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2fc37ad2dd
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a2108cc7c9
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landmarks.bin
BIN
landmarks.bin
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289
landmarks.js
289
landmarks.js
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const fs = require("fs");
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const path = require("path");
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const { ArgumentParser } = require("argparse");
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const cv = require("@techstark/opencv-js");
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const yaml = require("js-yaml");
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const { Pose, POSE_LANDMARKS } = require("@mediapipe/pose");
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const logging = console;
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const warnings = console;
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class Landmarker {
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static resizedHeight = 256;
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static resizedWidth = 256;
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constructor() {
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this.args = this.parseArgs();
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this.measurements = this.loadLandmarks();
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if (!this.args.frontImage) {
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throw new Error("Front image needs to be passed");
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}
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if (!this.args.sideImage) {
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throw new Error("Side image needs to be passed");
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}
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this.frontImage = cv.imread(this.args.frontImage);
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this.sideImage = cv.imread(this.args.sideImage);
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this.frontImageResized = cv.resize(
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this.frontImage,
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new cv.Size(Landmarker.resizedWidth, Landmarker.resizedHeight),
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);
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this.sideImageResized = cv.resize(
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this.sideImage,
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new cv.Size(Landmarker.resizedWidth, Landmarker.resizedHeight),
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);
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this.distances = {};
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this.personHeight = this.args.personHeight;
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this.pixelHeight = this.args.pixelHeight;
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this.pose = new Pose({
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locateFile: (file) => {
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return `https://cdn.jsdelivr.net/npm/@mediapipe/pose/${file}`;
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},
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});
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this.landmarksIndices = [
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POSE_LANDMARKS.LEFT_SHOULDER,
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POSE_LANDMARKS.RIGHT_SHOULDER,
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POSE_LANDMARKS.LEFT_ELBOW,
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POSE_LANDMARKS.RIGHT_ELBOW,
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POSE_LANDMARKS.LEFT_WRIST,
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POSE_LANDMARKS.RIGHT_WRIST,
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POSE_LANDMARKS.LEFT_HIP,
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POSE_LANDMARKS.RIGHT_HIP,
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POSE_LANDMARKS.LEFT_KNEE,
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POSE_LANDMARKS.RIGHT_KNEE,
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POSE_LANDMARKS.LEFT_ANKLE,
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POSE_LANDMARKS.RIGHT_ANKLE,
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];
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}
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loadLandmarks() {
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const file = fs.readFileSync(this.args.yamlFile, "utf8");
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const landmarksData = yaml.load(file);
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const measurements = {};
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for (const measurement of landmarksData.measurements) {
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measurements[measurement.name] = measurement.landmarks;
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}
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return measurements;
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}
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parseArgs() {
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const parser = new ArgumentParser({
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description: "Process images and calculate measurements",
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});
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parser.add_argument("--front", {
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dest: "frontImage",
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required: true,
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help: "Path to the front image",
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});
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parser.add_argument("--side", {
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dest: "sideImage",
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required: true,
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help: "Path to the side image",
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});
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parser.add_argument("--poseDetectionConfidence", {
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dest: "poseDetectionConfidence",
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default: 0.5,
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type: "float",
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help: "Confidence score for pose detection",
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});
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parser.add_argument("--poseTrackingConfidence", {
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dest: "poseTrackingConfidence",
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default: 0.5,
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type: "float",
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help: "Confidence score for pose tracking",
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});
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parser.add_argument("--personHeight", {
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dest: "personHeight",
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required: true,
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type: "int",
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help: "Person height in cm",
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});
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parser.add_argument("--pixelHeight", {
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dest: "pixelHeight",
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type: "int",
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help: "Pixel height of person",
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});
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parser.add_argument("--measurement", {
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dest: "measurement",
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nargs: "+",
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type: "str",
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help: "Type of measurement",
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});
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parser.add_argument("--yamlFile", {
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dest: "yamlFile",
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required: true,
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help: "Path to the YAML file containing landmarks",
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});
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return parser.parse_args();
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}
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async run() {
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await this.pose.initialize();
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const { frontResults, sideResults } = await this.processImages();
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this.getCenterTopPoint(sideResults);
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const table = [];
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if (this.args.measurement) {
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for (const m of this.args.measurement) {
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if (!this.measurements[m]) {
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throw new Error("Incorrect input (input not present in config.yml)");
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} else {
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const distance = this.calculateDistanceBetweenLandmarks(
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frontResults,
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m,
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);
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table.push([m, distance]);
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}
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}
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} else {
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for (const m in this.measurements) {
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const distance = this.calculateDistanceBetweenLandmarks(
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frontResults,
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m,
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);
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table.push([m, distance]);
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}
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}
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console.table(table);
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this.pose.close();
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}
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async processImages() {
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const frontResults = await this.pose.estimatePoses(this.frontImageResized);
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const sideResults = await this.pose.estimatePoses(this.sideImageResized);
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this.sideImageKeypoints = this.sideImageResized.clone();
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this.frontImageKeypoints = this.frontImageResized.clone();
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if (frontResults[0].landmarks) {
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this.drawLandmarks(
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this.frontImageKeypoints,
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frontResults[0].landmarks,
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this.landmarksIndices,
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);
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}
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if (sideResults[0].landmarks) {
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this.drawLandmarks(
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this.sideImageKeypoints,
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sideResults[0].landmarks,
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this.landmarksIndices,
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);
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}
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return {
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frontResults: frontResults[0],
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sideResults: sideResults[0],
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};
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}
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pixelToMetricRatio() {
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const pixelToMetricRatio = this.personHeight / this.pixelHeight;
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logging.debug("pixelToMetricRatio %s", pixelToMetricRatio);
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return pixelToMetricRatio;
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}
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drawLandmarks(image, landmarks, indices) {
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for (const idx of indices) {
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const landmark = landmarks[idx];
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const h = image.rows;
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const w = image.cols;
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const cx = Math.round(landmark.x * w);
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const cy = Math.round(landmark.y * h);
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this.circle(image, cx, cy);
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}
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}
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circle(image, cx, cy) {
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cv.circle(image, new cv.Point(cx, cy), 2, new cv.Scalar(255, 0, 0), -1);
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}
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calculateDistanceBetweenLandmarks(frontResults, measurementName) {
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if (!frontResults.landmarks) {
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return;
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}
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const landmarks = frontResults.landmarks;
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const landmarkNames = this.measurements[measurementName];
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let totalDistance = 0;
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for (let i = 0; i < landmarkNames.length - 1; i++) {
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const current = landmarks[landmarkNames[i]];
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const next = landmarks[landmarkNames[i + 1]];
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const pixelDistance = this.euclideanDistance(
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current.x * Landmarker.resizedWidth,
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current.y * Landmarker.resizedHeight,
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next.x * Landmarker.resizedWidth,
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next.y * Landmarker.resizedHeight,
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);
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const realDistance = pixelDistance * this.pixelToMetricRatio();
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totalDistance += realDistance;
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}
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return totalDistance;
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}
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euclideanDistance(x1, y1, x2, y2) {
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return Math.sqrt((x2 - x1) ** 2 + (y2 - y1) ** 2);
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}
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getCenterTopPoint(sideResults) {
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const grayImage = cv.cvtColor(this.sideImageKeypoints, cv.COLOR_BGR2GRAY);
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const blurredImage = cv.GaussianBlur(grayImage, new cv.Size(5, 5), 0);
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const roi = blurredImage.roi(
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new cv.Rect(
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0,
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0,
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this.sideImageResized.cols,
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Math.floor(this.sideImageResized.rows / 2),
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),
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);
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this.edges = cv.Canny(roi, 50, 150);
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const contours = this.edges.findContours(
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cv.RETR_EXTERNAL,
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cv.CHAIN_APPROX_SIMPLE,
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);
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let xt, yt;
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this.topmostPoint = null;
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for (const contour of contours) {
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const [xt, yt] = contour.minEnclosingCircle();
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if (this.topmostPoint === null || yt < this.topmostPoint[1]) {
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this.topmostPoint = [xt, yt];
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}
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}
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const { x, y } = sideResults.landmarks[POSE_LANDMARKS.NOSE];
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const centerPoint = [
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x * Landmarker.resizedWidth,
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y * Landmarker.resizedHeight,
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];
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this.pixelHeight = Math.abs(centerPoint[1] - this.topmostPoint[1]);
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cv.circle(
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this.sideImageKeypoints,
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new cv.Point(centerPoint[0], centerPoint[1]),
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2,
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new cv.Scalar(255, 0, 0),
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-1,
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);
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cv.circle(
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this.sideImageKeypoints,
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new cv.Point(this.topmostPoint[0], this.topmostPoint[1]),
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2,
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new cv.Scalar(255, 0, 0),
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-1,
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);
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}
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}
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const landmarker = new Landmarker();
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landmarker.run().catch((error) => {
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console.error(error);
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});
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@ -1,3 +0,0 @@
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[tool.black]
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line-length = 120
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@ -1,4 +0,0 @@
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mediapipe==0.10.13
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tabulate==0.9.0
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opencv-python-headless==4.10.0.84
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pyyaml==6.0.1
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