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implement blazepose and update demos

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Vladimir Mandic 2021-03-04 10:33:08 -05:00
parent 4c20662633
commit efbb152bc5
13 changed files with 135 additions and 177 deletions
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60
README.md
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@ -1,20 +1,23 @@
# Human Library
### 3D Face Detection, Face Embedding & Recognition,
### Body Pose Tracking, Hand & Finger Tracking,
### Iris Analysis, Age & Gender & Emotion Prediction
### & Gesture Recognition
**3D Face Detection, Face Embedding & Recognition,**
**Body Pose Tracking, Hand & Finger Tracking,**
**Iris Analysis, Age & Gender & Emotion Prediction**
**& Gesture Recognition**
<br>
Native JavaScript module using TensorFlow/JS Machine Learning library
Compatible with *Browser*, *WebWorker* and *NodeJS* execution on both Windows and Linux
Compatible with *Browser*, *WebWorker* and *NodeJS* execution on both Windows and Linux
- Browser/WebWorker: Compatible with *CPU*, *WebGL*, *WASM* and *WebGPU* backends
- NodeJS: Compatible with software *tfjs-node* and CUDA accelerated backends *tfjs-node-gpu*
Check out [**Live Demo**](https://vladmandic.github.io/human/demo/index.html) for processing of live WebCam video or static images
<br>
### Project pages:
## Project pages
- [**Live Demo**](https://vladmandic.github.io/human/demo/index.html)
- [**Code Repository**](https://github.com/vladmandic/human)
@ -24,7 +27,7 @@ Compatible with *Browser*, *WebWorker* and *NodeJS* execution on both Windows an
<br>
### Wiki pages:
## Wiki pages
- [**Home**](https://github.com/vladmandic/human/wiki)
- [**Demos**](https://github.com/vladmandic/human/wiki/Demos)
@ -37,7 +40,7 @@ Compatible with *Browser*, *WebWorker* and *NodeJS* execution on both Windows an
<br>
### Additional notes:
## Additional notes
- [**Notes on Backends**](https://github.com/vladmandic/human/wiki/Backends)
- [**Development Server**](https://github.com/vladmandic/human/wiki/Development-Server)
@ -49,13 +52,35 @@ Compatible with *Browser*, *WebWorker* and *NodeJS* execution on both Windows an
<br>
*See [issues](https://github.com/vladmandic/human/issues?q=) and [discussions](https://github.com/vladmandic/human/discussions) for list of known limitations and planned enhancements*
## Default models
Default models in Human library are:
- **Face Detection**: MediaPipe BlazeFace-Back
- **Face Mesh**: MediaPipe FaceMesh
- **Face Iris Analysis**: MediaPipe Iris
- **Emotion Detection**: Oarriaga Emotion
- **Gender Detection**: Oarriaga Gender
- **Age Detection**: SSR-Net Age IMDB
- **Body Analysis**: PoseNet
- **Face Embedding**: Sirius-AI MobileFaceNet Embedding
Note that alternative models are provided and can be enabled via configuration
For example, `PoseNet` model can be switched for `BlazePose` model depending on the use case
For more info, see [**Configuration Details**](https://github.com/vladmandic/human/wiki/Configuration) and [**List of Models**](https://github.com/vladmandic/human/wiki/Models)
<br>
*See [**issues**](https://github.com/vladmandic/human/issues?q=) and [**discussions**](https://github.com/vladmandic/human/discussions) for list of known limitations and planned enhancements*
*Suggestions are welcome!*
<br><hr><br>
## Options ##
## Options
As presented in the demo application...
![Options visible in demo](assets/screenshot-menu.png)
@ -65,12 +90,17 @@ Compatible with *Browser*, *WebWorker* and *NodeJS* execution on both Windows an
<br>
**Training image:**
![Example Training Image](assets/screenshot-sample.png)
**Using static images:**
![Example Using Image](assets/screenshot1.jpg)
![Example Using Image](assets/screenshot-images.jpg)
**Live WebCam view:**
![Example Using WebCam](assets/screenshot-webcam.jpg)
<br>
**Using webcam:**
![Example Using WebCam](assets/screenshot2.jpg)

2
TODO.md
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@ -1,7 +1,5 @@
# To-Do list for Human library
- Explore BlazePose model
- Explore MediaPipe TFLite models
- Fix BlazeFace NodeJS missing ops
- Prune pre-packaged models
- Build Face embedding database

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18
config.js
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@ -105,8 +105,7 @@ export default {
age: {
enabled: true,
modelPath: '../models/age-ssrnet-imdb.json', // can be 'age-ssrnet-imdb' or 'age-ssrnet-wiki'
// which determines training set for model
modelPath: '../models/age-ssrnet-imdb.json',
inputSize: 64, // fixed value
skipFrames: 31, // how many frames to go without re-running the detector
// only used for video inputs
@ -115,7 +114,7 @@ export default {
gender: {
enabled: true,
minConfidence: 0.1, // threshold for discarding a prediction
modelPath: '../models/gender.json', // can be 'gender', 'gender-ssrnet-imdb' or 'gender-ssrnet-wiki'
modelPath: '../models/gender.json', // can be 'gender' or 'gender-ssrnet-imdb'
inputSize: 64, // fixed value
skipFrames: 41, // how many frames to go without re-running the detector
// only used for video inputs
@ -126,7 +125,7 @@ export default {
inputSize: 64, // fixed value
minConfidence: 0.1, // threshold for discarding a prediction
skipFrames: 21, // how many frames to go without re-running the detector
modelPath: '../models/emotion-large.json', // can be 'mini', 'large'
modelPath: '../models/emotion.json',
},
embedding: {
@ -138,16 +137,17 @@ export default {
body: {
enabled: true,
modelPath: '../models/posenet.json',
inputSize: 257, // fixed value
modelPath: '../models/posenet.json', // can be 'posenet' or 'blazepose'
inputSize: 257, // fixed value, 257 for posenet and 256 for blazepose
maxDetections: 10, // maximum number of people detected in the input
// should be set to the minimum number for performance
// only valid for posenet as blazepose only detects single pose
scoreThreshold: 0.5, // threshold for deciding when to remove boxes based on score
// in non-maximum suppression
// only valid for posenet as blazepose only detects single pose
nmsRadius: 20, // radius for deciding points are too close in non-maximum suppression
outputStride: 16, // size of block in which to run point detection, smaller value means higher resolution
// defined by model itself, can be 8, 16, or 32
modelType: 'MobileNet', // Human includes MobileNet version, but you can switch to ResNet
// only valid for posenet as blazepose only detects single pose
modelType: 'posenet-mobilenet', // can be 'posenet-mobilenet', 'posenet-resnet', 'blazepose'
},
hand: {

33
demo/browser.js
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@ -14,10 +14,12 @@ const userConfig = {}; // add any user configuration overrides
const userConfig = {
backend: 'wasm',
async: false,
warmup: 'full',
videoOptimized: false,
face: { enabled: true, iris: { enabled: false }, mesh: { enabled: true }, age: { enabled: true }, gender: { enabled: true }, emotion: { enabled: true }, embedding: { enabled: true } },
body: { enabled: false },
hand: { enabled: false },
face: { enabled: true, iris: { enabled: true }, mesh: { enabled: true }, age: { enabled: true }, gender: { enabled: true }, emotion: { enabled: true }, embedding: { enabled: true } },
hand: { enabled: true },
gestures: { enabled: true },
body: { enabled: true, modelType: 'blazepose', modelPath: '../models/blazepose.json' },
};
*/
@ -31,15 +33,16 @@ const ui = {
baseFontProto: 'small-caps {size} "Segoe UI"',
baseLineWidth: 12,
crop: true,
columns: 4,
columns: 2,
busy: false,
facing: true,
useWorker: false,
worker: 'worker.js',
samples: ['../assets/sample6.jpg', '../assets/sample1.jpg', '../assets/sample4.jpg', '../assets/sample5.jpg', '../assets/sample3.jpg', '../assets/sample2.jpg'],
compare: '../assets/sample-me.jpg',
drawLabels: true,
drawBoxes: true,
drawPoints: false,
drawPoints: true,
drawPolygons: true,
fillPolygons: false,
useDepth: true,
@ -52,6 +55,7 @@ const ui = {
detectFPS: [],
drawFPS: [],
buffered: false,
drawWarmup: false,
drawThread: null,
detectThread: null,
framesDraw: 0,
@ -120,7 +124,7 @@ async function drawResults(input) {
await menu.process.updateChart('FPS', ui.detectFPS);
// get updated canvas
if (ui.buffered || !result.canvas) result.canvas = await human.image(input, userConfig);
if (ui.buffered || !result.canvas) result.canvas = await human.image(input).canvas;
// draw image from video
const ctx = canvas.getContext('2d');
@ -436,6 +440,7 @@ function setupMenu() {
});
menu.display.addHTML('<hr style="border-style: inset; border-color: dimgray">');
menu.display.addBool('use 3D depth', ui, 'useDepth');
menu.display.addBool('print labels', ui, 'drawLabels');
menu.display.addBool('draw boxes', ui, 'drawBoxes');
menu.display.addBool('draw polygons', ui, 'drawPolygons');
menu.display.addBool('Fill Polygons', ui, 'fillPolygons');
@ -530,6 +535,18 @@ function setupMenu() {
document.getElementById('play').addEventListener('click', () => detectVideo());
}
async function drawWarmup(res) {
const canvas = document.getElementById('canvas');
canvas.width = res.canvas.width;
canvas.height = res.canvas.height;
const ctx = canvas.getContext('2d');
ctx.drawImage(res.canvas, 0, 0, res.canvas.width, res.canvas.height, 0, 0, canvas.width, canvas.height);
await draw.face(res.face, canvas, ui, human.facemesh.triangulation);
await draw.body(res.body, canvas, ui);
await draw.hand(res.hand, canvas, ui);
await draw.gesture(res.gesture, canvas, ui);
}
async function main() {
log('Demo starting ...');
log('Browser:', navigator?.userAgent);
@ -543,7 +560,9 @@ async function main() {
}
if (!ui.useWorker) {
status('initializing');
await human.warmup(userConfig); // this is not required, just pre-warms all models for faster initial inference
const res = await human.warmup(userConfig); // this is not required, just pre-warms all models for faster initial inference
ui.baseFont = ui.baseFontProto.replace(/{size}/, '16px');
if (res && res.canvas && ui.drawWarmup) await drawWarmup(res);
}
status('human: ready');
document.getElementById('loader').style.display = 'none';

27
demo/node.js
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@ -14,16 +14,19 @@ const myConfig = {
videoOptimized: false,
async: false,
face: {
// detector: { modelPath: 'file://models/faceboxes.json' },
detector: { modelPath: 'file://models/blazeface-back.json' }, // cannot use blazeface in nodejs due to missing required kernel function in tfjs-node
mesh: { modelPath: 'file://models/facemesh.json' },
iris: { modelPath: 'file://models/iris.json' },
age: { modelPath: 'file://models/age-ssrnet-imdb.json' },
gender: { modelPath: 'file://models/gender.json' },
emotion: { modelPath: 'file://models/emotion-large.json' },
enabled: true,
detector: { modelPath: 'file://models/faceboxes.json', enabled: true, minConfidence: 0.5 },
// detector: { modelPath: 'file://models/blazeface-back.json', enabled: false }, // cannot use blazeface in nodejs due to missing required kernel function in tfjs-node
mesh: { modelPath: 'file://models/facemesh.json', enabled: false }, // depends on blazeface detector
iris: { modelPath: 'file://models/iris.json', enabled: true },
age: { modelPath: 'file://models/age-ssrnet-imdb.json', enabled: true },
gender: { modelPath: 'file://models/gender.json', enabled: true },
emotion: { modelPath: 'file://models/emotion.json', enabled: true },
},
body: { modelPath: 'file://models/posenet.json' },
// body: { modelPath: 'file://models/blazepose.json', modelType: 'blazepose', inputSize: 256, enabled: true },
body: { modelPath: 'file://models/posenet.json', modelType: 'posenet', inputSize: 257, enabled: true },
hand: {
enabled: true,
detector: { modelPath: 'file://models/handdetect.json' },
skeleton: { modelPath: 'file://models/handskeleton.json' },
},
@ -35,7 +38,14 @@ async function init() {
// create instance of human
human = new Human(myConfig);
// pre-load models
log.info('Human:', human.version);
log.info('Active Configuration', human.config);
log.info('TFJS Version:', human.tf.version_core, 'Backend:', tf.getBackend());
log.info('TFJS Flags:', human.tf.env().features);
await human.load();
const loaded = Object.keys(human.models).filter((a) => human.models[a]);
log.info('Loaded:', loaded);
log.info('Memory state:', human.tf.engine().memory());
}
async function detect(input) {
@ -74,6 +84,7 @@ async function test() {
async function main() {
log.info('NodeJS:', process.version);
log.info('Current folder:', process.env.PWD);
await init();
if (process.argv.length !== 3) {
log.warn('Parameters: <input image> missing');

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105
models/emotion-mini.json
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@ -1,105 +0,0 @@
{
"format": "graph-model",
"generatedBy": "2.3.1",
"convertedBy": "TensorFlow.js Converter v2.4.0",
"userDefinedMetadata":
{
"signature":
{
"inputs": {"input_1:0":{"name":"input_1:0","dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"-1"},{"size":"64"},{"size":"64"},{"size":"1"}]}}},
"outputs": {"Identity:0":{"name":"Identity:0","dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"-1"},{"size":"7"}]}}}
}
},
"modelTopology":
{
"node":
[
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2
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"paths": ["emotion-large.bin"],
"paths": ["emotion.bin"],
"weights": [{"name":"unknown_26","shape":[3,3,128,1],"dtype":"float32"},{"name":"unknown_32","shape":[3,3,256,1],"dtype":"float32"},{"name":"unknown_9","shape":[3,3,64,1],"dtype":"float32"},{"name":"unknown_15","shape":[3,3,128,1],"dtype":"float32"},{"name":"unknown_43","shape":[3,3,256,7],"dtype":"float32"},{"name":"unknown_44","shape":[7],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/global_average_pooling2d_1/Mean/reduction_indices","shape":[2],"dtype":"int32"},{"name":"StatefulPartitionedCall/model_1/conv2d_1/Conv2D_weights","shape":[3,3,1,32],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/conv2d_1/Conv2D_bn_offset","shape":[32],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/conv2d_2/Conv2D_weights","shape":[3,3,32,64],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/separable_conv2d_4/separable_conv2d_weights","shape":[1,1,256,256],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/conv2d_2/Conv2D_bn_offset","shape":[64],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/conv2d_3/Conv2D_weights","shape":[1,1,64,128],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/separable_conv2d_4/separable_conv2d_bn_offset","shape":[256],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/conv2d_3/Conv2D_bn_offset","shape":[128],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/separable_conv2d_1/separable_conv2d_weights","shape":[1,1,64,128],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/separable_conv2d_1/separable_conv2d_bn_offset","shape":[128],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/separable_conv2d_2/separable_conv2d_weights","shape":[1,1,128,128],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/separable_conv2d_2/separable_conv2d_bn_offset","shape":[128],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/conv2d_4/Conv2D_weights","shape":[1,1,128,256],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/conv2d_4/Conv2D_bn_offset","shape":[256],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/separable_conv2d_3/separable_conv2d_weights","shape":[1,1,128,256],"dtype":"float32"},{"name":"StatefulPartitionedCall/model_1/separable_conv2d_3/separable_conv2d_bn_offset","shape":[256],"dtype":"float32"}]
}
]

6
package.json
View File

@ -1,6 +1,6 @@
{
"name": "@vladmandic/human",
"version": "0.30.6",
"version": "0.40.0",
"description": "Human: AI-powered 3D Face Detection, Face Embedding & Recognition, Body Pose Tracking, Hand & Finger Tracking, Iris Analysis, Age & Gender & Emotion Prediction & Gesture Recognition",
"sideEffects": false,
"main": "dist/human.node.js",
@ -71,6 +71,8 @@
"age-estimation",
"emotion-detection",
"gender-prediction",
"gesture-recognition"
"gesture-recognition",
"blazeface",
"blazepose"
]
}

57
src/human.ts
View File

@ -9,6 +9,7 @@ import * as emotion from './emotion/emotion';
import * as embedding from './embedding/embedding';
import * as posenet from './posenet/posenet';
import * as handpose from './handpose/handpose';
import * as blazepose from './blazepose/blazepose';
import * as gesture from './gesture/gesture';
import * as image from './image';
import * as profile from './profile';
@ -49,6 +50,7 @@ class Human {
checkSanity: boolean;
firstRun: boolean;
perf: any;
image: any;
models: any;
// models
facemesh: any;
@ -74,18 +76,21 @@ class Human {
this.models = {
facemesh: null,
posenet: null,
blazepose: null,
handpose: null,
iris: null,
age: null,
gender: null,
emotion: null,
};
// export access to image processing
this.image = (input) => image.process(input, this.config);
// export raw access to underlying models
this.facemesh = facemesh;
this.age = age;
this.gender = gender;
this.emotion = emotion;
this.body = posenet;
this.body = this.config.body.modelType.startsWith('posenet') ? posenet : blazepose;
this.hand = handpose;
}
@ -146,16 +151,18 @@ class Human {
this.models.gender,
this.models.emotion,
this.models.embedding,
this.models.posenet,
this.models.handpose,
this.models.posenet,
this.models.blazepose,
] = await Promise.all([
this.models.face || (this.config.face.enabled ? face.load(this.config) : null),
this.models.age || ((this.config.face.enabled && this.config.face.age.enabled) ? age.load(this.config) : null),
this.models.gender || ((this.config.face.enabled && this.config.face.gender.enabled) ? gender.load(this.config) : null),
this.models.emotion || ((this.config.face.enabled && this.config.face.emotion.enabled) ? emotion.load(this.config) : null),
this.models.embedding || ((this.config.face.enabled && this.config.face.embedding.enabled) ? embedding.load(this.config) : null),
this.models.posenet || (this.config.body.enabled ? posenet.load(this.config) : null),
this.models.handpose || (this.config.hand.enabled ? handpose.load(this.config) : null),
this.models.posenet || (this.config.body.enabled && this.config.body.modelType.startsWith('posenet') ? posenet.load(this.config) : null),
this.models.posenet || (this.config.body.enabled && this.config.body.modelType.startsWith('blazepose') ? blazepose.load(this.config) : null),
]);
} else {
if (this.config.face.enabled && !this.models.face) this.models.face = await face.load(this.config);
@ -163,8 +170,9 @@ class Human {
if (this.config.face.enabled && this.config.face.gender.enabled && !this.models.gender) this.models.gender = await gender.load(this.config);
if (this.config.face.enabled && this.config.face.emotion.enabled && !this.models.emotion) this.models.emotion = await emotion.load(this.config);
if (this.config.face.enabled && this.config.face.embedding.enabled && !this.models.embedding) this.models.embedding = await embedding.load(this.config);
if (this.config.body.enabled && !this.models.posenet) this.models.posenet = await posenet.load(this.config);
if (this.config.hand.enabled && !this.models.handpose) this.models.handpose = await handpose.load(this.config);
if (this.config.body.enabled && !this.models.posenet && this.config.body.modelType.startsWith('posenet')) this.models.posenet = await posenet.load(this.config);
if (this.config.body.enabled && !this.models.blazepose && this.config.body.modelType.startsWith('blazepose')) this.models.blazepose = await blazepose.load(this.config);
}
if (this.firstRun) {
@ -346,16 +354,6 @@ class Human {
return faceRes;
}
/*
async processImage(input, userConfig = {}) {
this.state = 'image';
this.config = mergeDeep(this.config, userConfig);
const process = image.process(input, this.config);
process?.tensor?.dispose();
return process?.canvas;
}
*/
// main detect function
async detect(input, userConfig = {}) {
// detection happens inside a promise
@ -374,7 +372,7 @@ class Human {
resolve({ error });
}
let poseRes;
let bodyRes;
let handRes;
let faceRes;
@ -410,15 +408,17 @@ class Human {
this.perf.face = Math.trunc(now() - timeStamp);
}
// run posenet
// run body: can be posenet or blazepose
this.analyze('Start Body:');
if (this.config.async) {
poseRes = this.config.body.enabled ? this.models.posenet?.estimatePoses(process.tensor, this.config) : [];
if (this.config.body.modelType.startsWith('posenet')) bodyRes = this.config.body.enabled ? this.models.posenet?.estimatePoses(process.tensor, this.config) : [];
else bodyRes = this.config.body.enabled ? blazepose.predict(process.tensor, this.config) : [];
if (this.perf.body) delete this.perf.body;
} else {
this.state = 'run:body';
timeStamp = now();
poseRes = this.config.body.enabled ? await this.models.posenet?.estimatePoses(process.tensor, this.config) : [];
if (this.config.body.modelType.startsWith('posenet')) bodyRes = this.config.body.enabled ? await this.models.posenet?.estimatePoses(process.tensor, this.config) : [];
else bodyRes = this.config.body.enabled ? await blazepose.predict(process.tensor, this.config) : [];
this.perf.body = Math.trunc(now() - timeStamp);
}
this.analyze('End Body:');
@ -438,7 +438,7 @@ class Human {
// if async wait for results
if (this.config.async) {
[faceRes, poseRes, handRes] = await Promise.all([faceRes, poseRes, handRes]);
[faceRes, bodyRes, handRes] = await Promise.all([faceRes, bodyRes, handRes]);
}
process.tensor.dispose();
@ -449,14 +449,14 @@ class Human {
if (this.config.gesture.enabled) {
timeStamp = now();
// @ts-ignore
gestureRes = [...gesture.face(faceRes), ...gesture.body(poseRes), ...gesture.hand(handRes), ...gesture.iris(faceRes)];
gestureRes = [...gesture.face(faceRes), ...gesture.body(bodyRes), ...gesture.hand(handRes), ...gesture.iris(faceRes)];
if (!this.config.async) this.perf.gesture = Math.trunc(now() - timeStamp);
else if (this.perf.gesture) delete this.perf.gesture;
}
this.perf.total = Math.trunc(now() - timeStart);
this.state = 'idle';
resolve({ face: faceRes, body: poseRes, hand: handRes, gesture: gestureRes, performance: this.perf, canvas: process.canvas });
resolve({ face: faceRes, body: bodyRes, hand: handRes, gesture: gestureRes, performance: this.perf, canvas: process.canvas });
});
}
@ -487,21 +487,24 @@ class Human {
src = 'data:image/jpeg;base64,' + sample.face;
break;
case 'full':
case 'body':
size = 1200;
src = 'data:image/jpeg;base64,' + sample.body;
break;
default:
src = null;
}
const img = new Image(size, size);
img.onload = () => {
// src = encodeURI('../assets/human-sample-face.jpg');
const img = new Image();
img.onload = async () => {
const canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(size, size) : document.createElement('canvas');
canvas.width = size;
canvas.height = size;
canvas.width = img.naturalWidth;
canvas.height = img.naturalHeight;
const ctx = canvas.getContext('2d');
ctx?.drawImage(img, 0, 0);
const data = ctx?.getImageData(0, 0, size, size);
this.detect(data, this.config).then((res) => resolve(res));
// const data = ctx?.getImageData(0, 0, canvas.height, canvas.width);
const res = await this.detect(canvas, this.config);
resolve(res);
};
if (src) img.src = src;
else resolve(null);

2
wiki

@ -1 +1 @@
Subproject commit 55e854ea9263ca0eae7ffbb7d60b87e1ca3a7065
Subproject commit c60f442714b1b5887ae25feb35fa413bc9996402