import * as tf from '@tensorflow/tfjs-core' export function nonMaxSuppression( boxes: tf.Tensor2D, scores: number[], maxOutputSize: number, iouThreshold: number, scoreThreshold: number ): number[] { const numBoxes = boxes.shape[0] const outputSize = Math.min( maxOutputSize, numBoxes ) const candidates = scores .map((score, boxIndex) => ({ score, boxIndex })) .filter(c => c.score > scoreThreshold) .sort((c1, c2) => c2.score - c1.score) const suppressFunc = (x: number) => x <= iouThreshold ? 1 : 0 const selected: number[] = [] candidates.forEach(c => { if (selected.length >= outputSize) { return } const originalScore = c.score for (let j = selected.length - 1; j >= 0; --j) { const iou = IOU(boxes, c.boxIndex, selected[j]) if (iou === 0.0) { continue } c.score *= suppressFunc(iou) if (c.score <= scoreThreshold) { break } } if (originalScore === c.score) { selected.push(c.boxIndex) } }) return selected } function IOU(boxes: tf.Tensor2D, i: number, j: number) { const boxesData = boxes.arraySync() const yminI = Math.min(boxesData[i][0], boxesData[i][2]) const xminI = Math.min(boxesData[i][1], boxesData[i][3]) const ymaxI = Math.max(boxesData[i][0], boxesData[i][2]) const xmaxI = Math.max(boxesData[i][1], boxesData[i][3]) const yminJ = Math.min(boxesData[j][0], boxesData[j][2]) const xminJ = Math.min(boxesData[j][1], boxesData[j][3]) const ymaxJ = Math.max(boxesData[j][0], boxesData[j][2]) const xmaxJ = Math.max(boxesData[j][1], boxesData[j][3]) const areaI = (ymaxI - yminI) * (xmaxI - xminI) const areaJ = (ymaxJ - yminJ) * (xmaxJ - xminJ) if (areaI <= 0 || areaJ <= 0) { return 0.0 } const intersectionYmin = Math.max(yminI, yminJ) const intersectionXmin = Math.max(xminI, xminJ) const intersectionYmax = Math.min(ymaxI, ymaxJ) const intersectionXmax = Math.min(xmaxI, xmaxJ) const intersectionArea = Math.max(intersectionYmax - intersectionYmin, 0.0) * Math.max(intersectionXmax - intersectionXmin, 0.0) return intersectionArea / (areaI + areaJ - intersectionArea) }