Markers detection
=================

![Detected markers](../../img/detected_markers.png)

Firstly, the ArUco detector needs to know the expected dictionary and size (in centimeter) of the markers it have to detect.

Notice that extra parameters are passed to detector: see [OpenCV ArUco markers detection parameters documentation](https://docs.opencv.org/4.x/d1/dcd/structcv_1_1aruco_1_1DetectorParameters.html) to know more.

``` python
from argaze.ArUcoMarkers import ArUcoDetector, ArUcoCamera

# Assuming camera calibration data are loaded

# Loading extra detector parameters
extra_parameters = ArUcoDetector.DetectorParameters.from_json('./detector_parameters.json')

# Create ArUco detector to track DICT_APRILTAG_16h5 5cm length markers 
aruco_detector = ArUcoDetector.ArUcoDetector(camera=aruco_camera, dictionary='DICT_APRILTAG_16h5', marker_size=5, parameters=extra_parameters)
```

Here is detector parameters JSON file example:

```
{
       "cornerRefinementMethod": 1,
       "aprilTagQuadSigma": 2,
       "aprilTagDeglitch": 1
}
```

The ArUco detector processes frame to detect markers and allows to draw detection results onto it:

``` python
# Detect markers into a frame and draw them
aruco_detector.detect_markers(frame)
aruco_detector.draw_detected_markers(frame)

# Get corners position into frame related to each detected markers
for marker_id, marker in aruco_detector.detected_markers.items():

       print(f'marker {marker_id} corners: ', marker.corners)

       # Do something with detected marker i corners
       ...

```