create_deep_matching_3dT_create_deep_matching_3dCreateDeepMatching3dCreateDeepMatching3dcreate_deep_matching_3d (Operator)
create_deep_matching_3dT_create_deep_matching_3dCreateDeepMatching3dCreateDeepMatching3dcreate_deep_matching_3d — Create a Deep 3D Matching model.
Signature
void CreateDeepMatching3d(const HTuple& ObjectModel3D, const HTuple& Symmetry, const HTuple& GenParamName, const HTuple& GenParamValue, HTuple* Deep3DMatchingModel)
void HDeepMatching3D::HDeepMatching3D(const HObjectModel3D& ObjectModel3D, const HTuple& Symmetry, const HTuple& GenParamName, const HTuple& GenParamValue)
void HDeepMatching3D::HDeepMatching3D(const HObjectModel3D& ObjectModel3D, const HString& Symmetry, const HString& GenParamName, const HString& GenParamValue)
void HDeepMatching3D::HDeepMatching3D(const HObjectModel3D& ObjectModel3D, const char* Symmetry, const char* GenParamName, const char* GenParamValue)
void HDeepMatching3D::HDeepMatching3D(const HObjectModel3D& ObjectModel3D, const wchar_t* Symmetry, const wchar_t* GenParamName, const wchar_t* GenParamValue)
(
Windows only)
void HDeepMatching3D::CreateDeepMatching3d(const HObjectModel3D& ObjectModel3D, const HTuple& Symmetry, const HTuple& GenParamName, const HTuple& GenParamValue)
void HDeepMatching3D::CreateDeepMatching3d(const HObjectModel3D& ObjectModel3D, const HString& Symmetry, const HString& GenParamName, const HString& GenParamValue)
void HDeepMatching3D::CreateDeepMatching3d(const HObjectModel3D& ObjectModel3D, const char* Symmetry, const char* GenParamName, const char* GenParamValue)
void HDeepMatching3D::CreateDeepMatching3d(const HObjectModel3D& ObjectModel3D, const wchar_t* Symmetry, const wchar_t* GenParamName, const wchar_t* GenParamValue)
(
Windows only)
static void HOperatorSet.CreateDeepMatching3d(HTuple objectModel3D, HTuple symmetry, HTuple genParamName, HTuple genParamValue, out HTuple deep3DMatchingModel)
public HDeepMatching3D(HObjectModel3D objectModel3D, HTuple symmetry, HTuple genParamName, HTuple genParamValue)
public HDeepMatching3D(HObjectModel3D objectModel3D, string symmetry, string genParamName, string genParamValue)
void HDeepMatching3D.CreateDeepMatching3d(HObjectModel3D objectModel3D, HTuple symmetry, HTuple genParamName, HTuple genParamValue)
void HDeepMatching3D.CreateDeepMatching3d(HObjectModel3D objectModel3D, string symmetry, string genParamName, string genParamValue)
Description
create_deep_matching_3dcreate_deep_matching_3dCreateDeepMatching3dCreateDeepMatching3dcreate_deep_matching_3d creates a Deep 3D Matching model for
finding the poses of the 3D object model ObjectModel3DObjectModel3DObjectModel3DobjectModel3Dobject_model_3d and returns
its handle in Deep3DMatchingModelDeep3DMatchingModelDeep3DMatchingModeldeep3DMatchingModeldeep_3dmatching_model.
If the 3D object model is symmetric, symmetry information has to be set with the
parameter SymmetrySymmetrySymmetrysymmetrysymmetry. It defines the symmetries of the 3D object model
ObjectModel3DObjectModel3DObjectModel3DobjectModel3Dobject_model_3d in a dictionary. Currently discrete symmetries are supported
and set in the dictionary key 'symmetry_poses'"symmetry_poses""symmetry_poses""symmetry_poses""symmetry_poses" with the value consisting
of HALCON poses (see create_posecreate_poseCreatePoseCreatePosecreate_pose). All poses that keep the model
identical under transformation have to be set, including the identity. By default,
this parameter is set to 'no_symmetry'"no_symmetry""no_symmetry""no_symmetry""no_symmetry" (as a string instead of a dictionary)
which means that no symmetry is active.
Internally create_deep_matching_3dcreate_deep_matching_3dCreateDeepMatching3dCreateDeepMatching3dcreate_deep_matching_3d reads pretrained backbone models and
creates the model components for object detection and 3D pose estimation.
The backbone for
3D pose estimation is filled with the 3D object model ObjectModel3DObjectModel3DObjectModel3DobjectModel3Dobject_model_3d
and possibly its symmetry information for training.
The behavior of the operator can be influenced by setting GenParamNameGenParamNameGenParamNamegenParamNamegen_param_name
to the value passed in GenParamValueGenParamValueGenParamValuegenParamValuegen_param_value:
- 'backbone_name_detector'"backbone_name_detector""backbone_name_detector""backbone_name_detector""backbone_name_detector":
-
Sets the backbone of the deep learning model for object detection.
A list of possible backbones can be found in the documentation of
create_dl_model_detectioncreate_dl_model_detectionCreateDlModelDetectionCreateDlModelDetectioncreate_dl_model_detection.
Default:
'pretrained_dl_classifier_compact.hdl'"pretrained_dl_classifier_compact.hdl""pretrained_dl_classifier_compact.hdl""pretrained_dl_classifier_compact.hdl""pretrained_dl_classifier_compact.hdl".
- 'backbone_name_pose_estimation'"backbone_name_pose_estimation""backbone_name_pose_estimation""backbone_name_pose_estimation""backbone_name_pose_estimation":
-
Sets the backbone of the deep learning model for 3D pose estimation.
HALCON provides pretrained backbones to be used for Deep 3D Matching.
The following pretrained neural networks are provided:
- 'pretrained_dl_3d_pose_estimation_compact.hdl'"pretrained_dl_3d_pose_estimation_compact.hdl""pretrained_dl_3d_pose_estimation_compact.hdl""pretrained_dl_3d_pose_estimation_compact.hdl""pretrained_dl_3d_pose_estimation_compact.hdl":
-
This is a smaller neural network designed for easier tasks and is
more memory and runtime efficient.
This network expects the images to be of the type byte.
Additionally, the network is designed for certain image properties.
The corresponding values can be retrieved with
get_dl_model_paramget_dl_model_paramGetDlModelParamGetDlModelParamget_dl_model_param and listed below:
'image_width'"image_width""image_width""image_width""image_width": 256
'image_height'"image_height""image_height""image_height""image_height": 256
'image_num_channels'"image_num_channels""image_num_channels""image_num_channels""image_num_channels": 3
Restriction:
The network architecture does not allow changes concerning the image dimensions.
- 'pretrained_dl_3d_pose_estimation_enhanced.hdl'"pretrained_dl_3d_pose_estimation_enhanced.hdl""pretrained_dl_3d_pose_estimation_enhanced.hdl""pretrained_dl_3d_pose_estimation_enhanced.hdl""pretrained_dl_3d_pose_estimation_enhanced.hdl":
-
This is a larger neural network designed for more difficult tasks and requires
more memory and runtime.
This network expects the images to be of the type byte.
Additionally, the network is designed for certain image properties.
The corresponding values can be retrieved with
get_dl_model_paramget_dl_model_paramGetDlModelParamGetDlModelParamget_dl_model_param and listed below:
'image_width'"image_width""image_width""image_width""image_width": 256
'image_height'"image_height""image_height""image_height""image_height": 256
'image_num_channels'"image_num_channels""image_num_channels""image_num_channels""image_num_channels": 3
Restriction:
The network architecture does not allow changes concerning the image dimensions.
List of values:
'pretrained_dl_3d_pose_estimation_compact.hdl'"pretrained_dl_3d_pose_estimation_compact.hdl""pretrained_dl_3d_pose_estimation_compact.hdl""pretrained_dl_3d_pose_estimation_compact.hdl""pretrained_dl_3d_pose_estimation_compact.hdl",
'pretrained_dl_3d_pose_estimation_enhanced.hdl'"pretrained_dl_3d_pose_estimation_enhanced.hdl""pretrained_dl_3d_pose_estimation_enhanced.hdl""pretrained_dl_3d_pose_estimation_enhanced.hdl""pretrained_dl_3d_pose_estimation_enhanced.hdl".
Default:
'pretrained_dl_3d_pose_estimation_enhanced.hdl'"pretrained_dl_3d_pose_estimation_enhanced.hdl""pretrained_dl_3d_pose_estimation_enhanced.hdl""pretrained_dl_3d_pose_estimation_enhanced.hdl""pretrained_dl_3d_pose_estimation_enhanced.hdl".
- 'detector_params'"detector_params""detector_params""detector_params""detector_params":
-
Dictionary with parameters used to configure the backbone of the deep
learning model for object detection. A list with the settable parameters
can be found in the documentation of create_dl_model_detectioncreate_dl_model_detectionCreateDlModelDetectionCreateDlModelDetectioncreate_dl_model_detection.
The deep learning models used for Deep 3D Matching can be obtained by
get_deep_matching_3d_paramget_deep_matching_3d_paramGetDeepMatching3dParamGetDeepMatching3dParamget_deep_matching_3d_param and trained using train_dl_model_batchtrain_dl_model_batchTrainDlModelBatchTrainDlModelBatchtrain_dl_model_batch.
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.
This operator returns a handle. Note that the state of an instance of this handle type may be changed by specific operators even though the handle is used as an input parameter by those operators.
Parameters
ObjectModel3DObjectModel3DObjectModel3DobjectModel3Dobject_model_3d (input_control) object_model_3d → HObjectModel3D, HTupleHHandleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)
3D model to search.
SymmetrySymmetrySymmetrysymmetrysymmetry (input_control) attribute.value → HTupleUnion[HHandle, str]HTupleHtuple (string / handle) (string / HHandle) (HString / HHandle) (char* / handle)
Symmetries of the 3D model.
Default:
'no_symmetry'
"no_symmetry"
"no_symmetry"
"no_symmetry"
"no_symmetry"
GenParamNameGenParamNameGenParamNamegenParamNamegen_param_name (input_control) attribute.name(-array) → HTupleMaybeSequence[str]HTupleHtuple (string) (string) (HString) (char*)
Names of parameters.
Default:
[]
Suggested values:
'backbone_name_detector'"backbone_name_detector""backbone_name_detector""backbone_name_detector""backbone_name_detector", 'backbone_name_pose_estimation'"backbone_name_pose_estimation""backbone_name_pose_estimation""backbone_name_pose_estimation""backbone_name_pose_estimation"
GenParamValueGenParamValueGenParamValuegenParamValuegen_param_value (input_control) attribute.value(-array) → HTupleMaybeSequence[Union[str, float, int]]HTupleHtuple (string / real / integer) (string / double / int / long) (HString / double / Hlong) (char* / double / Hlong)
Values of parameters.
Default:
[]
Suggested values:
'pretrained_dl_classifier_compact.hdl'"pretrained_dl_classifier_compact.hdl""pretrained_dl_classifier_compact.hdl""pretrained_dl_classifier_compact.hdl""pretrained_dl_classifier_compact.hdl", 'pretrained_dl_3d_pose_estimation_compact.hdl'"pretrained_dl_3d_pose_estimation_compact.hdl""pretrained_dl_3d_pose_estimation_compact.hdl""pretrained_dl_3d_pose_estimation_compact.hdl""pretrained_dl_3d_pose_estimation_compact.hdl", 'pretrained_dl_3d_pose_estimation_enhanced.hdl'"pretrained_dl_3d_pose_estimation_enhanced.hdl""pretrained_dl_3d_pose_estimation_enhanced.hdl""pretrained_dl_3d_pose_estimation_enhanced.hdl""pretrained_dl_3d_pose_estimation_enhanced.hdl"
Deep3DMatchingModelDeep3DMatchingModelDeep3DMatchingModeldeep3DMatchingModeldeep_3dmatching_model (output_control) deep_matching_3d → HDeepMatching3D, HTupleHHandleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)
Deep 3D Matching model.
Module
3D Metrology