Key Points Detection

Overview

Key Points Detection node locates user-defined keypoints and their connecting structure in the input frame using a custom-trained model.

Unlike Pose Estimation which targets human body joints, this node works with any keypoint schema defined by the loaded model — for example component pins on a PCB, fasteners on a product, or anatomical landmarks for non-human subjects. Use this node when Pose Estimation's fixed human skeleton does not fit your use case.

Input

Input Image

image required

The image frame to analyze. Connect this to a camera or upstream image output.

Model Directory Path

string required

Path to the keypoint model directory. See Model Directory Path for details.

Confidence Threshold

number required

Minimum confidence score to keep a detected keypoint group. See Confidence Threshold for tuning guidance.

NMS Threshold

number required

Non-Maximum Suppression threshold for overlapping detections. See NMS Threshold for tuning guidance.

Overlay Results

boolean required

Whether to draw keypoint markers and connecting lines on the output frame. See Overlay Results.

Draw Label Text

boolean required

When enabled, draws each keypoint's name next to its marker on the overlay.

Advanced Setting

boolean

Reveals extra framework and architecture fields for non-.nam models. See Advanced Setting.

Output

Overlay Image

image

Output frame from the node. If overlays are enabled, keypoint markers, connecting lines, and optional labels are drawn on this frame.

Detected Count

integer

Number of detected objects (keypoint groups) in the current frame.

Detected Objects

array

Array of keypoint detection objects. Each object contains:

• bbox array: Bounding box [x, y, width, height] around the detected instance.
• keypoints array: Array of keypoint objects, each with x, y, confidence, and optionally a name from the model schema.
• confidence number: Overall detection confidence.