Comments (3)
I think that there is already a file points.yaml
among the state files that contains the optimized (deformed) pattern point positions, and it should be simple to compute the original point positions from the pattern definition YAML file. See FeatureDetectorTaggedPattern::GetCorners()
and PatternData::IsValidFeatureCoord()
in /applications/camera_calibration/src/camera_calibration/feature_detection/feature_detector_tagged_pattern.cc/h
for how to obtain the feature positions as integers (without scaling). So I think that the required information is already present and relatively easy to access.
from camera_calibration.
Thank you for the information. I tried to add the functionality I'd like to the SavePointsAndIndexMapping
function but FeatureDetectorTaggedPattern::GetCorners is not static and I couldn't figure out where to get an instance from. I ran a debugger with a breakpoint in the contructor of FeatureDetectorTaggedPattern
and it didn't trigger.
Could you give me a rough idea where to start adding the functionality?
I'd also like to get 3D feature points for every image used.
from camera_calibration.
This is where the feature detector is constructed (it is only allocated if needed):
This then builds the map from feature IDs to positions using GetCorners()
(if image directories are given):
It should be possible to use this mapping after this has been called. This map is also saved in the dataset files as the "known geometries":
It could be an option to load them from these files and then associate them with the optimized point positions based on the feature ID. This should not require modifying the camera calibration code.
The features for each image are also saved in the dataset files:
from camera_calibration.
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from camera_calibration.