* range 'blockSize' is now the complete block size (equal for all iterations)
* command lines nodes can use this complete block size to compute the iteration number on software side; delegate range cropping for last iteration to software.
* 'effectiveBlockSize' is still accessible through 'rangeEffectiveBlockSize' parameter
* add 'matchDescription' method on desc.Attribute.
* desc.ListAttribute/desc.GroupAttribute: 'matchDescription' ensure that value perfectly match element/group description. Enable recursive checking for child attributes.
* nodeFactory: detect DescriptionConflicts in pre-process pass by checking that serialized node's attributes perfectly match their descriptions
* CompatibilityNode.attributeDescFromNameAttribute: consider link expressions as valid values
* test_compatibility: more complete description conflicts unit testing
* required for PySide2 > 5.11.1 (and compatible with 5.11.1)
* AttributeItemDelegate: test for list length to determine whether to create a slider component (if range is set to None on Python side, it will be an empty list on the QML/JS side)
* ListAttribute, GroupAttribute: can now be exported on command line
with customizable join character.
* ChoiceParam with non exclusive values are exported on command line as
before but using the new getValueStr()
* node size is an estimation of the number of element to process on a given node, that may be used for parallelization.
* replace the explicit reference to an attribute on a node (Parallelization.inputListParamName)
* size can be:
* dynamic: depends on the size of the node connected to a specific Attribute
* static
* catch error in case the required attribute is not found in preceding nodes
* set an empty list of chunks when this happens
* avoid uncatched exceptions in the middle of an update
* Add chunk notion for parallelization
* Allows Node desc to implement custom updateInternals
* CameraInit node implement a specific updateInternals to update the
input image list
* FeatureExtraction, FeatureMatching, DepthMap, DepthMapFilter:
implement parallelization
Inputs and outputs Attributes are now declared in two separate lists
* no more isOutput field on Attribute description
* guarantee attributes order (was not the case in Python2 with class attributes)
* Attribute's name is now part of its description
Note: for now, input and output Attributes are still stored in a single model inside a Graph.
