ppu-yolo-onnx-inference/interface.d.ts

Use your YOLO onnx object detection model in Typescript Bun environment easily.

import type { Tensor } from "onnxruntime-node";
/**
 * Controls verbose output and image dumps for debugging OCR.
 */
export interface DebuggingOptions {
    /**
     * Enable detailed logging of each processing step.
     * @default false
     */
    verbose?: boolean;
    /**
     * Save intermediate image data to disk for inspection.
     * @default false
     */
    debug?: boolean;
    /**
     * Directory where debug images will be written.
     * Relative to the current working directory.
     * @default "out"
     */
    debugFolder?: string;
}
/**
 * Simple rectangle representation.
 */
export interface Box {
    /** X-coordinate of the top-left corner. */
    x: number;
    /** Y-coordinate of the top-left corner. */
    y: number;
    /** Width of the box in pixels. */
    width: number;
    /** Height of the box in pixels. */
    height: number;
}
export interface ModelOptions {
    onnx: ArrayBuffer;
    classNames: string[];
}
export interface ModelThresholds {
    confidence?: number;
    iou?: number;
    classConfidence?: number;
}
export interface ModelMetadata {
    inputShape: [number, number];
    inputTensorName: string;
    outputTensorName: string;
}
export interface YoloDetectionOptions {
    /** File paths to the required Onnx YOLO model and class name list. */
    model: ModelOptions;
    /** Controls threshold for object detection. */
    thresholds?: ModelThresholds;
    /** Controls model input output tensor metadata. */
    modelMetadata?: ModelMetadata;
    /** Controls logging and image dump behavior for debugging. */
    debug?: DebuggingOptions;
}
export interface PreprocessYoloResult {
    tensor: Float32Array;
    modelInputWidth: number;
    modelInputHeight: number;
    originalWidth: number;
    originalHeight: number;
    scaleRatio: number;
}
export interface DetectedObject {
    box: Box;
    className: string;
    classId: number;
    confidence: number;
}
/**
 * The common part of the value metadata type for both tensor and non-tensor values.
 */
export interface ValueMetadataBase {
    /**
     * The name of the specified input or output.
     */
    readonly name: string;
}
/**
 * Represents the metadata of a tensor value.
 */
export interface TensorValueMetadata extends ValueMetadataBase {
    /**
     * Get a value indicating whether the value is a tensor.
     */
    readonly isTensor: true;
    /**
     * Get the data type of the tensor.
     */
    readonly type: Tensor.Type;
    /**
     * Get the shape of the tensor.
     *
     * If the shape is not defined, the value will an empty array. Otherwise, it will be an array representing the shape
     * of the tensor. Each element in the array can be a number or a string. If the element is a number, it represents
     * the corresponding dimension size. If the element is a string, it represents a symbolic dimension.
     */
    readonly shape: ReadonlyArray<number | string>;
}