SAM3_VideoTrack - ComfyUI Built-in Node Documentation - ComfyUI

Track objects across video frames using SAM3’s memory-based tracker. This node processes a sequence of video frames and maintains object identities across frames, using either initial masks or text prompts to define what to track.

Inputs

Parameter	Description	Data Type	Required	Range
`images`	Video frames as batched images	IMAGE	Yes	Batched video frames
`model`	The SAM3 model to use for tracking	MODEL	Yes	SAM3 model
`initial_mask`	Mask(s) for the first frame to track (one per object)	MASK	No	One mask per object
`conditioning`	Text conditioning for detecting new objects during tracking	CONDITIONING	No	Text conditioning
`detection_threshold`	Score threshold for text-prompted detection (default: 0.5)	FLOAT	No	0.0 to 1.0
`max_objects`	Max tracked objects. Initial masks count toward this limit. 0 uses the internal cap of 64. (default: 4)	INT	No	0 to 64
`detect_interval`	Run detection every N frames (1=every frame). Higher values save compute. (default: 1)	INT	No	1 or higher

Note: Either initial_mask or conditioning must be provided. If both are omitted, the node raises an error.

Outputs

Output Name	Description	Data Type
`track_data`	Tracking data containing object masks and metadata across all video frames	SAM3TrackData

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