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Diffstat (limited to 'docs/use_cases/air_controller_gaze_study/introduction.md')
| -rw-r--r-- | docs/use_cases/air_controller_gaze_study/introduction.md | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/docs/use_cases/air_controller_gaze_study/introduction.md b/docs/use_cases/air_controller_gaze_study/introduction.md index 313e492..b7cccbe 100644 --- a/docs/use_cases/air_controller_gaze_study/introduction.md +++ b/docs/use_cases/air_controller_gaze_study/introduction.md @@ -26,14 +26,14 @@ A traffic simulation of moderate difficulty with a maximum of 13 and 16 aircraft The setup to integrate **ArGaze** to the experiment is defined by 3 main files detailled in the next chapters: -* The context file that reads gaze data and scene camera video records: [post_processing_context.json](context.md) +* The context file that playback gaze data and scene camera video records: [data_playback_context.json](context.md) * The pipeline file that processes gaze data and scene camera video: [post_processing_pipeline.json](pipeline.md) * The observers file that exports analysis outputs: [observers.py](observers.md) As any **ArGaze** setup, it is loaded by executing the [*load* command](../../user_guide/utils/main_commands.md): ```shell -python -m argaze load post_processing_context.json +python -m argaze load segment_playback_context.json ``` This command opens one GUI window per frame (one for the scene camera, one for the sector screen and one for the info screen) that allow to monitor gaze mapping while processing. |