|Note: This tutorial assumes that you have completed the previous tutorials: First Steps, Parameters.|
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Visualizing DataDescription: This tutorial introduces some utility scripts for visualizing data from Ensenso cameras.
Tutorial Level: BEGINNER
Next Tutorial: Using the Ensenso Urdf Files
All image topics of the camera node are camera publishers from the image_transport package. In addition to the image, they also publish the camera calibration. This means that you can display them as a camera view in RViz, aligning the image with the point cloud or any other data in the scene.
Textured Point Clouds
The texture_point_cloud node can texture point clouds using data from the rectified camera images. The easiest way of using it is to launch the texture_point_cloud launch file.
$ roslaunch ensenso_camera texture_point_cloud.launch
This launch file bundles a texture_point_cloud node together with an image_stream node that periodically requests rectified images from the camera. Whenever you request a point cloud from the camera node that is published on /point_cloud, the node will automatically texture it and republish the result on /textured_point_cloud.
Visualizing Calibration Patterns
The pattern_marker node periodically captures images and searches for calibration patterns.
$ rosrun ensenso_camera pattern_marker
When it finds patterns, it creates RViz markers at their pose and publishes them on /pattern_marker.
The fit_primitive sample node periodically acquires point clouds and searches for planes via RANSAC algorithm in the scene. It creates a RViz markerArray visualizing the found planes and publishes them under the /primitive_markers topic.
$ rosrun ensenso_camera fit_primitive