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
```