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 - boolean; indicates whether or not the camera following a valid prediction * seeking - boolean; 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.

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

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[instance_segmentation_prediction, object_detection_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.
  • 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",
    "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>"
}