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Estimate ArUco markers pose
===========================
This **ArGaze** application detects ArUco markers inside a movie frame then, export pose estimation as .obj file into a folder.
Firstly, edit **utils/estimate_markers_pose/context.json** file as to select a movie *path*.
```json
{
"argaze.utils.contexts.OpenCV.Movie" : {
"name": "ArUco markers pose estimator",
"path": "./src/argaze/utils/demo/tobii_record/segments/1/fullstream.mp4",
"pipeline": "pipeline.json"
}
}
```
Sencondly, edit **utils/estimate_markers_pose/pipeline.json** file to setup ArUco camera *size*, ArUco detector *dictionary*, *pose_size* and *pose_ids* attributes.
```json
{
"argaze.ArUcoMarker.ArUcoCamera.ArUcoCamera": {
"name": "Full HD Camera",
"size": [1920, 1080],
"aruco_detector": {
"dictionary": "DICT_APRILTAG_16h5",
"pose_size": 4,
"pose_ids": [],
"parameters": {
"useAruco3Detection": true
},
"observers":{
"observers.ArUcoMarkersPoseRecorder": {
"output_folder": "_export/records/aruco_markers_group"
}
}
},
"sides_mask": 420,
"image_parameters": {
"background_weight": 1,
"draw_gaze_positions": {
"color": [0, 255, 255],
"size": 4
},
"draw_detected_markers": {
"color": [255, 255, 255],
"draw_axes": {
"thickness": 4
}
}
}
}
}
```
Then, launch the application.
```shell
python -m argaze load ./src/argaze/utils/estimate_markers_pose/context.json
```
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