ambiser
/
human
mirror of https://github.com/vladmandic/human
9
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

update todo

pull/134/head
Vladimir Mandic 2021-04-19 11:36:44 -04:00
parent 13a3a71656
commit 4730e3f542
2 changed files with 53 additions and 27 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

19
TODO.md
View File

@ -2,15 +2,24 @@
## Big Ticket Items ## Big Ticket Items
- N/A N/A
## Exploring Features
- Detect input from uri
- Canvas.js for WASM on NodeJS
## Explore Models ## Explore Models
- InsightFace - InsightFace
RetinaFace detector and ArcFace recognition RetinaFace detector and ArcFace recognition
<https://github.com/deepinsight/insightface> <https://github.com/deepinsight/insightface>
- Blazepose
Needs detector before running pose to center the image
- Efficientpose
Needs detector before running pose to center the image
## Issues ## Soon to be Removed
- box sizing on mobile - MobileFace based embedding
- canvas.js for wasm on node - SSR-Net based age&gender

61
demo/node.js
View File

@ -61,46 +61,63 @@ async function detect(input) {
} }
// decode image using tfjs-node so we don't need external depenencies // decode image using tfjs-node so we don't need external depenencies
// can also be done using canvas.js or some other 3rd party image library
const decoded = human.tf.node.decodeImage(buffer); const decoded = human.tf.node.decodeImage(buffer);
const casted = decoded.toFloat(); const casted = decoded.toFloat();
const image = casted.expandDims(0); const tensor = casted.expandDims(0);
decoded.dispose(); decoded.dispose();
casted.dispose(); casted.dispose();
// image shape contains image dimensions and depth // image shape contains image dimensions and depth
log.state('Processing:', image.shape); log.state('Processing:', tensor.shape);
// run actual detection // run actual detection
const result = await human.detect(image, myConfig); const result = await human.detect(tensor, myConfig);
// no need to print results as they are printed to console during detection from within the library due to human.config.debug set
// dispose image tensor as we no longer need it // dispose image tensor as we no longer need it
image.dispose(); tensor.dispose();
// print data to console // print data to console
log.data('Results:'); log.data('Results:');
for (let i = 0; i < result.face.length; i++) { if (result && result.face && result.face.length > 0) {
const face = result.face[i]; for (let i = 0; i < result.face.length; i++) {
const emotion = face.emotion.reduce((prev, curr) => (prev.score > curr.score ? prev : curr)); const face = result.face[i];
log.data(` Face: #${i} boxConfidence:${face.boxConfidence} faceConfidence:${face.boxConfidence} age:${face.age} genderConfidence:${face.genderConfidence} gender:${face.gender} emotionScore:${emotion.score} emotion:${emotion.emotion} iris:${face.iris}`); const emotion = face.emotion.reduce((prev, curr) => (prev.score > curr.score ? prev : curr));
log.data(` Face: #${i} boxConfidence:${face.boxConfidence} faceConfidence:${face.boxConfidence} age:${face.age} genderConfidence:${face.genderConfidence} gender:${face.gender} emotionScore:${emotion.score} emotion:${emotion.emotion} iris:${face.iris}`);
}
} }
for (let i = 0; i < result.body.length; i++) { if (result && result.body && result.body.length > 0) {
const body = result.body[i]; for (let i = 0; i < result.body.length; i++) {
log.data(` Body: #${i} score:${body.score}`); const body = result.body[i];
log.data(` Body: #${i} score:${body.score}`);
}
} else {
log.data(' Body: N/A');
} }
for (let i = 0; i < result.hand.length; i++) { if (result && result.hand && result.hand.length > 0) {
const hand = result.hand[i]; for (let i = 0; i < result.hand.length; i++) {
log.data(` Hand: #${i} confidence:${hand.confidence}`); const hand = result.hand[i];
log.data(` Hand: #${i} confidence:${hand.confidence}`);
}
} else {
log.data(' Hand: N/A');
} }
for (let i = 0; i < result.gesture.length; i++) { if (result && result.gesture && result.gesture.length > 0) {
const [key, val] = Object.entries(result.gesture[i]); for (let i = 0; i < result.gesture.length; i++) {
log.data(` Gesture: ${key[0]}#${key[1]} gesture:${val[1]}`); const [key, val] = Object.entries(result.gesture[i]);
log.data(` Gesture: ${key[0]}#${key[1]} gesture:${val[1]}`);
}
} else {
log.data(' Gesture: N/A');
} }
for (let i = 0; i < result.object.length; i++) { if (result && result.object && result.object.length > 0) {
const object = result.object[i]; for (let i = 0; i < result.object.length; i++) {
log.data(` Object: #${i} score:${object.score} label:${object.label}`); const object = result.object[i];
log.data(` Object: #${i} score:${object.score} label:${object.label}`);
}
} else {
log.data(' Object: N/A');
} }
result.face.length = 0;
return result; return result;
} }