClassRegionsclassRegionsclass_regions (output_object) region-array → objectHRegionHObjectHRegionHobject *
Segmented classes.
SVMHandleSVMHandleSVMHandleSVMHandleSVMHandlesvmhandle (input_control) class_svm → HClassSvm, HTupleHHandleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)
SVM handle.
例程 (HDevelop)
read_image (Image, 'ic')
gen_rectangle1 (Board, 20, 270, 160, 420)
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_svm (3, 'rbf', 0.01, 0.01, 4, 'one-versus-all', \
'normalization', 3, SVMHandle)
add_samples_image_class_svm (Image, Classes, SVMHandle)
train_class_svm (SVMHandle, 0.001, 'default')
reduce_class_svm (SVMHandle, 'bottom_up', 2, 0.01, SVMHandleReduced)
classify_image_class_svm (Image, ClassRegions, SVMHandleReduced)
dev_display (ClassRegions)
结果
If the parameters are valid 该算子
classify_image_class_svmclassify_image_class_svmClassifyImageClassSvmClassifyImageClassSvmClassifyImageClassSvmclassify_image_class_svm 返回值 2 (
H_MSG_TRUE)
. If
necessary, an exception is raised.
可能的前置算子
train_class_svmtrain_class_svmTrainClassSvmTrainClassSvmTrainClassSvmtrain_class_svm,
read_class_svmread_class_svmReadClassSvmReadClassSvmReadClassSvmread_class_svm,
reduce_class_svmreduce_class_svmReduceClassSvmReduceClassSvmReduceClassSvmreduce_class_svm
可替代算子
classify_image_class_gmmclassify_image_class_gmmClassifyImageClassGmmClassifyImageClassGmmClassifyImageClassGmmclassify_image_class_gmm,
classify_image_class_knnclassify_image_class_knnClassifyImageClassKnnClassifyImageClassKnnClassifyImageClassKnnclassify_image_class_knn,
classify_image_class_mlpclassify_image_class_mlpClassifyImageClassMlpClassifyImageClassMlpClassifyImageClassMlpclassify_image_class_mlp,
classify_image_class_lutclassify_image_class_lutClassifyImageClassLutClassifyImageClassLutClassifyImageClassLutclassify_image_class_lut,
class_ndim_normclass_ndim_normClassNdimNormClassNdimNormClassNdimNormclass_ndim_norm,
class_2dim_supclass_2dim_supClass2dimSupClass2dimSupClass2dimSupclass_2dim_sup
参考其它
add_samples_image_class_svmadd_samples_image_class_svmAddSamplesImageClassSvmAddSamplesImageClassSvmAddSamplesImageClassSvmadd_samples_image_class_svm,
create_class_svmcreate_class_svmCreateClassSvmCreateClassSvmCreateClassSvmcreate_class_svm
模块
Foundation