diff --git a/CHANGELOG.md b/CHANGELOG.md
index 11d1064a..3779468d 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -9,11 +9,11 @@
   
 ## Changelog
   
-### **HEAD -> main** 2021/09/25 mandic00@live.com
-
-
-### **origin/main** 2021/09/25 mandic00@live.com
+### **HEAD -> main** 2021/09/27 mandic00@live.com
 
+- autodetect number of bodies and hands
+- upload new samples
+- new samples gallery and major code folder restructure
 - new release
 
 ### **2.2.3** 2021/09/24 mandic00@live.com
diff --git a/src/draw.ts b/src/draw.ts
index 5a1e4506..b5fe1edb 100644
--- a/src/draw.ts
+++ b/src/draw.ts
@@ -400,7 +400,7 @@ export async function hand(inCanvas: HTMLCanvasElement | OffscreenCanvas, result
     if (localOptions.drawPoints) {
       if (h.keypoints && h.keypoints.length > 0) {
         for (const pt of h.keypoints) {
-          ctx.fillStyle = localOptions.useDepth ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.5)` : localOptions.color;
+          ctx.fillStyle = localOptions.useDepth ? `rgba(${127.5 + (2 * (pt[2] || 0))}, ${127.5 - (2 * (pt[2] || 0))}, 255, 0.5)` : localOptions.color;
           point(ctx, pt[0], pt[1], 0, localOptions);
         }
       }
diff --git a/src/efficientpose/efficientpose.ts b/src/efficientpose/efficientpose.ts
index b647808c..2f319005 100644
--- a/src/efficientpose/efficientpose.ts
+++ b/src/efficientpose/efficientpose.ts
@@ -6,7 +6,7 @@
 
 import { log, join } from '../util';
 import * as tf from '../../dist/tfjs.esm.js';
-import type { BodyResult } from '../result';
+import type { BodyResult, Box } from '../result';
 import type { GraphModel, Tensor } from '../tfjs/types';
 import type { Config } from '../config';
 import { env } from '../env';
@@ -16,8 +16,8 @@ let model: GraphModel | null;
 type Keypoints = { score: number, part: string, position: [number, number], positionRaw: [number, number] };
 
 const keypoints: Array<Keypoints> = [];
-let box: [number, number, number, number] = [0, 0, 0, 0];
-let boxRaw: [number, number, number, number] = [0, 0, 0, 0];
+let box: Box = [0, 0, 0, 0];
+let boxRaw: Box = [0, 0, 0, 0];
 let score = 0;
 let skipped = Number.MAX_SAFE_INTEGER;
 
diff --git a/src/handpose/handpose.ts b/src/handpose/handpose.ts
index 20e5bed4..262eabd9 100644
--- a/src/handpose/handpose.ts
+++ b/src/handpose/handpose.ts
@@ -9,7 +9,7 @@ import * as tf from '../../dist/tfjs.esm.js';
 import * as handdetector from './handdetector';
 import * as handpipeline from './handpipeline';
 import * as fingerPose from '../fingerpose/fingerpose';
-import type { HandResult } from '../result';
+import type { HandResult, Box, Point } from '../result';
 import type { Tensor, GraphModel } from '../tfjs/types';
 import type { Config } from '../config';
 import { env } from '../env';
@@ -39,10 +39,10 @@ export async function predict(input: Tensor, config: Config): Promise<HandResult
       }
     }
 
-    const keypoints = predictions[i].landmarks as unknown as Array<[number, number, number]>;
+    const keypoints = predictions[i].landmarks as unknown as Array<Point>;
 
-    let box: [number, number, number, number] = [Number.MAX_SAFE_INTEGER, Number.MAX_SAFE_INTEGER, 0, 0]; // maximums so conditionals work
-    let boxRaw: [number, number, number, number] = [0, 0, 0, 0];
+    let box: Box = [Number.MAX_SAFE_INTEGER, Number.MAX_SAFE_INTEGER, 0, 0]; // maximums so conditionals work
+    let boxRaw: Box = [0, 0, 0, 0];
     if (keypoints && keypoints.length > 0) { // if we have landmarks, calculate box based on landmarks
       for (const pt of keypoints) {
         if (pt[0] < box[0]) box[0] = pt[0];
diff --git a/src/handtrack/handtrack.ts b/src/handtrack/handtrack.ts
index 79b1e93f..f45d4d94 100644
--- a/src/handtrack/handtrack.ts
+++ b/src/handtrack/handtrack.ts
@@ -8,7 +8,7 @@
 
 import { log, join, scaleBox } from '../util';
 import * as tf from '../../dist/tfjs.esm.js';
-import type { HandResult } from '../result';
+import type { HandResult, Box } from '../result';
 import type { GraphModel, Tensor } from '../tfjs/types';
 import type { Config } from '../config';
 import { env } from '../env';
@@ -29,10 +29,10 @@ let outputSize: [number, number] = [0, 0];
 type HandDetectResult = {
   id: number,
   score: number,
-  box: [number, number, number, number],
-  boxRaw: [number, number, number, number],
+  box: Box,
+  boxRaw: Box,
   label: string,
-  yxBox: [number, number, number, number],
+  yxBox: Box,
 }
 
 const cache: {
@@ -111,17 +111,17 @@ async function detectHands(input: Tensor, config: Config): Promise<HandDetectRes
     tf.dispose(t.nms);
     for (const res of Array.from(nms)) { // generates results for each class
       const boxSlice = tf.slice(t.boxes, res, 1);
-      let yxBox: [number, number, number, number] = [0, 0, 0, 0];
+      let yxBox: Box = [0, 0, 0, 0];
       if (config.hand.landmarks) { // scale box
-        const detectedBox: [number, number, number, number] = await boxSlice.data();
+        const detectedBox: Box = await boxSlice.data();
         const boxCenter: [number, number] = [(detectedBox[0] + detectedBox[2]) / 2, (detectedBox[1] + detectedBox[3]) / 2];
-        const boxDiff: [number, number, number, number] = [+boxCenter[0] - detectedBox[0], +boxCenter[1] - detectedBox[1], -boxCenter[0] + detectedBox[2], -boxCenter[1] + detectedBox[3]];
+        const boxDiff: Box = [+boxCenter[0] - detectedBox[0], +boxCenter[1] - detectedBox[1], -boxCenter[0] + detectedBox[2], -boxCenter[1] + detectedBox[3]];
         yxBox = [boxCenter[0] - boxScaleFact * boxDiff[0], boxCenter[1] - boxScaleFact * boxDiff[1], boxCenter[0] + boxScaleFact * boxDiff[2], boxCenter[1] + boxScaleFact * boxDiff[3]];
       } else { // use box as-is
         yxBox = await boxSlice.data();
       }
-      const boxRaw: [number, number, number, number] = [yxBox[1], yxBox[0], yxBox[3] - yxBox[1], yxBox[2] - yxBox[0]];
-      const box: [number, number, number, number] = [Math.trunc(boxRaw[0] * outputSize[0]), Math.trunc(boxRaw[1] * outputSize[1]), Math.trunc(boxRaw[2] * outputSize[0]), Math.trunc(boxRaw[3] * outputSize[1])];
+      const boxRaw: Box = [yxBox[1], yxBox[0], yxBox[3] - yxBox[1], yxBox[2] - yxBox[0]];
+      const box: Box = [Math.trunc(boxRaw[0] * outputSize[0]), Math.trunc(boxRaw[1] * outputSize[1]), Math.trunc(boxRaw[2] * outputSize[0]), Math.trunc(boxRaw[3] * outputSize[1])];
       tf.dispose(boxSlice);
       const scoreSlice = tf.slice(classScores[i], res, 1);
       const score = (await scoreSlice.data())[0];
diff --git a/src/human.ts b/src/human.ts
index 17ded9c7..098efe68 100644
--- a/src/human.ts
+++ b/src/human.ts
@@ -37,6 +37,7 @@ export * from './config';
 export * from './result';
 export type { DrawOptions } from './draw';
 export { env, Env } from './env';
+export { Box, Point } from './result';
 export { Models } from './models';
 
 /** Defines all possible input types for **Human** detection
diff --git a/src/interpolate.ts b/src/interpolate.ts
index 43e3586d..4df8bd72 100644
--- a/src/interpolate.ts
+++ b/src/interpolate.ts
@@ -2,7 +2,7 @@
  * Results interpolation for smoothening of video detection results inbetween detected frames
  */
 
-import type { Result, FaceResult, BodyResult, HandResult, ObjectResult, GestureResult, PersonResult } from './result';
+import type { Result, FaceResult, BodyResult, HandResult, ObjectResult, GestureResult, PersonResult, Box, Point } from './result';
 
 const bufferedResult: Result = { face: [], body: [], hand: [], gesture: [], object: [], persons: [], performance: {}, timestamp: 0 };
 
@@ -30,9 +30,9 @@ export function calc(newResult: Result): Result {
   } else {
     for (let i = 0; i < newResult.body.length; i++) {
       const box = newResult.body[i].box // update box
-        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.body[i].box[j] + b) / bufferedFactor) as [number, number, number, number];
+        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.body[i].box[j] + b) / bufferedFactor) as Box;
       const boxRaw = newResult.body[i].boxRaw // update boxRaw
-        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.body[i].boxRaw[j] + b) / bufferedFactor) as [number, number, number, number];
+        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.body[i].boxRaw[j] + b) / bufferedFactor) as Box;
       const keypoints = (newResult.body[i].keypoints // update keypoints
         .map((keypoint, j) => ({
           score: keypoint.score,
@@ -56,13 +56,13 @@ export function calc(newResult: Result): Result {
   } else {
     for (let i = 0; i < newResult.hand.length; i++) {
       const box = (newResult.hand[i].box// update box
-        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.hand[i].box[j] + b) / bufferedFactor)) as [number, number, number, number];
+        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.hand[i].box[j] + b) / bufferedFactor)) as Box;
       const boxRaw = (newResult.hand[i].boxRaw // update boxRaw
-        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.hand[i].boxRaw[j] + b) / bufferedFactor)) as [number, number, number, number];
+        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.hand[i].boxRaw[j] + b) / bufferedFactor)) as Box;
       if (bufferedResult.hand[i].keypoints.length !== newResult.hand[i].keypoints.length) bufferedResult.hand[i].keypoints = newResult.hand[i].keypoints; // reset keypoints as previous frame did not have them
       const keypoints = newResult.hand[i].keypoints && newResult.hand[i].keypoints.length > 0 ? newResult.hand[i].keypoints // update landmarks
         .map((landmark, j) => landmark
-          .map((coord, k) => (((bufferedFactor - 1) * bufferedResult.hand[i].keypoints[j][k] + coord) / bufferedFactor)) as [number, number, number])
+          .map((coord, k) => (((bufferedFactor - 1) * (bufferedResult.hand[i].keypoints[j][k] || 1) + (coord || 0)) / bufferedFactor)) as Point)
         : [];
       const annotations = {};
       if (Object.keys(bufferedResult.hand[i].annotations).length !== Object.keys(newResult.hand[i].annotations).length) bufferedResult.hand[i].annotations = newResult.hand[i].annotations; // reset annotations as previous frame did not have them
@@ -83,9 +83,9 @@ export function calc(newResult: Result): Result {
   } else {
     for (let i = 0; i < newResult.face.length; i++) {
       const box = (newResult.face[i].box // update box
-        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.face[i].box[j] + b) / bufferedFactor)) as [number, number, number, number];
+        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.face[i].box[j] + b) / bufferedFactor)) as Box;
       const boxRaw = (newResult.face[i].boxRaw // update boxRaw
-        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.face[i].boxRaw[j] + b) / bufferedFactor)) as [number, number, number, number];
+        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.face[i].boxRaw[j] + b) / bufferedFactor)) as Box;
       const rotation: {
         matrix: [number, number, number, number, number, number, number, number, number],
         angle: { roll: number, yaw: number, pitch: number },
@@ -112,9 +112,9 @@ export function calc(newResult: Result): Result {
   } else {
     for (let i = 0; i < newResult.object.length; i++) {
       const box = (newResult.object[i].box // update box
-        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.object[i].box[j] + b) / bufferedFactor)) as [number, number, number, number];
+        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.object[i].box[j] + b) / bufferedFactor)) as Box;
       const boxRaw = (newResult.object[i].boxRaw // update boxRaw
-        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.object[i].boxRaw[j] + b) / bufferedFactor)) as [number, number, number, number];
+        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.object[i].boxRaw[j] + b) / bufferedFactor)) as Box;
       bufferedResult.object[i] = { ...newResult.object[i], box, boxRaw }; // shallow clone plus updated values
     }
   }
@@ -127,7 +127,7 @@ export function calc(newResult: Result): Result {
     } else {
       for (let i = 0; i < newPersons.length; i++) { // update person box, we don't update the rest as it's updated as reference anyhow
         bufferedResult.persons[i].box = (newPersons[i].box
-          .map((box, j) => ((bufferedFactor - 1) * bufferedResult.persons[i].box[j] + box) / bufferedFactor)) as [number, number, number, number];
+          .map((box, j) => ((bufferedFactor - 1) * bufferedResult.persons[i].box[j] + box) / bufferedFactor)) as Box;
       }
     }
   }
diff --git a/src/movenet/movenet.ts b/src/movenet/movenet.ts
index 37f37c5f..e29322bd 100644
--- a/src/movenet/movenet.ts
+++ b/src/movenet/movenet.ts
@@ -6,7 +6,7 @@
 
 import { log, join, scaleBox } from '../util';
 import * as tf from '../../dist/tfjs.esm.js';
-import type { BodyResult } from '../result';
+import type { BodyResult, Box } from '../result';
 import type { GraphModel, Tensor } from '../tfjs/types';
 import type { Config } from '../config';
 import { fakeOps } from '../tfjs/backend';
@@ -14,14 +14,11 @@ import { env } from '../env';
 
 let model: GraphModel | null;
 let inputSize = 0;
-const cachedBoxes: Array<[number, number, number, number]> = [];
+const cachedBoxes: Array<Box> = [];
 
 type Keypoints = { score: number, part: string, position: [number, number], positionRaw: [number, number] };
-type Body = { id: number, score: number, box: [number, number, number, number], boxRaw: [number, number, number, number], keypoints: Array<Keypoints> }
+type Body = { id: number, score: number, box: Box, boxRaw: Box, keypoints: Array<Keypoints> }
 
-let box: [number, number, number, number] = [0, 0, 0, 0];
-let boxRaw: [number, number, number, number] = [0, 0, 0, 0];
-let score = 0;
 let skipped = Number.MAX_SAFE_INTEGER;
 const keypoints: Array<Keypoints> = [];
 
@@ -43,6 +40,7 @@ export async function load(config: Config): Promise<GraphModel> {
 async function parseSinglePose(res, config, image, inputBox) {
   const kpt = res[0][0];
   keypoints.length = 0;
+  let score = 0;
   for (let id = 0; id < kpt.length; id++) {
     score = kpt[id][2];
     if (score > config.body.minConfidence) {
@@ -64,7 +62,7 @@ async function parseSinglePose(res, config, image, inputBox) {
   score = keypoints.reduce((prev, curr) => (curr.score > prev ? curr.score : prev), 0);
   const x = keypoints.map((a) => a.position[0]);
   const y = keypoints.map((a) => a.position[1]);
-  box = [
+  const box: Box = [
     Math.min(...x),
     Math.min(...y),
     Math.max(...x) - Math.min(...x),
@@ -72,7 +70,7 @@ async function parseSinglePose(res, config, image, inputBox) {
   ];
   const xRaw = keypoints.map((a) => a.positionRaw[0]);
   const yRaw = keypoints.map((a) => a.positionRaw[1]);
-  boxRaw = [
+  const boxRaw: Box = [
     Math.min(...xRaw),
     Math.min(...yRaw),
     Math.max(...xRaw) - Math.min(...xRaw),
@@ -87,7 +85,7 @@ async function parseMultiPose(res, config, image, inputBox) {
   const bodies: Array<Body> = [];
   for (let id = 0; id < res[0].length; id++) {
     const kpt = res[0][id];
-    score = Math.round(100 * kpt[51 + 4]) / 100;
+    const score = Math.round(100 * kpt[51 + 4]) / 100;
     // eslint-disable-next-line no-continue
     if (score < config.body.minConfidence) continue;
     keypoints.length = 0;
@@ -106,7 +104,7 @@ async function parseMultiPose(res, config, image, inputBox) {
         });
       }
     }
-    boxRaw = [kpt[51 + 1], kpt[51 + 0], kpt[51 + 3] - kpt[51 + 1], kpt[51 + 2] - kpt[51 + 0]];
+    const boxRaw: Box = [kpt[51 + 1], kpt[51 + 0], kpt[51 + 3] - kpt[51 + 1], kpt[51 + 2] - kpt[51 + 0]];
     bodies.push({
       id,
       score,
diff --git a/src/object/centernet.ts b/src/object/centernet.ts
index b3a9355c..d6ab47e4 100644
--- a/src/object/centernet.ts
+++ b/src/object/centernet.ts
@@ -7,7 +7,7 @@
 import { log, join } from '../util';
 import * as tf from '../../dist/tfjs.esm.js';
 import { labels } from './labels';
-import type { ObjectResult } from '../result';
+import type { ObjectResult, Box } from '../result';
 import type { GraphModel, Tensor } from '../tfjs/types';
 import type { Config } from '../config';
 import { env } from '../env';
@@ -60,18 +60,18 @@ async function process(res: Tensor | null, outputShape, config: Config) {
       detections[0][id][0] / inputSize,
       detections[0][id][1] / inputSize,
     ];
-    const boxRaw = [
+    const boxRaw: Box = [
       x,
       y,
       detections[0][id][2] / inputSize - x,
       detections[0][id][3] / inputSize - y,
-    ] as [number, number, number, number];
-    const box = [
+    ];
+    const box: Box = [
       Math.trunc(boxRaw[0] * outputShape[0]),
       Math.trunc(boxRaw[1] * outputShape[1]),
       Math.trunc(boxRaw[2] * outputShape[0]),
       Math.trunc(boxRaw[3] * outputShape[1]),
-    ] as [number, number, number, number];
+    ];
     results.push({ id: i++, score, class: classVal, label, box, boxRaw });
   }
   return results;
diff --git a/src/object/nanodet.ts b/src/object/nanodet.ts
index fd491f9f..bbb0c91a 100644
--- a/src/object/nanodet.ts
+++ b/src/object/nanodet.ts
@@ -7,7 +7,7 @@
 import { log, join } from '../util';
 import * as tf from '../../dist/tfjs.esm.js';
 import { labels } from './labels';
-import type { ObjectResult } from '../result';
+import type { ObjectResult, Box } from '../result';
 import type { GraphModel, Tensor } from '../tfjs/types';
 import type { Config } from '../config';
 import { env } from '../env';
@@ -58,8 +58,8 @@ async function process(res, inputSize, outputShape, config) {
               cx + (scaleBox / strideSize * boxOffset[2]) - x,
               cy + (scaleBox / strideSize * boxOffset[3]) - y,
             ];
-            let boxRaw = [x, y, w, h]; // results normalized to range 0..1
-            boxRaw = boxRaw.map((a) => Math.max(0, Math.min(a, 1))); // fix out-of-bounds coords
+            let boxRaw: Box = [x, y, w, h]; // results normalized to range 0..1
+            boxRaw = boxRaw.map((a) => Math.max(0, Math.min(a, 1))) as Box; // fix out-of-bounds coords
             const box = [ // results normalized to input image pixels
               boxRaw[0] * outputShape[0],
               boxRaw[1] * outputShape[1],
@@ -74,8 +74,8 @@ async function process(res, inputSize, outputShape, config) {
               label: labels[j].label,
               // center: [Math.trunc(outputShape[0] * cx), Math.trunc(outputShape[1] * cy)],
               // centerRaw: [cx, cy],
-              box: (box.map((a) => Math.trunc(a))) as [number, number, number, number],
-              boxRaw: boxRaw as [number, number, number, number],
+              box: box.map((a) => Math.trunc(a)) as Box,
+              boxRaw,
             };
             results.push(result);
           }
diff --git a/src/persons.ts b/src/persons.ts
index edd9755c..2529edd2 100644
--- a/src/persons.ts
+++ b/src/persons.ts
@@ -2,7 +2,7 @@
  * Analyze detection Results and sort&combine them into per-person view
  */
 
-import type { FaceResult, BodyResult, HandResult, GestureResult, PersonResult } from './result';
+import type { FaceResult, BodyResult, HandResult, GestureResult, PersonResult, Box } from './result';
 
 export function join(faces: Array<FaceResult>, bodies: Array<BodyResult>, hands: Array<HandResult>, gestures: Array<GestureResult>, shape: Array<number> | undefined): Array<PersonResult> {
   let id = 0;
@@ -44,7 +44,7 @@ export function join(faces: Array<FaceResult>, bodies: Array<BodyResult>, hands:
     // create new overarching box from all boxes beloning to person
     const x: number[] = [];
     const y: number[] = [];
-    const extractXY = (box: [number, number, number, number] | undefined) => { // extract all [x, y] coordinates from boxes [x, y, width, height]
+    const extractXY = (box: Box | undefined) => { // extract all [x, y] coordinates from boxes [x, y, width, height]
       if (box && box.length === 4) {
         x.push(box[0], box[0] + box[2]);
         y.push(box[1], box[1] + box[3]);
diff --git a/src/posenet/poses.ts b/src/posenet/poses.ts
index fcef4f25..2b8c75a9 100644
--- a/src/posenet/poses.ts
+++ b/src/posenet/poses.ts
@@ -5,6 +5,7 @@
 
 import * as utils from './utils';
 import * as kpt from './keypoints';
+import type { Box } from '../result';
 
 const localMaximumRadius = 1;
 const outputStride = 16;
@@ -125,7 +126,7 @@ function getInstanceScore(existingPoses, keypoints) {
 }
 
 export function decode(offsets, scores, displacementsFwd, displacementsBwd, maxDetected, minConfidence) {
-  const poses: Array<{ keypoints, box: [number, number, number, number], score: number }> = [];
+  const poses: Array<{ keypoints, box: Box, score: number }> = [];
   const queue = buildPartWithScoreQueue(minConfidence, scores);
   // Generate at most maxDetected object instances per image in decreasing root part score order.
   while (poses.length < maxDetected && !queue.empty()) {
diff --git a/src/result.ts b/src/result.ts
index fe0280c0..75babe52 100644
--- a/src/result.ts
+++ b/src/result.ts
@@ -5,6 +5,9 @@
 import type { Tensor } from './tfjs/types';
 import type { FaceGesture, BodyGesture, HandGesture, IrisGesture } from './gesture/gesture';
 
+export type Box = [number, number, number, number];
+export type Point = [number, number, number?];
+
 /** Face results
  * Combined results of face detector, face mesh, age, gender, emotion, embedding, iris models
  * Some values may be null if specific model is not enabled
@@ -37,11 +40,11 @@ export interface FaceResult {
   score: number,
   boxScore: number,
   faceScore: number,
-  box: [number, number, number, number],
-  boxRaw: [number, number, number, number],
-  mesh: Array<[number, number, number]>
-  meshRaw: Array<[number, number, number]>
-  annotations: Record<string, Array<[number, number, number]>>,
+  box: Box,
+  boxRaw: Box,
+  mesh: Array<Point>
+  meshRaw: Array<Point>
+  annotations: Record<string, Point[]>,
   age?: number,
   gender?: string,
   genderScore?: number,
@@ -72,12 +75,12 @@ export interface FaceResult {
 export interface BodyResult {
   id: number,
   score: number,
-  box: [number, number, number, number],
-  boxRaw: [number, number, number, number],
+  box: Box,
+  boxRaw: Box,
   keypoints: Array<{
     part: string,
-    position: [number, number, number?],
-    positionRaw: [number, number, number?],
+    position: Point,
+    positionRaw: Point,
     score: number,
     presence?: number,
   }>
@@ -99,13 +102,13 @@ export interface HandResult {
   score: number,
   boxScore: number,
   fingerScore: number,
-  box: [number, number, number, number],
-  boxRaw: [number, number, number, number],
-  keypoints: Array<[number, number, number]>,
+  box: Box,
+  boxRaw: Box,
+  keypoints: Array<Point>,
   label: string,
   annotations: Record<
     'index' | 'middle' | 'pinky' | 'ring' | 'thumb' | 'palm',
-    Array<[number, number, number]>
+    Array<Point>
   >,
   landmarks: Record<
     'index' | 'middle' | 'pinky' | 'ring' | 'thumb',
@@ -130,8 +133,8 @@ export interface ObjectResult {
   score: number,
   class: number,
   label: string,
-  box: [number, number, number, number],
-  boxRaw: [number, number, number, number],
+  box: Box,
+  boxRaw: Box,
 }
 
 /** Gesture results
@@ -166,8 +169,8 @@ export interface PersonResult {
   body: BodyResult | null,
   hands: { left: HandResult | null, right: HandResult | null },
   gestures: Array<GestureResult>,
-  box: [number, number, number, number],
-  boxRaw?: [number, number, number, number],
+  box: Box,
+  boxRaw?: Box,
 }
 
 /**
diff --git a/src/util.ts b/src/util.ts
index 2a8f22ba..5f845e45 100644
--- a/src/util.ts
+++ b/src/util.ts
@@ -2,6 +2,8 @@
  * Simple helper functions used accross codebase
  */
 
+import type { Box } from './result';
+
 // helper function: join two paths
 export function join(folder: string, file: string): string {
   const separator = folder.endsWith('/') ? '' : '/';
@@ -81,18 +83,18 @@ export function scaleBox(keypoints, boxScaleFact, outputSize) {
     Math.trunc(center[1] - diff),
     Math.trunc(2 * diff),
     Math.trunc(2 * diff),
-  ] as [number, number, number, number];
+  ] as Box;
   const boxRaw = [ // work backwards
     box[0] / outputSize[0],
     box[1] / outputSize[1],
     box[2] / outputSize[0],
     box[3] / outputSize[1],
-  ] as [number, number, number, number];
+  ] as Box;
   const yxBox = [ // work backwards
     boxRaw[1],
     boxRaw[0],
     boxRaw[3] + boxRaw[1],
     boxRaw[2] + boxRaw[0],
-  ] as [number, number, number, number];
+  ] as Box;
   return { box, boxRaw, yxBox };
 }