import { IDetectionService, DetectionBox, SideAlignment, ClassificationResult } from './interfaces/IDetectionService';
export declare class DetectionService implements IDetectionService {
    private debug;
    private useDocumentClassification;
    private useDocumentDetector;
    private session?;
    private mobileNetSession?;
    private mobileNetClassMap?;
    private modelLoaded;
    private deviceStrategy;
    private readonly MODEL_PATH;
    private readonly MODEL_PATH_FP32;
    private readonly MOBILENET_MODEL_PATH;
    private readonly MOBILENET_CLASSES_PATH;
    private readonly INPUT_SIZE;
    private readonly CONFIDENCE_THRESHOLD;
    private useFloat16;
    private readonly _f32View;
    private readonly _u32View;
    private readonly _tensorF32;
    private readonly _tensorF16;
    private preprocessCanvas?;
    private preprocessCtx?;
    private captureCanvas?;
    private static canvasPool;
    private static readonly MAX_POOL_SIZE;
    constructor(debug?: boolean, useDocumentClassification?: boolean, useDocumentDetector?: boolean);
    loadModel(): Promise<void>;
    loadClassificationModel(): Promise<void>;
    isModelLoaded(): boolean;
    preprocess(video: HTMLVideoElement): any;
    runInference(inputTensor: any): Promise<DetectionBox[]>;
    classifyDocument(canvas: HTMLCanvasElement): Promise<ClassificationResult | null>;
    checkSideAlignment(box: DetectionBox, maskConfig: any): SideAlignment;
    isCardInFrame(box: DetectionBox): boolean;
    areAllSidesAligned(alignment: SideAlignment): boolean;
    cleanup(): void;
    private initializeCanvasPool;
    private cleanupCanvasPool;
    private detectFloat16Support;
    private float32ToFloat16;
    private preprocessMobileNet;
    private getCanvas;
    private returnCanvas;
    static clearCanvasPools(): void;
    getPoolStats(): {
        [key: string]: number;
    };
}