import type * as tf_type from '@tensorflow/tfjs';
export type BoundingBox = {
    /** center x of bounding box in px */
    x: number;
    /** center y of bounding box in px */
    y: number;
    /** width of bounding box in px */
    width: number;
    /** height of bounding box in px */
    height: number;
    /** class index with highest confidence */
    class_index: number;
    /** confidence of the class with highest confidence */
    confidence: number;
    /** confidence of all classes */
    all_confidences: number[];
};
/**
 * output shape: [batch, box]
 *
 * Array of batches, each containing array of detected bounding boxes
 * */
export type BoxResult = BoundingBox[][];
export type DecodeBoxArgs = {
    /**
     * tensorflow runtime:
     * - browser: `import * as tf from '@tensorflow/tfjs'`
     * - nodejs: `import * as tf from '@tensorflow/tfjs-node'`
     */
    tf: typeof tf_type;
    /** e.g. `1` for single class */
    num_classes: number;
    /** batched predict result, e.g. 1x84x8400 */
    output: number[][][];
    /**
     * Number of boxes to return using non-max suppression.
     * If not provided, all boxes will be returned
     *
     * e.g. `1` for only selecting the bounding box with highest confidence.
     */
    maxOutputSize?: number;
    /**
     * the threshold for deciding whether boxes overlap too much with respect to IOU.
     *
     * default: `0.5`
     */
    iouThreshold?: number;
    /**
     * the threshold for deciding whether a box is a valid detection.
     *
     * default: `-Infinity`
     */
    scoreThreshold?: number;
};
/**
 * tensorflow output: [batch, features, instances]
 * features:
 * - 4: x, y, width, height
 * - num_classes: class confidence
 *
 * e.g. 1x84x8400 for 1 batch of 8400 instances with 80 classes
 *
 * The confidence are already normalized between 0 to 1.
 */
export declare function decodeBox(args: DecodeBoxArgs): Promise<BoxResult>;
/**
 * Sync version of `decodeBox`.
 */
export declare function decodeBoxSync(args: DecodeBoxArgs): BoxResult;