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human
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experimental: add efficientpose

pull/293/head
Vladimir Mandic 2021-03-27 15:43:48 -04:00
parent ae9d6caabc
commit 23e515d26f
3 changed files with 25 additions and 16 deletions
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3
CHANGELOG.md
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@ -9,8 +9,9 @@ Repository: **<git+https://github.com/vladmandic/human.git>**
## Changelog ## Changelog
### **HEAD -> main** 2021/03/26 mandic00@live.com ### **HEAD -> main** 2021/03/27 mandic00@live.com
- start working on efficientpose
### **1.2.5** 2021/03/25 mandic00@live.com ### **1.2.5** 2021/03/25 mandic00@live.com

12
demo/browser.js
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@ -3,16 +3,17 @@ import Human from '../src/human';
import Menu from './menu.js'; import Menu from './menu.js';
import GLBench from './gl-bench.js'; import GLBench from './gl-bench.js';
// const userConfig = { backend: 'webgl' }; // add any user configuration overrides const userConfig = { backend: 'webgl' }; // add any user configuration overrides
/*
const userConfig = { const userConfig = {
backend: 'webgl', backend: 'webgl',
async: false, async: false,
profile: false, profile: false,
warmup: 'full', warmup: 'full',
videoOptimized: true, videoOptimized: false,
filter: { enabled: true }, filter: { enabled: true },
face: { enabled: true, face: { enabled: false,
mesh: { enabled: true }, mesh: { enabled: true },
iris: { enabled: true }, iris: { enabled: true },
description: { enabled: true }, description: { enabled: true },
@ -20,9 +21,12 @@ const userConfig = {
}, },
hand: { enabled: false }, hand: { enabled: false },
gesture: { enabled: false }, gesture: { enabled: false },
body: { enabled: false, modelPath: '../models/blazepose.json' }, body: { enabled: false },
// body: { enabled: true, modelPath: '../models/blazepose.json' },
// body: { enabled: true, modelPath: '../models/efficientpose.json' },
object: { enabled: false }, object: { enabled: false },
}; };
*/
const human = new Human(userConfig); const human = new Human(userConfig);

24
src/efficientpose/efficientpose.ts
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@ -3,7 +3,7 @@ import * as tf from '../../dist/tfjs.esm.js';
import * as profile from '../profile'; import * as profile from '../profile';
let model; let model;
let last = { }; let keypoints = { };
let skipped = Number.MAX_SAFE_INTEGER; let skipped = Number.MAX_SAFE_INTEGER;
const bodyParts = ['head', 'neck', 'rightShoulder', 'rightElbow', 'rightWrist', 'chest', 'leftShoulder', 'leftElbow', 'leftWrist', 'pelvis', 'rightHip', 'rightKnee', 'rightAnkle', 'leftHip', 'leftKnee', 'leftAnkle']; const bodyParts = ['head', 'neck', 'rightShoulder', 'rightElbow', 'rightWrist', 'chest', 'leftShoulder', 'leftElbow', 'leftWrist', 'pelvis', 'rightHip', 'rightKnee', 'rightAnkle', 'leftHip', 'leftKnee', 'leftAnkle'];
@ -39,28 +39,31 @@ function max2d(inputs, minScore) {
export async function predict(image, config) { export async function predict(image, config) {
if (!model) return null; if (!model) return null;
if ((skipped < config.body.skipFrames) && config.videoOptimized && Object.keys(last).length > 0) { if ((skipped < config.body.skipFrames) && config.videoOptimized && Object.keys(keypoints).length > 0) {
skipped++; skipped++;
return last; return keypoints;
} }
if (config.videoOptimized) skipped = 0; if (config.videoOptimized) skipped = 0;
else skipped = Number.MAX_SAFE_INTEGER; else skipped = Number.MAX_SAFE_INTEGER;
return new Promise(async (resolve) => { return new Promise(async (resolve) => {
const tensor = tf.tidy(() => {
const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false); const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);
const enhance = tf.mul(resize, [255.0]); const enhance = tf.mul(resize, 2);
tf.dispose(resize); const norm = enhance.sub(1);
return norm;
});
let resT; let resT;
if (!config.profile) { if (!config.profile) {
if (config.body.enabled) resT = await model.predict(enhance); if (config.body.enabled) resT = await model.executeAsync(tensor);
} else { } else {
const profileT = config.body.enabled ? await tf.profile(() => model.predict(enhance)) : {}; const profileT = config.body.enabled ? await tf.profile(() => model.executeAsync(tensor)) : {};
resT = profileT.result.clone(); resT = profileT.result.clone();
profileT.result.dispose(); profileT.result.dispose();
profile.run('body', profileT); profile.run('body', profileT);
} }
enhance.dispose(); tensor.dispose();
if (resT) { if (resT) {
const parts: Array<{ id, score, part, position: { x, y }, positionRaw: { xRaw, yRaw} }> = []; const parts: Array<{ id, score, part, position: { x, y }, positionRaw: { xRaw, yRaw} }> = [];
@ -90,8 +93,9 @@ export async function predict(image, config) {
} }
} }
stack.forEach((s) => tf.dispose(s)); stack.forEach((s) => tf.dispose(s));
last = parts; keypoints = parts;
} }
resolve(last); console.log(keypoints);
resolve([{ keypoints }]);
}); });
} }