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authorThéo de la Hogue2024-01-17 15:17:24 +0100
committerThéo de la Hogue2024-01-17 15:17:24 +0100
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Merge branch 'dev/video_thread'
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.md10
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()