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5856721002
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185
landmarks.js
185
landmarks.js
@ -1,9 +1,9 @@
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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('opencv');
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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 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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@ -25,8 +25,14 @@ class Landmarker {
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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 = this.frontImage.resize(Landmarker.resizedHeight, Landmarker.resizedWidth);
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this.sideImageResized = this.sideImage.resize(Landmarker.resizedHeight, Landmarker.resizedWidth);
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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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@ -36,7 +42,7 @@ class Landmarker {
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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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});
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this.landmarksIndices = [
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@ -51,12 +57,12 @@ class Landmarker {
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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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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 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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@ -66,15 +72,53 @@ class Landmarker {
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}
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parseArgs() {
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const parser = new ArgumentParser();
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parser.add_argument('--front', { dest: 'frontImage', type: 'str', help: 'Front image' });
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parser.add_argument('--side', { dest: 'sideImage', type: 'str', help: 'Side image' });
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parser.add_argument('--poseDetectionConfidence', { dest: 'poseDetectionConfidence', default: 0.5, type: 'float', help: 'Confidence score for pose detection' });
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parser.add_argument('--poseTrackingConfidence', { dest: 'poseTrackingConfidence', default: 0.5, type: 'float', help: 'Confidence score for pose tracking' });
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parser.add_argument('--personHeight', { dest: 'personHeight', type: 'int', help: 'Person height in cm' });
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parser.add_argument('--pixelHeight', { dest: 'pixelHeight', type: 'int', help: 'Pixel height of person' });
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parser.add_argument('--measurement', { dest: 'measurement', nargs: '+', type: 'str', help: 'Type of measurement' });
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parser.add_argument('--yamlFile', { dest: 'yamlFile', type: 'str', help: 'Path to the YAML file containing landmarks' });
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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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@ -90,13 +134,19 @@ class Landmarker {
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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(frontResults, m);
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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(frontResults, m);
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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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@ -110,23 +160,30 @@ class Landmarker {
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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.copy();
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this.frontImageKeypoints = this.frontImageResized.copy();
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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(this.frontImageKeypoints, frontResults[0].landmarks, this.landmarksIndices);
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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(this.sideImageKeypoints, sideResults[0].landmarks, this.landmarksIndices);
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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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sideResults: sideResults[0],
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};
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}
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pixelToMetricRatio() {
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this.pixelHeight = this.pixelDistance * 2;
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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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@ -144,7 +201,7 @@ class Landmarker {
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}
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circle(image, cx, cy) {
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return image.drawCircle(new cv.Point(cx, cy), 2, new cv.Vec(255, 0, 0), -1);
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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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@ -163,7 +220,7 @@ class Landmarker {
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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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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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@ -176,43 +233,57 @@ class Landmarker {
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}
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getCenterTopPoint(sideResults) {
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const grayImage = this.sideImageKeypoints.cvtColor(cv.COLOR_BGR2GRAY);
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const blurredImage = grayImage.gaussianBlur(new cv.Size(5, 5), 0);
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const roi = blurredImage.getRegion(new cv.Rect(0, 0, this.sideImageResized.cols, Math.floor(this.sideImageResized.rows / 2)));
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this.edges = roi.canny(50, 150);
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const contours = this.edges.findContours(cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE);
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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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if (contours.length > 0) {
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const largestContour = contours.sort((a, b) => b.area - a.area)[0];
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this.topmostPoint = largestContour.minBy(pt => pt.y);
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xt = this.topmostPoint.x;
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yt = this.topmostPoint.y;
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this.circle(this.sideImageKeypoints, xt, yt);
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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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let xc, yc;
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if (sideResults.landmarks) {
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const leftHip = sideResults.landmarks[POSE_LANDMARKS.LEFT_HIP];
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const rightHip = sideResults.landmarks[POSE_LANDMARKS.RIGHT_HIP];
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const { x, y } = sideResults.landmarks[POSE_LANDMARKS.NOSE];
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const centerPoint = [
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(leftHip.x + rightHip.x) / 2,
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(leftHip.y + rightHip.y) / 2
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x * Landmarker.resizedWidth,
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y * Landmarker.resizedHeight,
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];
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xc = Math.round(centerPoint[0] * this.sideImageResized.cols);
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yc = Math.round(centerPoint[1] * this.sideImageResized.rows);
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this.circle(this.sideImageKeypoints, xc, yc);
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}
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this.pixelHeight = Math.abs(centerPoint[1] - this.topmostPoint[1]);
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this.pixelDistance = this.euclideanDistance(xt, yt, xc, yc);
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this.pixelDistance *= 2;
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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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(async () => {
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const landmarker = new Landmarker();
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await landmarker.run();
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})();
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landmarker.run().catch((error) => {
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console.error(error);
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});
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@ -189,6 +189,7 @@ class Landmarker:
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tablefmt="plain",
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)
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print(output)
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self.pose.close()
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def process_images(self):
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@ -279,6 +280,7 @@ class Landmarker:
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distance = math.sqrt((x2 - x1) ** 2 + (y2 - y1) ** 2)
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return distance
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def get_center_top_point(self, side_results):
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gray_image = cv2.cvtColor(
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self.side_image_keypoints,
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