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Diffstat (limited to 'docs/user_guide/aruco_markers_pipeline/configuration_and_execution.md')
| -rw-r--r-- | docs/user_guide/aruco_markers_pipeline/configuration_and_execution.md | 10 |
1 files changed, 2 insertions, 8 deletions
diff --git a/docs/user_guide/aruco_markers_pipeline/configuration_and_execution.md b/docs/user_guide/aruco_markers_pipeline/configuration_and_execution.md index 329a137..43bb64e 100644 --- a/docs/user_guide/aruco_markers_pipeline/configuration_and_execution.md +++ b/docs/user_guide/aruco_markers_pipeline/configuration_and_execution.md @@ -98,17 +98,11 @@ The usual [ArFrame visualisation parameters](../gaze_analysis_pipeline/visualisa Pass each camera image to [ArUcoCamera.watch](../../argaze.md/#argaze.ArFeatures.ArCamera.watch) method to execute the whole pipeline dedicated to ArUco markers detection, scene pose estimation and 3D AOI projection. ```python -# Assuming that Full HD (1920x1080) video stream or file is opened -... - -# Assuming that the video reading is handled in a looping code block +# Assuming that Full HD (1920x1080) timestamped images are available ...: - # Capture image from video stream of file - image = video_capture.read() - # Detect ArUco markers, estimate scene pose then, project 3D AOI into camera frame - aruco_camera.watch(image) + aruco_camera.watch(timestamp, image) # Display ArUcoCamera frame image to display detected ArUco markers, scene pose, 2D AOI projection and ArFrame visualisation. ... aruco_camera.image() |