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-rw-r--r--docs/user_guide/aruco_markers_pipeline/advanced_topics/scripting.md4
-rw-r--r--docs/user_guide/aruco_markers_pipeline/aoi_3d_frame.md10
-rw-r--r--docs/user_guide/aruco_markers_pipeline/configuration_and_execution.md10
3 files changed, 6 insertions, 18 deletions
diff --git a/docs/user_guide/aruco_markers_pipeline/advanced_topics/scripting.md b/docs/user_guide/aruco_markers_pipeline/advanced_topics/scripting.md
index 892d6dd..c79c8b5 100644
--- a/docs/user_guide/aruco_markers_pipeline/advanced_topics/scripting.md
+++ b/docs/user_guide/aruco_markers_pipeline/advanced_topics/scripting.md
@@ -75,11 +75,11 @@ for name, aruco_scene in aruco_camera.scenes.items():
[ArUcoCamera.watch](../../../argaze.md/#argaze.ArFeatures.ArCamera.watch) method returns data about pipeline execution.
```python
-# Assuming that images are available
+# Assuming that timestamped images are available
...:
# Watch image with ArUco camera
- detection_time, projection_time, exception = aruco_camera.watch(image)
+ detection_time, projection_time, exception = aruco_camera.watch(timestamp, image)
# Do something with pipeline times
...
diff --git a/docs/user_guide/aruco_markers_pipeline/aoi_3d_frame.md b/docs/user_guide/aruco_markers_pipeline/aoi_3d_frame.md
index 7f60f86..86839c1 100644
--- a/docs/user_guide/aruco_markers_pipeline/aoi_3d_frame.md
+++ b/docs/user_guide/aruco_markers_pipeline/aoi_3d_frame.md
@@ -101,17 +101,11 @@ The names of 3D AOI **and** their related [ArFrames](../../argaze.md/#argaze.ArF
After camera image is passed to [ArUcoCamera.watch](../../argaze.md/#argaze.ArFeatures.ArCamera.watch) method, it is possible to apply a perpective transformation in order to project watched image into each [ArUcoScenes](../../argaze.md/#argaze.ArUcoMarkers.ArUcoScene) [frames background](../../argaze.md/#argaze.ArFeatures.ArFrame) image.
```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)
# Map watched image into ArUcoScenes frames background
aruco_camera.map()
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()