SAM3 Detect Node

Overview

The SAM3 Detect node performs open-vocabulary detection and segmentation using text descriptions, bounding boxes, or point prompts. It can identify and segment objects in an image based on what you describe in text, where you draw boxes, or where you click points.

Inputs

Parameter	Description	Data Type	Required	Range
`model`	The SAM3 model to use for detection and segmentation	MODEL	Yes	-
`image`	The input image to process	IMAGE	Yes	-
`conditioning`	Text conditioning from CLIPTextEncode. Required when using text prompts for detection	CONDITIONING	No	-
`bboxes`	Bounding boxes to segment within. Can be a single box (applied to all frames), a list of boxes (applied to all frames), or a list of lists (per-frame boxes). When provided without text conditioning, the node segments inside each box	BOUNDING_BOX	No	-
`positive_coords`	Positive point prompts as JSON format `[{"x": int, "y": int}, ...]` using pixel coordinates. These are points you want to include in the segmentation	STRING	No	-
`negative_coords`	Negative point prompts as JSON format `[{"x": int, "y": int}, ...]` using pixel coordinates. These are points you want to exclude from the segmentation	STRING	No	-
`threshold`	Confidence threshold for text-based detections. Only detections with scores above this value are kept (default: 0.5)	FLOAT	No	0.0 to 1.0
`refine_iterations`	Number of SAM decoder refinement passes. Higher values can improve mask quality. Set to 0 to use raw detector masks without refinement (default: 2)	INT	No	0 to 5
`individual_masks`	When enabled, outputs separate masks for each detected object instead of combining them into a single mask (default: False)	BOOLEAN	No	True/False

Parameter Constraints and Notes

Text prompts: To use text-based detection, you must provide conditioning input. When text conditioning is provided, the node runs text-guided detection on the image.
Box prompts: When bboxes are provided without text conditioning, the node segments the area inside each bounding box.
Point prompts: When positive_coords or negative_coords are provided, the node uses point-based segmentation. Points are scaled to the model’s internal resolution automatically.
Multiple prompt types: You can combine different prompt types. For example, you can provide both text conditioning and bounding boxes to restrict text detection to specific areas.
Batch processing: The node supports batched images. When processing multiple frames, bounding boxes can be provided per-frame using a list of lists format.
JSON format for points: Point coordinates must be provided as valid JSON strings in the format [{"x": 100, "y": 200}, {"x": 150, "y": 250}].

Outputs

Output Name	Description	Data Type
`masks`	Segmentation masks. When `individual_masks` is False (default), returns a single combined mask per frame. When True, returns individual masks for each detected object	MASK
`bboxes`	Detected bounding boxes with coordinates and confidence scores. Each box includes `x`, `y`, `width`, `height`, and `score` values	BOUNDING_BOX

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Nodes

SAM3_Detect - ComfyUI Built-in Node Documentation

SAM3 Detect Node

Overview

Inputs

Parameter Constraints and Notes

Outputs

​SAM3 Detect Node

​Overview

​Inputs

​Parameter Constraints and Notes

​Outputs

SAM3 Detect Node

Overview

Inputs

Parameter Constraints and Notes

Outputs