Script the pipeline

All ArUco marker pipeline objects are accessible from a Python script. This could be particularly useful for real-time AR interaction applications.

Load ArUcoCamera configuration from dictionary

An ArUcoCamera configuration can be loaded from a Python dictionary.

from argaze import DataFeatures
from argaze.ArUcoMarker import ArUcoCamera

# Set working directory to enable relative file path loading 
DataFeatures.set_working_directory('path/to/folder')

# Edit a dict with ArUcoCamera configuration
configuration = {
    "name": "My FullHD camera",
    "size": (1920, 1080),
    ...
    "aruco_detector": {
        ...
    },
    "scenes": {
        "MyScene" : {
             "aruco_markers_group": {
                ...
            },
            "layers": {
                "MyLayer": {
                    "aoi_scene": {
                    ...
                    }
                },
                ...
            }
        },
        ...
    }
    "layers": {
        "MyLayer": {
            ...
        },
        ...
    },
    "image_parameters": {
        ...
    }
}

# Load ArUcoCamera
with ArUcoCamera.ArUcoCamera(**configuration) as aruco_camera:

    # Do something with ArUcoCamera
    ...

Access to ArUcoCamera and ArScenes attributes

Then, once the configuration is loaded, it is possible to access to its attributes: read ArUcoCamera code reference to get a complete list of what is available.

Thus, the ArUcoCamera.scenes attribute allows to access each loaded ArUcoScene and so, access to their attributes: read ArUcoScene code reference to get a complete list of what is available.

from argaze import ArFeatures

# Assuming the ArUcoCamera is loaded
...

    # Iterate over each ArUcoCamera scene
    for name, aruco_scene in aruco_camera.scenes.items():
        ...

Pipeline execution

Detect ArUco markers, estimate scene pose and project 3D AOI

Pass each camera image with timestamp information to the ArUcoCamera.watch method to execute the whole pipeline dedicated to ArUco marker detection, scene pose estimation and 3D AOI projection.

# Assuming that Full HD (1920x1080) images are available with timestamp values
...:

    # Edit timestamped image
    timestamped_image = DataFeatures.TimestampedImage(image, timestamp=timestamp)

    try:

        # Detect ArUco markers, estimate scene pose then, project 3D AOI into camera frame
        aruco_camera.watch(timestamped_image)

    # Do something with pipeline exception
    except Exception as e:

        ...

    # Display ArUcoCamera frame image to display detected ArUco markers, scene pose, 2D AOI projection and ArFrame visualization.
    ... aruco_camera.image()

Detection outputs

The ArUcoCamera.watch method returns data about pipeline execution.

# Assuming that watch method has been called

# Do something with detected_markers
... aruco_camera.aruco_detector.detected_markers()

Let's understand the meaning of each returned data.

aruco_camera.aruco_detector.detected_markers()

A dictionary containing all detected markers is provided by ArUcoDetector class.

Analyse timestamped gaze positions into the camera frame

As mentioned above, ArUcoCamera inherits from ArFrame and, so, benefits from all the services described in the gaze analysis pipeline section.

Particularly, timestamped gaze positions can be passed one by one to the ArUcoCamera.look method to execute the whole pipeline dedicated to gaze analysis.

# Assuming that timestamped gaze positions are available
...

    try:

        # Look ArUcoCamera frame at a timestamped gaze position
        aruco_camera.look(timestamped_gaze_position)

    # Do something with pipeline exception
    except Exception as e:

        ...

Setup ArUcoCamera image parameters

Specific ArUcoCamera.image method parameters can be configured with a Python dictionary.

# Assuming ArUcoCamera is loaded
...

# Edit a dict with ArUcoCamera image parameters
image_parameters = {
    "draw_detected_markers": {
        ...
    },
    "draw_scenes": {
        ...   
    },
    "draw_optic_parameters_grid": {
        ...
    },
    ...
}

# Pass image parameters to ArUcoCamera
aruco_camera_image = aruco_camera.image(**image_parameters)

# Do something with ArUcoCamera image
...

Display ArUcoScene frames

All ArUcoScene frames image can be displayed as any ArFrame.

    ...

    # Display all ArUcoScene frames
    for frame in aruco_camera.scene_frames():

        ... frame.image()