import { FaceDetection } from '../classes/FaceDetection';
import { env } from '../env';
import { createCanvas } from './createCanvas';
import { getContext2dOrThrow } from './getContext2dOrThrow';
import { imageTensorToCanvas } from './imageTensorToCanvas';
import { toNetInput } from './toNetInput';
/**
 * Extracts the image regions containing the detected faces.
 *
 * @param input The image that face detection has been performed on.
 * @param detections The face detection results or face bounding boxes for that image.
 * @returns The Canvases of the corresponding image region for each detected face.
 */
export async function extractFaces(input, detections) {
    const { Canvas } = env.getEnv();
    let canvas = input;
    if (!(input instanceof Canvas)) {
        const netInput = await toNetInput(input);
        if (netInput.batchSize > 1) {
            throw new Error('extractFaces - batchSize > 1 not supported');
        }
        const tensorOrCanvas = netInput.getInput(0);
        canvas = tensorOrCanvas instanceof Canvas
            ? tensorOrCanvas
            : await imageTensorToCanvas(tensorOrCanvas);
    }
    const ctx = getContext2dOrThrow(canvas);
    const boxes = detections.map(det => det instanceof FaceDetection
        ? det.forSize(canvas.width, canvas.height).box.floor()
        : det)
        .map(box => box.clipAtImageBorders(canvas.width, canvas.height));
    return boxes.map(({ x, y, width, height }) => {
        const faceImg = createCanvas({ width, height });
        getContext2dOrThrow(faceImg)
            .putImageData(ctx.getImageData(x, y, width, height), 0, 0);
        return faceImg;
    });
}
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