create_class_lut_svm — 使用支持向量机创建查找表来对字节图像进行分类。
create_class_lut_svm( : : SVMHandle, GenParamName, GenParamValue : ClassLUTHandle)
create_class_lut_svm generates a look-up table (LUT)
ClassLUTHandle using the data of a trained Support-Vector-Machine
(SVM) SVMHandle to classify multi-channel byte images. By using
this SVM-based LUT classifier the operator classify_image_class_svm
of the subsequent classification can be replaced by the operator
classify_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 SVM is stored in the LUT.
For the generation of the LUT, the parameters NumFeatures,
Preprocessing, and NumComponents defined in the earlier
called operator create_class_svm are important.
In NumFeatures, the number of image channels the images must have
to be classified is defined. By using the Preprocessing
(see create_class_svm) the number of image channels can be
transformed to NumComponents. NumComponents defines
the length of the feature vector, which the classifier
classify_class_svm handles internally. Because of performance and
disk space, the LUT is restricted to be maximal 3-dimensional. Since
it replaces the operator classify_class_svm,
NumComponents <= 3 must hold.
If there is no preprocessing that reduces the number of image channels
(NumFeatures = NumComponents), all possible pixel values,
which can occur in a byte image, are classified with
classify_class_svm。The returned classes are stored in the LUT.
If there is a preprocessing that reduces the number of image channels
(NumFeatures > NumComponents), the preprocessing
parameters of the SVM are stored in a separate structure of the LUT. To
create the LUT, all transformed pixel values are classified with
classify_class_svm。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_svm。With 'bit_depth' and '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 SVM-based LUT classifier can be set with
GenParamName and GenParamValue:
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' <= 8). If the bit depth of the
LUT is smaller ('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 NumComponents denotes the dimension of the LUT, which is
specified in create_class_svm。For example,
for 'bit_depth' = 7,
NumComponents = 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 NumComponents = 3,
'bit_depth' = 8 and NumClasses < 16
(specified in create_class_svm), the LUT requires 8 MB of storage
with internal storage optimization. If NumClasses = 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_lut
becomes minimal if the LUT fits into the cache.
Typical values: 6,7,8
Default: 8
Restriction: 'bit_depth' >= 1, 'bit_depth' <= 8.
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' is ignored if the bit depth of
the LUT is maximal, thus 'bit_depth' = 8 holds.
If the bit depth of the LUT is smaller
('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 NumComponents denotes the dimension of the LUT, which is
specified in create_class_svm。By choosing
'class_selection' = 'best', the class that
appears most often in the cluster is stored in the LUT.
For 'class_selection' = '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
。
Possible values: 'fast', 'best'
Default: 'fast'
此算子返回一个句柄。请注意，即使该句柄被用作特定算子的输入参数，这些算子仍可能改变此句柄类型的实例状态。
SVMHandle (输入控制) class_svm → (handle)
SVM 句柄。
GenParamName (输入控制) attribute.name-array → (string)
Names of the generic parameters that can be adjusted for the LUT classifier creation.
默认值： []
建议值： 'bit_depth', 'class_selection'
GenParamValue (输入控制) attribute.value-array → (string / integer)
Values of the generic parameters that can be adjusted for the LUT classifier creation.
默认值： []
建议值： 8, 7, 6, 'fast', 'best'
ClassLUTHandle (输出控制) class_lut → (handle)
Handle of the LUT classifier.
如果参数有效，算子 create_class_lut_svm 返回值 2 ( H_MSG_TRUE )。如有必要，则抛出异常。
train_class_svm,
read_class_svm
create_class_lut_gmm,
create_class_lut_knn,
create_class_lut_mlp
classify_image_class_lut,
clear_class_lut
基础