PTZ Tracking (ONVIF)

Class: ONVIFSinkBlockV1

Source: inference.core.workflows.core_steps.sinks.onvif_movement.v1.ONVIFSinkBlockV1

This ONVIF block allows a workflow to control an ONVIF capable PTZ camera to follow a detected object.

The block returns three values: * predictions: a predictions object containing the single prediction the camera is currently following (can be empty) * seeking: indicates whether or not the camera is currently seeking an object (set asynchronously)

There are two modes:

*Follow: The object it follows is the maximum confidence prediction out of all predictions passed into it. To follow a specific object, use the appropriate filters on the predictiion object to specify the object you want to follow. Additionally if a tracker is used, the camera will follow the tracked object until it disappears. Additionally, zoom can be toggled to get the camera to zoom into a position.

*Move to Preset: The camera can also move to a defined preset position. The camera must support the GotoPreset service.

Note that the tracking block uses the ONVIF continuous movement service. Tracking is adjusted on each successive workflow execution. If workflow execution stops, and the camera is currently moving, the camera will continue moving until it reaches the limits and will no longer be following an object.

Use of a camera with variable speed movement is highly recommended for this block. "Simulate variable speed" can sometimes be used in place of this, but might result in jerky movements and hunting. This setting sends the camera a 100% movement command followed by a stop for a period in order to simulate a percentage speed movement. This can work in some cases, but the success varies depending on the camera's responsiveness.

PID tuning is generally necessary for this block to avoid having the camera overshoot and hunt. Having a significant lag between the camera movement and video (using a lazy buffer consumption strategy) can make tuning extremely difficult. Using an eager buffer consumption strategy is recommended. Increasing the dead zone can also help, but can affect zooming.

Type identifier

Use the following identifier in step "type" field: roboflow_core/onvif_sink@v1to add the block as as step in your workflow.

Properties

Name	Type	Description	Refs
name	str	Enter a unique identifier for this step..	❌
camera_ip	str	Camera IP address or hostname.	✅
camera_port	int	Camera ONVIF port.	✅
camera_username	str	Camera username.	✅
camera_password	str	Camera password.	✅
movement_type	str	Follow object or go to default position preset on execution.	❌
simulate_variable_speed	bool	Simulate variable speed on a lower end camera by using frequent stop commands.	✅
zoom_if_able	bool	Attempt to zoom into an object so it fills the image.	✅
follow_tracker	bool	Lock to the tracking id of the highest confidence prediction until idle or reset. A tracker must be added to the workflow..	✅
dead_zone	int	Camera will stop once bounding box is within this many pixels of FoV center (or border for zoom). Increasing dead zone helps avoid pan/tilt hunting, but decreasing dead zone helps avoid hunting after zoom..	✅
default_position_preset	str	Preset name for default position. This must be a valid camera preset name..	✅
move_to_position_after_idle_seconds	int	Move to the default position after this many seconds of not seeking (0 to disable).	✅
camera_update_rate_limit	int	Minimum number of milliseconds between ONVIF movement updates.	✅
flip_x_movement	bool	Flip X movement if image is mirrored horizontally.	✅
flip_y_movement	bool	Flip Y movement if image is mirrored vertically.	✅
minimum_camera_speed	float	Minimum camera speed as percent (0-1). Some cameras won't honor speeds below a certain amount..	✅
pid_kp	float	PID Kp (proportional) constant. Decrease Kp to reduce hunting at the expense of speed..	✅
pid_ki	float	PID Ki (integral) constant. Use to reduce steady state error, but it can usually be zero..	✅
pid_kd	float	PID Kd (derivative) constant. Increase Kd with lag between video and movement, but excessive Kd can also cause hunting..	✅

The Refs column marks possibility to parametrise the property with dynamic values available in workflow runtime. See Bindings for more info.

Available Connections

Compatible Blocks

Check what blocks you can connect to PTZ Tracking (ONVIF) in version v1.

• inputs: Anthropic Claude, Stitch OCR Detections, Line Counter, Line Counter, LMM For Classification, PTZ Tracking (ONVIF).md), Image Contours, Camera Focus, Google Gemini, Cosine Similarity, VLM as Classifier, Object Detection Model, Dynamic Zone, Byte Tracker, Detections Consensus, Detections Filter, Roboflow Custom Metadata, OCR Model, Object Detection Model, Bounding Rectangle, JSON Parser, Detections Transformation, LMM, YOLO-World Model, Perspective Correction, Moondream2, Florence-2 Model, Template Matching, Velocity, Webhook Sink, Distance Measurement, VLM as Detector, Pixel Color Count, Segment Anything 2 Model, Keypoint Detection Model, Slack Notification, Detections Stabilizer, Byte Tracker, Path Deviation, Multi-Label Classification Model, SIFT Comparison, Overlap Filter, Gaze Detection, VLM as Detector, CSV Formatter, Time in Zone, Instance Segmentation Model, Llama 3.2 Vision, Google Vision OCR, VLM as Classifier, Roboflow Dataset Upload, CogVLM, Byte Tracker, Identify Outliers, Roboflow Dataset Upload, Detection Offset, Single-Label Classification Model, OpenAI, Time in Zone, Email Notification, Local File Sink, OpenAI, Detections Classes Replacement, Detections Merge, OpenAI, Florence-2 Model, Path Deviation, Model Monitoring Inference Aggregator, Twilio SMS Notification, Instance Segmentation Model, SIFT Comparison, Detections Stitch, Identify Changes, Clip Comparison, Dynamic Crop
• outputs: Crop Visualization, Stitch OCR Detections, Line Counter, Line Counter, Blur Visualization, PTZ Tracking (ONVIF).md), Line Counter Visualization, Color Visualization, Mask Visualization, Circle Visualization, Object Detection Model, Multi-Label Classification Model, Dynamic Zone, Keypoint Detection Model, Byte Tracker, Detections Consensus, Detections Filter, Trace Visualization, Roboflow Custom Metadata, Object Detection Model, Detections Transformation, Polygon Zone Visualization, Size Measurement, Halo Visualization, Perspective Correction, Florence-2 Model, Stability AI Inpainting, Template Matching, Velocity, Label Visualization, Webhook Sink, Distance Measurement, Segment Anything 2 Model, Triangle Visualization, Keypoint Detection Model, Background Color Visualization, Slack Notification, Detections Stabilizer, Corner Visualization, Byte Tracker, Path Deviation, Multi-Label Classification Model, Icon Visualization, Overlap Filter, Pixelate Visualization, Gaze Detection, Model Comparison Visualization, Time in Zone, Instance Segmentation Model, Reference Path Visualization, Roboflow Dataset Upload, Byte Tracker, Roboflow Dataset Upload, Detection Offset, Single-Label Classification Model, Classification Label Visualization, Polygon Visualization, Keypoint Visualization, Dot Visualization, Time in Zone, Email Notification, Single-Label Classification Model, Bounding Box Visualization, Detections Classes Replacement, Ellipse Visualization, Detections Merge, Florence-2 Model, Path Deviation, Model Monitoring Inference Aggregator, Twilio SMS Notification, Instance Segmentation Model, SIFT Comparison, Detections Stitch, Dynamic Crop

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds PTZ Tracking (ONVIF) in version v1 has.

Bindings

• input

  • predictions (Union[object_detection_prediction, instance_segmentation_prediction]): Object predictions.
  • camera_ip (string): Camera IP address or hostname.
  • camera_port (integer): Camera ONVIF port.
  • camera_username (string): Camera username.
  • camera_password (secret): Camera password.
  • simulate_variable_speed (boolean): Simulate variable speed on a lower end camera by using frequent stop commands.
  • zoom_if_able (boolean): Attempt to zoom into an object so it fills the image.
  • follow_tracker (boolean): Lock to the tracking id of the highest confidence prediction until idle or reset. A tracker must be added to the workflow..
  • dead_zone (integer): Camera will stop once bounding box is within this many pixels of FoV center (or border for zoom). Increasing dead zone helps avoid pan/tilt hunting, but decreasing dead zone helps avoid hunting after zoom..
  • default_position_preset (string): Preset name for default position. This must be a valid camera preset name..
  • move_to_position_after_idle_seconds (integer): Move to the default position after this many seconds of not seeking (0 to disable).
  • camera_update_rate_limit (integer): Minimum number of milliseconds between ONVIF movement updates.
  • flip_x_movement (boolean): Flip X movement if image is mirrored horizontally.
  • flip_y_movement (boolean): Flip Y movement if image is mirrored vertically.
  • minimum_camera_speed (float_zero_to_one): Minimum camera speed as percent (0-1). Some cameras won't honor speeds below a certain amount..
  • pid_kp (float): PID Kp (proportional) constant. Decrease Kp to reduce hunting at the expense of speed..
  • pid_ki (float): PID Ki (integral) constant. Use to reduce steady state error, but it can usually be zero..
  • pid_kd (float): PID Kd (derivative) constant. Increase Kd with lag between video and movement, but excessive Kd can also cause hunting..

• output

  • predictions (object_detection_prediction): Prediction with detected bounding boxes in form of sv.Detections(...) object.
  • seeking (boolean): Boolean flag.

Example JSON definition of step PTZ Tracking (ONVIF) in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/onvif_sink@v1",
    "predictions": "$steps.object_detection_model.predictions",
    "camera_ip": "<block_does_not_provide_example>",
    "camera_port": "<block_does_not_provide_example>",
    "camera_username": "<block_does_not_provide_example>",
    "camera_password": "<block_does_not_provide_example>",
    "movement_type": "Follow",
    "simulate_variable_speed": true,
    "zoom_if_able": true,
    "follow_tracker": true,
    "dead_zone": 50,
    "default_position_preset": "",
    "move_to_position_after_idle_seconds": "<block_does_not_provide_example>",
    "camera_update_rate_limit": "<block_does_not_provide_example>",
    "flip_x_movement": true,
    "flip_y_movement": true,
    "minimum_camera_speed": "<block_does_not_provide_example>",
    "pid_kp": "<block_does_not_provide_example>",
    "pid_ki": "<block_does_not_provide_example>",
    "pid_kd": "<block_does_not_provide_example>"
}