get_dl_classifier_paramT_get_dl_classifier_paramGetDlClassifierParamGetDlClassifierParamget_dl_classifier_param (Operator)
Name
get_dl_classifier_paramT_get_dl_classifier_paramGetDlClassifierParamGetDlClassifierParamget_dl_classifier_param — Return the parameters of a deep-learning-based classifier.
Warning
get_dl_classifier_paramget_dl_classifier_paramGetDlClassifierParamGetDlClassifierParamGetDlClassifierParamget_dl_classifier_param is obsolete and is only provided for
reasons of backward compatibility. New applications should use common
CNN-based operator get_dl_model_paramget_dl_model_paramGetDlModelParamGetDlModelParamGetDlModelParamget_dl_model_param instead.
Signature
Description
get_dl_classifier_paramget_dl_classifier_paramGetDlClassifierParamGetDlClassifierParamGetDlClassifierParamget_dl_classifier_param returns the parameter values
GenParamValueGenParamValueGenParamValueGenParamValuegenParamValuegen_param_value of GenParamNameGenParamNameGenParamNameGenParamNamegenParamNamegen_param_name of the neural
network DLClassifierHandleDLClassifierHandleDLClassifierHandleDLClassifierHandleDLClassifierHandledlclassifier_handle.
The hyperparameters and network parameters can be set with the operator
set_dl_classifier_paramset_dl_classifier_paramSetDlClassifierParamSetDlClassifierParamSetDlClassifierParamset_dl_classifier_param, in whose reference entry they are described
in detail. With get_dl_classifier_paramget_dl_classifier_paramGetDlClassifierParamGetDlClassifierParamGetDlClassifierParamget_dl_classifier_param you can query all these
values.
Additionally, there are parameters defined by the network which are
read-only. These parameters are:
- 'image_range_min'"image_range_min""image_range_min""image_range_min""image_range_min""image_range_min":
Minimum gray value.
- 'image_range_max'"image_range_max""image_range_max""image_range_max""image_range_max""image_range_max":
-
Maximum gray value.
The precise values for these parameters and the default parameters for the
image dimension depend on the concrete network, see
read_dl_classifierread_dl_classifierReadDlClassifierReadDlClassifierReadDlClassifierread_dl_classifier.
Every image that is fed into the network must be present according to the
parameters defining the image properties.
To preprocess images accordingly, the procedure
preprocess_dl_classifier_images is available.
For an explanation of the concept of deep-learning-based classification
see the introduction of chapter Deep Learning / Classification.
The workflow involving this legacy operator is described in the chapter
Legacy / DL Classification.
Execution Information
- Multithreading type: reentrant (runs in parallel with non-exclusive operators).
- Multithreading scope: global (may be called from any thread).
- Processed without parallelization.
Parameters
DLClassifierHandleDLClassifierHandleDLClassifierHandleDLClassifierHandleDLClassifierHandledlclassifier_handle (input_control) dl_classifier → HDlClassifier, HTupleHHandleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)
Handle of the deep-learning-based classifier.
GenParamNameGenParamNameGenParamNameGenParamNamegenParamNamegen_param_name (input_control) attribute.name(-array) → HTupleMaybeSequence[str]HTupleHtuple (string) (string) (HString) (char*)
Name of the generic parameter.
Default:
'gpu'
"gpu"
"gpu"
"gpu"
"gpu"
"gpu"
List of values:
'batch_size'"batch_size""batch_size""batch_size""batch_size""batch_size", 'batch_size_multiplier'"batch_size_multiplier""batch_size_multiplier""batch_size_multiplier""batch_size_multiplier""batch_size_multiplier", 'classes'"classes""classes""classes""classes""classes", 'gpu'"gpu""gpu""gpu""gpu""gpu", 'image_dimensions'"image_dimensions""image_dimensions""image_dimensions""image_dimensions""image_dimensions", 'image_height'"image_height""image_height""image_height""image_height""image_height", 'image_num_channels'"image_num_channels""image_num_channels""image_num_channels""image_num_channels""image_num_channels", 'image_range_max'"image_range_max""image_range_max""image_range_max""image_range_max""image_range_max", 'image_range_min'"image_range_min""image_range_min""image_range_min""image_range_min""image_range_min", 'image_width'"image_width""image_width""image_width""image_width""image_width", 'learning_rate'"learning_rate""learning_rate""learning_rate""learning_rate""learning_rate", 'momentum'"momentum""momentum""momentum""momentum""momentum", 'runtime'"runtime""runtime""runtime""runtime""runtime", 'runtime_init'"runtime_init""runtime_init""runtime_init""runtime_init""runtime_init", 'weight_prior'"weight_prior""weight_prior""weight_prior""weight_prior""weight_prior"
GenParamValueGenParamValueGenParamValueGenParamValuegenParamValuegen_param_value (output_control) attribute.name(-array) → HTupleSequence[Union[str, float, int]]HTupleHtuple (integer / string / real) (int / long / string / double) (Hlong / HString / double) (Hlong / char* / double)
Value of the generic parameter.
Result
If the parameters are valid, the operator get_dl_classifier_paramget_dl_classifier_paramGetDlClassifierParamGetDlClassifierParamGetDlClassifierParamget_dl_classifier_param
returns the value 2 (
H_MSG_TRUE)
. If necessary, an exception is raised.
Possible Predecessors
read_dl_classifierread_dl_classifierReadDlClassifierReadDlClassifierReadDlClassifierread_dl_classifier,
set_dl_classifier_paramset_dl_classifier_paramSetDlClassifierParamSetDlClassifierParamSetDlClassifierParamset_dl_classifier_param
Possible Successors
train_dl_classifier_batchtrain_dl_classifier_batchTrainDlClassifierBatchTrainDlClassifierBatchTrainDlClassifierBatchtrain_dl_classifier_batch,
apply_dl_classifierapply_dl_classifierApplyDlClassifierApplyDlClassifierApplyDlClassifierapply_dl_classifier
Alternatives
get_dl_model_paramget_dl_model_paramGetDlModelParamGetDlModelParamGetDlModelParamget_dl_model_param
See also
set_dl_classifier_paramset_dl_classifier_paramSetDlClassifierParamSetDlClassifierParamSetDlClassifierParamset_dl_classifier_param
Module
Deep Learning Inference