Object Tracking¶

This example showcases the usage of object tracking in Depthai SDK.

For more information about tracker configuration, please refer to config tracker reference.

Note

Visualization in current example is done with blocking behavor. This means that the program will halt at oak.start() until the window is closed. This is done to keep the example simple. For more advanced usage, see Blocking behavior section.

Demo¶

Setup¶

Please run the install script to download all required dependencies. Please note that this script must be ran from git context, so you have to download the depthai repository first and then run the script

git clone https://github.com/luxonis/depthai.git
cd depthai/
python3 install_requirements.py

For additional information, please follow our installation guide.

Pipeline¶

Source Code¶

Also available on GitHub.

from depthai_sdk import OakCamera
import depthai as dai

with OakCamera() as oak:
    color = oak.create_camera('color')
    # List of models that are supported out-of-the-box by the SDK:
    # https://docs.luxonis.com/projects/sdk/en/latest/features/ai_models/#sdk-supported-models
    nn = oak.create_nn('yolov6nr3_coco_640x352', color, tracker=True)

    nn.config_nn(resize_mode='stretch')
    nn.config_tracker(
        tracker_type=dai.TrackerType.ZERO_TERM_COLOR_HISTOGRAM,
        track_labels=[0], # Track only 1st object from the object map. If unspecified, track all object types
        # track_labels=['person'] # Track only people (for coco datasets, person is 1st object in the map)
        assignment_policy=dai.TrackerIdAssignmentPolicy.SMALLEST_ID,
        max_obj=10, # Max objects to track, which can improve performance
        threshold=0.1 # Tracker threshold
    )

    oak.visualize([nn.out.tracker], fps=True)
    oak.visualize(nn.out.passthrough)
    oak.start(blocking=True)

Got questions?

Head over to Discussion Forum for technical support or any other questions you might have.