/**
 * YOLOv8n person detector for the MCP-side follow-me loop.
 *
 * Loads a YOLOv8n ONNX model and runs person-only detection on a single JPEG/PNG
 * frame. Image decoded with sharp; inference via onnxruntime-node (CPU).
 *
 * Model lookup order:
 *   1. AGENTICROS_YOLOV8_MODEL env var (absolute path)
 *   2. ~/.agenticros/models/yolov8n.onnx
 * If the file is missing it is downloaded from AGENTICROS_YOLOV8_URL (or a default
 * public mirror). 6 MB, one-time.
 */
export interface PersonDetection {
    /** Bounding box in original image pixel coordinates. */
    x: number;
    y: number;
    width: number;
    height: number;
    /** Center of the bbox (image pixels). */
    cx: number;
    cy: number;
    /** Detection confidence [0,1]. */
    confidence: number;
}
export interface DetectorOptions {
    /** Score threshold for filtering raw detections (default 0.4). */
    scoreThreshold?: number;
    /** IoU threshold for NMS (default 0.5). */
    iouThreshold?: number;
}
export declare class PersonDetector {
    private session;
    private readonly scoreThreshold;
    private readonly iouThreshold;
    constructor(opts?: DetectorOptions);
    load(): Promise<void>;
    /**
     * Detect people in a JPEG/PNG image buffer.
     *
     * Returns bounding boxes in the original image's pixel space.
     */
    detect(image: Buffer | Uint8Array): Promise<{
        width: number;
        height: number;
        persons: PersonDetection[];
    }>;
    /**
     * Detect a single COCO class (0..79) in a JPEG/PNG image buffer.
     * 0=person, 67=cell phone, 56=chair, ... see find-object/coco-classes.ts.
     */
    detectClass(image: Buffer | Uint8Array, classId: number): Promise<{
        width: number;
        height: number;
        detections: PersonDetection[];
    }>;
    dispose(): Promise<void>;
}
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