text: /**
   * @license
   * Copyright 2019 Google LLC. All Rights Reserved.
   * Licensed under the Apache License, Version 2.0 (the "License");
   * you may not use this file except in compliance with the License.
   * You may obtain a copy of the License at
   *
   * https://www.apache.org/licenses/LICENSE-2.0
   *
   * Unless required by applicable law or agreed to in writing, software
   * distributed under the License is distributed on an "AS IS" BASIS,
   * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
   * See the License for the specific language governing permissions and
   * limitations under the License.
   * =============================================================================
   */
  import * as posenet from '@tensorflow-models/posenet';
  import * as tf from '@tensorflow/tfjs';
  
  const color = 'aqua';
  const boundingBoxColor = 'red';
  const lineWidth = 2;
  
  export const tryResNetButtonName = 'tryResNetButton';
  export const tryResNetButtonText = '[New] Try ResNet50';
  const tryResNetButtonTextCss = 'width:100%;text-decoration:underline;';
  const tryResNetButtonBackgroundCss = 'background:#e61d5f;';
  
  function isAndroid() {
      return /Android/i.test(navigator.userAgent);
  }
  
  function isiOS() {
      return /iPhone|iPad|iPod/i.test(navigator.userAgent);
  }
  
  export function isMobile() {
      return isAndroid() || isiOS();
  }
  
  function setDatGuiPropertyCss(propertyText, liCssString, spanCssString = '') {
      var spans = document.getElementsByClassName('property-name');
      for (var i = 0; i < spans.length; i++) {
          var text = spans[i].textContent || spans[i].innerText;
          if (text == propertyText) {
              spans[i].parentNode.parentNode.style = liCssString;
              if (spanCssString !== '') {
                  spans[i].style = spanCssString;
              }
          }
      }
  }
  
  export function updateTryResNetButtonDatGuiCss() {
      setDatGuiPropertyCss(
          tryResNetButtonText, tryResNetButtonBackgroundCss,
          tryResNetButtonTextCss);
  }
  
  /**
   * Toggles between the loading UI and the main canvas UI.
   */
  export function toggleLoadingUI(
      showLoadingUI, loadingDivId = 'loading', mainDivId = 'main') {
      if (showLoadingUI) {
          document.getElementById(loadingDivId).style.display = 'block';
          document.getElementById(mainDivId).style.display = 'none';
      } else {
          document.getElementById(loadingDivId).style.display = 'none';
          document.getElementById(mainDivId).style.display = 'block';
      }
  }
  
  function toTuple({
      y,
      x
  }) {
      return [y, x];
  }
  
  export function drawPoint(ctx, y, x, r, color) {
      ctx.beginPath();
      ctx.arc(x, y, r, 0, 2 * Math.PI);
      ctx.fillStyle = color;
      ctx.fill();
  }
  
  /**
   * Draws a line on a canvas, i.e. a joint
   */
  export function drawSegment([ay, ax], [by, bx], color, scale, ctx) {
      ctx.beginPath();
      ctx.moveTo(ax * scale, ay * scale);
      ctx.lineTo(bx * scale, by * scale);
      ctx.lineWidth = lineWidth;
      ctx.strokeStyle = color;
      ctx.stroke();
  }
  
  /**
   * Draws a pose skeleton by looking up all adjacent keypoints/joints
   */
  export function drawSkeleton(keypoints, minConfidence, ctx, scale = 1) {
      const adjacentKeyPoints =
          posenet.getAdjacentKeyPoints(keypoints, minConfidence);
  
      adjacentKeyPoints.forEach((keypoints) => {
          drawSegment(
              toTuple(keypoints[0].position), toTuple(keypoints[1].position), color,
              scale, ctx);
      });
  }
  
  /**
   * Draw pose keypoints onto a canvas
   */
  export function drawKeypoints(keypoints, ctx, scale = 1) {
      for (let i = 0; i < keypoints.length; i++) {
          const keypoint = keypoints[i];
  
  
          const {
              y,
              x
          } = keypoint.position;
          drawPoint(ctx, y * scale, x * scale, 3, color);
      }
  }
  
  /**
   * Draw the bounding box of a pose. For example, for a whole person standing
   * in an image, the bounding box will begin at the nose and extend to one of
   * ankles
   */
  export function drawBoundingBox(keypoints, ctx) {
      const boundingBox = posenet.getBoundingBox(keypoints);
  
      ctx.rect(
          boundingBox.minX, boundingBox.minY, boundingBox.maxX - boundingBox.minX,
          boundingBox.maxY - boundingBox.minY);
  
      ctx.strokeStyle = boundingBoxColor;
      ctx.stroke();
  }
  
  /**
   * Converts an arary of pixel data into an ImageData object
   */
  export async function renderToCanvas(a, ctx) {
      const [height, width] = a.shape;
      const imageData = new ImageData(width, height);
  
      const data = await a.data();
  
      for (let i = 0; i < height * width; ++i) {
          const j = i * 4;
          const k = i * 3;
  
          imageData.data[j + 0] = data[k + 0];
          imageData.data[j + 1] = data[k + 1];
          imageData.data[j + 2] = data[k + 2];
          imageData.data[j + 3] = 255;
      }
  
      ctx.putImageData(imageData, 0, 0);
  }
  
  /**
   * Draw an image on a canvas
   */
  export function renderImageToCanvas(image, size, canvas) {
      canvas.width = size[0];
      canvas.height = size[1];
      const ctx = canvas.getContext('2d');
  
      ctx.drawImage(image, 0, 0);
  }
  
  /**
   * Draw heatmap values, one of the model outputs, on to the canvas
   * Read our blog post for a description of PoseNet's heatmap outputs
   * https://medium.com/tensorflow/real-time-human-pose-estimation-in-the-browser-with-tensorflow-js-7dd0bc881cd5
   */
  export function drawHeatMapValues(heatMapValues, outputStride, canvas) {
      const ctx = canvas.getContext('2d');
      const radius = 5;
      const scaledValues = heatMapValues.mul(tf.scalar(outputStride, 'int32'));
  
      drawPoints(ctx, scaledValues, radius, color);
  }
  
  /**
   * Used by the drawHeatMapValues method to draw heatmap points on to
   * the canvas
   */
  function drawPoints(ctx, points, radius, color) {
      const data = points.buffer().values;
  
      for (let i = 0; i < data.length; i += 2) {
          const pointY = data[i];
          const pointX = data[i + 1];
  
          if (pointX !== 0 && pointY !== 0) {
              ctx.beginPath();
              ctx.arc(pointX, pointY, radius, 0, 2 * Math.PI);
              ctx.fillStyle = color;
              ctx.fill();
          }
      }
  }
  
  /**
   * Draw offset vector values, one of the model outputs, on to the canvas
   * Read our blog post for a description of PoseNet's offset vector outputs
   * https://medium.com/tensorflow/real-time-human-pose-estimation-in-the-browser-with-tensorflow-js-7dd0bc881cd5
   */
  export function drawOffsetVectors(
      heatMapValues, offsets, outputStride, scale = 1, ctx) {
      const offsetPoints =
          posenet.singlePose.getOffsetPoints(heatMapValues, outputStride, offsets);
  
      const heatmapData = heatMapValues.buffer().values;
      const offsetPointsData = offsetPoints.buffer().values;
  
      for (let i = 0; i < heatmapData.length; i += 2) {
          const heatmapY = heatmapData[i] * outputStride;
          const heatmapX = heatmapData[i + 1] * outputStride;
          const offsetPointY = offsetPointsData[i];
          const offsetPointX = offsetPointsData[i + 1];
  
          drawSegment(
              [heatmapY, heatmapX], [offsetPointY, offsetPointX], color, scale, ctx);
      }
  }