* According to Meshroom issue #1179 (https://github.com/alicevision/meshroom/issues/1179),
add the describer type "tag16h5" to the following modules:
- ConvertSfmFormat (e.g., to be able to export the 3D AprilTag positions in a human-readable format as .sfm,
or to see only the AprilTag marker positions in the 3D view via .abc)
- FeatureExtraction (to be able to detect AprilTag markers from the tag16h5 family)
- FeatureMatching (to be able to match AprilTag markers)
- SfmTransform (to be able to use AprilTag markers, e.g., for the auto_from_markers transform)
- StructureFromMotion (to be able to compute the 3D positions of AprilTag markers)
* Added a new input to sfmTransform: markerDistances, which is a pair of marker IDs associated with the distance between them.
Added a corresponding new transform: from_marker_distances, which scales the model according to the given distances between pairs of markers.
Added another transform: auto_from_markers, which uses the existing markers parameter (ignoring their x,y,z positions) and applies the auto_from_... function only based on these given markers. The latter transform can, e.g., be used to align a set of markers with the ground plane.
* Revert "Added a new input to sfmTransform: markerDistances, which is a pair of marker IDs associated with the distance between them."
This reverts commit ed87c68f39.
Co-authored-by: jarne <jarne@ieee.org>
Co-authored-by: Fabien Castan <fabcastan@gmail.com>
* 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
* 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.
