mirror of https://github.com/vladmandic/human
implemented face and hand boundary checks
Vladimir Mandic
parent
3197c1cfee
commit
a0aa1bd8da
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@ -132,7 +132,7 @@ export default {
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inputSize: 257, // fixed value
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maxDetections: 10, // maximum number of people detected in the input
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// should be set to the minimum number for performance
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scoreThreshold: 0.8, // threshold for deciding when to remove boxes based on score
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scoreThreshold: 0.5, // threshold for deciding when to remove boxes based on score
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// in non-maximum suppression
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nmsRadius: 20, // radius for deciding points are too close in non-maximum suppression
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},
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@ -37,8 +37,6 @@ async function detect(input) {
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const decoded = human.tf.node.decodeImage(buffer);
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const casted = decoded.toFloat();
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const image = casted.expandDims(0);
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// console.log(image.arraySync());
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fs.writeFileSync('q.json', JSON.stringify(image.arraySync()));
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decoded.dispose();
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casted.dispose();
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// image shape contains image dimensions and depth
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@ -1,7 +1,7 @@
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{
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"inputs": {
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"dist/human.esm.js": {
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"bytes": 1786858,
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"imports": []
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},
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"demo/draw.js": {
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@ -38,17 +38,17 @@
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"dist/demo-browser-index.js.map": {
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},
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"dist/demo-browser-index.js": {
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"imports": [],
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"exports": [],
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"inputs": {
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@ -9,7 +9,7 @@
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"imports": []
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},
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"src/face/blazeface.js": {
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"bytes": 6993,
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"bytes": 6986,
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"imports": [
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{
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"path": "src/log.js"
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@ -53,7 +53,7 @@
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]
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},
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"src/face/facemesh.js": {
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"bytes": 2675,
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"imports": [
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"path": "src/log.js"
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]
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},
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"src/age/age.js": {
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"bytes": 1950,
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"imports": [
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{
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"path": "src/log.js"
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]
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},
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"src/gender/gender.js": {
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"bytes": 3391,
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"imports": [
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{
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"path": "src/log.js"
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]
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},
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"src/emotion/emotion.js": {
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"bytes": 2988,
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"imports": [
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{
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"path": "src/log.js"
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]
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},
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"src/embedding/embedding.js": {
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"bytes": 2048,
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"imports": [
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{
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"path": "src/log.js"
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@ -180,7 +180,7 @@
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]
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},
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"src/body/decodePose.js": {
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"bytes": 4540,
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"imports": [
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{
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"path": "src/body/keypoints.js"
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]
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},
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"src/body/decodeMultiple.js": {
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"bytes": 5605,
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"imports": [
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{
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"path": "src/body/buildParts.js"
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]
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},
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"src/body/modelPoseNet.js": {
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"path": "src/log.js"
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"imports": []
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"src/hand/handpose.js": {
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"imports": [
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{
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"path": "src/log.js"
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"imports": []
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},
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"src/sample.js": {
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"imports": []
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},
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"src/human.js": {
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"bytes": 16319,
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"imports": [
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{
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"path": "src/log.js"
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@ -402,7 +402,7 @@
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"dist/human.esm.js.map": {
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"imports": [],
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"inputs": {},
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"bytes": 2597262
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"dist/human.esm.js": {
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"imports": [],
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@ -411,7 +411,7 @@
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],
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"inputs": {
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"src/face/blazeface.js": {
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"bytesInOutput": 5113
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},
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"src/face/box.js": {
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@ -423,25 +423,25 @@
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"bytesInOutput": 30817
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"bytesInOutput": 9403
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"src/gender/gender.js": {
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"src/body/modelBase.js": {
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@ -465,28 +465,28 @@
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},
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"src/body/posenet.js": {
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"bytesInOutput": 2741
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"src/hand/anchors.js": {
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"src/hand/handpose.js": {
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"bytesInOutput": 1898
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"src/gesture/gesture.js": {
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@ -495,16 +495,16 @@
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"bytesInOutput": 13576
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"src/image.js": {
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"bytesInOutput": 4041
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},
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"src/log.js": {
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"dist/tfjs.esm.js": {
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"bytesInOutput": 1520559
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"src/human.js": {
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},
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"src/hand/box.js": {
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"config.js": {
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"imports": []
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},
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"src/face/blazeface.js": {
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"bytes": 6993,
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"imports": [
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{
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"path": "src/log.js"
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]
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},
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"src/face/facemesh.js": {
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"bytes": 2675,
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"imports": [
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{
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"path": "src/log.js"
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},
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"src/age/age.js": {
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"bytes": 1950,
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"imports": [
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{
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"path": "src/log.js"
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]
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},
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"src/gender/gender.js": {
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"bytes": 3391,
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"imports": [
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{
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},
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"src/emotion/emotion.js": {
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"bytes": 2988,
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"imports": [
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{
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"path": "src/log.js"
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]
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},
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"src/embedding/embedding.js": {
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"bytes": 2048,
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"imports": [
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]
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},
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"src/body/decodePose.js": {
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"bytes": 4540,
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"imports": [
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{
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"path": "src/body/keypoints.js"
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]
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},
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"src/body/decodeMultiple.js": {
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"bytes": 5605,
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"imports": [
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{
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"path": "src/body/buildParts.js"
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]
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},
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"src/body/modelPoseNet.js": {
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"bytes": 1912,
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"imports": [
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{
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"path": "src/log.js"
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"imports": []
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},
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"src/hand/handpose.js": {
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"bytes": 3122,
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"imports": [
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{
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"path": "src/log.js"
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"imports": []
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},
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"src/sample.js": {
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"imports": []
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},
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{
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"path": "src/log.js"
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"dist/human.js.map": {
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"imports": [],
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"inputs": {},
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},
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},
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"src/hand/handpose.js": {
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},
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||||
},
|
||||
"config.js": {
|
||||
"bytesInOutput": 1352
|
||||
"bytesInOutput": 1428
|
||||
},
|
||||
"src/sample.js": {
|
||||
"bytesInOutput": 11646
|
||||
|
|
@ -520,7 +520,7 @@
|
|||
"bytesInOutput": 21
|
||||
}
|
||||
},
|
||||
"bytes": 1786932
|
||||
"bytes": 1786768
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -9,7 +9,7 @@ let frame = Number.MAX_SAFE_INTEGER;
|
|||
async function load(config) {
|
||||
if (!models.age) {
|
||||
models.age = await tf.loadGraphModel(config.face.age.modelPath);
|
||||
log(`Human: load model: ${config.face.age.modelPath.match(/\/(.*)\./)[1]}`);
|
||||
log(`load model: ${config.face.age.modelPath.match(/\/(.*)\./)[1]}`);
|
||||
}
|
||||
return models.age;
|
||||
}
|
||||
|
|
|
|||
|
|
@ -14,9 +14,7 @@ function withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, { x, y },
|
|||
*/
|
||||
function getInstanceScore(existingPoses, squaredNmsRadius, instanceKeypoints) {
|
||||
const notOverlappedKeypointScores = instanceKeypoints.reduce((result, { position, score }, keypointId) => {
|
||||
if (!withinNmsRadiusOfCorrespondingPoint(existingPoses, squaredNmsRadius, position, keypointId)) {
|
||||
result += score;
|
||||
}
|
||||
if (!withinNmsRadiusOfCorrespondingPoint(existingPoses, squaredNmsRadius, position, keypointId)) result += score;
|
||||
return result;
|
||||
}, 0.0);
|
||||
return notOverlappedKeypointScores / instanceKeypoints.length;
|
||||
|
|
@ -80,7 +78,7 @@ const kLocalMaximumRadius = 1;
|
|||
* @return An array of poses and their scores, each containing keypoints and
|
||||
* the corresponding keypoint scores.
|
||||
*/
|
||||
function decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, outputStride, maxPoseDetections, scoreThreshold = 0.5, nmsRadius = 20) {
|
||||
function decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, outputStride, maxPoseDetections, scoreThreshold, nmsRadius) {
|
||||
const poses = [];
|
||||
const queue = buildParts.buildPartWithScoreQueue(scoreThreshold, kLocalMaximumRadius, scoresBuffer);
|
||||
const squaredNmsRadius = nmsRadius * nmsRadius;
|
||||
|
|
@ -97,7 +95,7 @@ function decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer
|
|||
// Start a new detection instance at the position of the root.
|
||||
const keypoints = decodePose.decodePose(root, scoresBuffer, offsetsBuffer, outputStride, displacementsFwdBuffer, displacementsBwdBuffer);
|
||||
const score = getInstanceScore(poses, squaredNmsRadius, keypoints);
|
||||
poses.push({ keypoints, score });
|
||||
if (score > scoreThreshold) poses.push({ keypoints, score });
|
||||
}
|
||||
return poses;
|
||||
}
|
||||
|
|
|
|||
|
|
@ -61,8 +61,7 @@ function decodePose(root, scores, offsets, outputStride, displacementsFwd, displ
|
|||
part: keypoints.partNames[rootPart.id],
|
||||
position: rootPoint,
|
||||
};
|
||||
// Decode the part positions upwards in the tree, following the backward
|
||||
// displacements.
|
||||
// Decode the part positions upwards in the tree, following the backward displacements.
|
||||
for (let edge = numEdges - 1; edge >= 0; --edge) {
|
||||
const sourceKeypointId = parentToChildEdges[edge];
|
||||
const targetKeypointId = childToParentEdges[edge];
|
||||
|
|
@ -70,8 +69,7 @@ function decodePose(root, scores, offsets, outputStride, displacementsFwd, displ
|
|||
instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, displacementsBwd);
|
||||
}
|
||||
}
|
||||
// Decode the part positions downwards in the tree, following the forward
|
||||
// displacements.
|
||||
// Decode the part positions downwards in the tree, following the forward displacements.
|
||||
for (let edge = 0; edge < numEdges; ++edge) {
|
||||
const sourceKeypointId = childToParentEdges[edge];
|
||||
const targetKeypointId = parentToChildEdges[edge];
|
||||
|
|
|
|||
|
|
@ -41,7 +41,7 @@ exports.PoseNet = PoseNet;
|
|||
async function load(config) {
|
||||
const graphModel = await tf.loadGraphModel(config.body.modelPath);
|
||||
const mobilenet = new modelMobileNet.MobileNet(graphModel, this.outputStride);
|
||||
log(`Human: load model: ${config.body.modelPath.match(/\/(.*)\./)[1]}`);
|
||||
log(`load model: ${config.body.modelPath.match(/\/(.*)\./)[1]}`);
|
||||
return new PoseNet(mobilenet);
|
||||
}
|
||||
exports.load = load;
|
||||
|
|
|
|||
|
|
@ -10,7 +10,7 @@ const models = {};
|
|||
async function load(config) {
|
||||
if (!models.embedding) {
|
||||
models.embedding = await tf.loadGraphModel(config.face.embedding.modelPath);
|
||||
log(`Human: load model: ${config.face.embedding.modelPath.match(/\/(.*)\./)[1]}`);
|
||||
log(`load model: ${config.face.embedding.modelPath.match(/\/(.*)\./)[1]}`);
|
||||
}
|
||||
return models.embedding;
|
||||
}
|
||||
|
|
|
|||
|
|
@ -14,7 +14,7 @@ const scale = 1; // score multiplication factor
|
|||
async function load(config) {
|
||||
if (!models.emotion) {
|
||||
models.emotion = await tf.loadGraphModel(config.face.emotion.modelPath);
|
||||
log(`Human: load model: ${config.face.emotion.modelPath.match(/\/(.*)\./)[1]}`);
|
||||
log(`load model: ${config.face.emotion.modelPath.match(/\/(.*)\./)[1]}`);
|
||||
}
|
||||
return models.emotion;
|
||||
}
|
||||
|
|
|
|||
|
|
@ -167,7 +167,7 @@ class BlazeFaceModel {
|
|||
async function load(config) {
|
||||
const blazeface = await tf.loadGraphModel(config.face.detector.modelPath, { fromTFHub: config.face.detector.modelPath.includes('tfhub.dev') });
|
||||
const model = new BlazeFaceModel(blazeface, config);
|
||||
log(`Human: load model: ${config.face.detector.modelPath.match(/\/(.*)\./)[1]}`);
|
||||
log(`load model: ${config.face.detector.modelPath.match(/\/(.*)\./)[1]}`);
|
||||
return model;
|
||||
}
|
||||
|
||||
|
|
|
|||
|
|
@ -25,9 +25,15 @@ class MediaPipeFaceMesh {
|
|||
}
|
||||
}
|
||||
}
|
||||
const box = prediction.box ? [
|
||||
Math.max(0, prediction.box.startPoint[0]),
|
||||
Math.max(0, prediction.box.startPoint[1]),
|
||||
Math.min(input.shape[2], prediction.box.endPoint[0]) - prediction.box.startPoint[0],
|
||||
Math.min(input.shape[1], prediction.box.endPoint[1]) - prediction.box.startPoint[1],
|
||||
] : 0;
|
||||
results.push({
|
||||
confidence: prediction.confidence || 0,
|
||||
box: prediction.box ? [prediction.box.startPoint[0], prediction.box.startPoint[1], prediction.box.endPoint[0] - prediction.box.startPoint[0], prediction.box.endPoint[1] - prediction.box.startPoint[1]] : 0,
|
||||
box,
|
||||
mesh,
|
||||
annotations,
|
||||
image: prediction.image ? tf.clone(prediction.image) : null,
|
||||
|
|
@ -47,8 +53,8 @@ async function load(config) {
|
|||
(!faceModels[2] && config.face.iris.enabled) ? tf.loadGraphModel(config.face.iris.modelPath, { fromTFHub: config.face.iris.modelPath.includes('tfhub.dev') }) : null,
|
||||
]);
|
||||
const faceMesh = new MediaPipeFaceMesh(faceModels[0], faceModels[1], faceModels[2], config);
|
||||
if (config.face.mesh.enabled) log(`Human: load model: ${config.face.mesh.modelPath.match(/\/(.*)\./)[1]}`);
|
||||
if (config.face.iris.enabled) log(`Human: load model: ${config.face.iris.modelPath.match(/\/(.*)\./)[1]}`);
|
||||
if (config.face.mesh.enabled) log(`load model: ${config.face.mesh.modelPath.match(/\/(.*)\./)[1]}`);
|
||||
if (config.face.iris.enabled) log(`load model: ${config.face.iris.modelPath.match(/\/(.*)\./)[1]}`);
|
||||
return faceMesh;
|
||||
}
|
||||
|
||||
|
|
|
|||
|
|
@ -14,7 +14,7 @@ async function load(config) {
|
|||
if (!models.gender) {
|
||||
models.gender = await tf.loadGraphModel(config.face.gender.modelPath);
|
||||
alternative = models.gender.inputs[0].shape[3] === 1;
|
||||
log(`Human: load model: ${config.face.gender.modelPath.match(/\/(.*)\./)[1]}`);
|
||||
log(`load model: ${config.face.gender.modelPath.match(/\/(.*)\./)[1]}`);
|
||||
}
|
||||
return models.gender;
|
||||
}
|
||||
|
|
|
|||
|
|
@ -51,14 +51,15 @@ class HandPose {
|
|||
annotations[key] = MESH_ANNOTATIONS[key].map((index) => prediction.landmarks[index]);
|
||||
}
|
||||
}
|
||||
const box = prediction.box ? [
|
||||
Math.max(0, prediction.box.topLeft[0]),
|
||||
Math.max(0, prediction.box.topLeft[1]),
|
||||
Math.min(input.shape[2], prediction.box.bottomRight[0]) - prediction.box.topLeft[0],
|
||||
Math.min(input.shape[1], prediction.box.bottomRight[1]) - prediction.box.topLeft[1],
|
||||
] : 0;
|
||||
hands.push({
|
||||
confidence: prediction.confidence,
|
||||
box: prediction.box ? [
|
||||
prediction.box.topLeft[0],
|
||||
prediction.box.topLeft[1],
|
||||
prediction.box.bottomRight[0] - prediction.box.topLeft[0],
|
||||
prediction.box.bottomRight[1] - prediction.box.topLeft[1],
|
||||
] : 0,
|
||||
box,
|
||||
landmarks: prediction.landmarks,
|
||||
annotations,
|
||||
});
|
||||
|
|
@ -76,8 +77,8 @@ async function load(config) {
|
|||
const detector = new handdetector.HandDetector(handDetectorModel, config.hand.inputSize, anchors.anchors);
|
||||
const pipe = new pipeline.HandPipeline(detector, handPoseModel, config.hand.inputSize);
|
||||
const handpose = new HandPose(pipe);
|
||||
if (config.hand.enabled) log(`Human: load model: ${config.hand.detector.modelPath.match(/\/(.*)\./)[1]}`);
|
||||
if (config.hand.landmarks) log(`Human: load model: ${config.hand.skeleton.modelPath.match(/\/(.*)\./)[1]}`);
|
||||
if (config.hand.enabled) log(`load model: ${config.hand.detector.modelPath.match(/\/(.*)\./)[1]}`);
|
||||
if (config.hand.landmarks) log(`load model: ${config.hand.skeleton.modelPath.match(/\/(.*)\./)[1]}`);
|
||||
return handpose;
|
||||
}
|
||||
exports.load = load;
|
||||
|
|
|
|||
22
src/human.js
22
src/human.js
|
|
@ -416,23 +416,27 @@ class Human {
|
|||
}
|
||||
|
||||
async warmup(userConfig) {
|
||||
if (userConfig) this.config = mergeDeep(this.config, userConfig);
|
||||
const width = 256;
|
||||
const height = 256;
|
||||
const video = this.config.videoOptimized;
|
||||
this.config.videoOptimized = false;
|
||||
return new Promise((resolve) => {
|
||||
log('Starting warmup');
|
||||
const img = new Image(256, 256);
|
||||
const img = new Image(width, height);
|
||||
img.onload = () => {
|
||||
log('Loading sample');
|
||||
const canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(256, 256) : document.createElement('canvas');
|
||||
canvas.width = 256;
|
||||
canvas.height = 256;
|
||||
const canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(width, height) : document.createElement('canvas');
|
||||
canvas.width = width;
|
||||
canvas.height = height;
|
||||
const ctx = canvas.getContext('2d');
|
||||
ctx.drawImage(img, 0, 0);
|
||||
const data = ctx.getImageData(0, 0, 255, 255);
|
||||
this.detect(data, userConfig).then((warmup) => {
|
||||
const data = ctx.getImageData(0, 0, width, height);
|
||||
this.detect(data, config).then((warmup) => {
|
||||
log('Warmup', warmup);
|
||||
this.config.videoOptimized = video;
|
||||
resolve(warmup);
|
||||
});
|
||||
};
|
||||
img.src = sample.data;
|
||||
img.src = sample.face;
|
||||
});
|
||||
}
|
||||
}
|
||||
|
|
|
|||
572
src/sample.js
572
src/sample.js
|
|
@ -1,4 +1,4 @@
|
|||
export const data = `data:image/jpeg;base64,
|
||||
export const face = `data:image/jpeg;base64,
|
||||
/9j/4AAQSkZJRgABAQEAYABgAAD/4QBoRXhpZgAATU0AKgAAAAgABAEaAAUAAAABAAAAPgEbAAUA
|
||||
AAABAAAARgEoAAMAAAABAAIAAAExAAIAAAARAAAATgAAAAAAAABgAAAAAQAAAGAAAAABcGFpbnQu
|
||||
bmV0IDQuMi4xMwAA/9sAQwAGBAUGBQQGBgUGBwcGCAoQCgoJCQoUDg8MEBcUGBgXFBYWGh0lHxob
|
||||
|
|
@ -150,3 +150,573 @@ c6oaM5TUJ8EgGsG4kLNUHT0M64OaqMMikSRsuKbnFMRLG3zVehOaGNE445NNlnVFpDMu6uie9Vo1
|
|||
8z5mOAOST2pDK91cNN+5tsrH3PrW54a06KxT7fdrlh/q1Pc+tJ6IUdZGvHPLezMcnBOWbsPap5r3
|
||||
ylFtbdT1xUWNWzU0/Zbwlgfmx8zGsHWtRHmMqE59aAMyNifvHPc1f0gtPdqkY5JosJHeNci2tktY
|
||||
euPnNY+oXWZEVJNrZ9aun8SIq/CzodHuriIokhDIR1ronbKZr0o6o8ipoz//2Q==`;
|
||||
|
||||
export const body = `data:image/jpeg;base64,
|
||||
/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAsICAoIBwsKCQoNDAsNERwSEQ8PESIZGhQcKSQrKigk
|
||||
JyctMkA3LTA9MCcnOEw5PUNFSElIKzZPVU5GVEBHSEX/2wBDAQwNDREPESESEiFFLicuRUVFRUVF
|
||||
RUVFRUVFRUVFRUVFRUVFRUVFRUVFRUVFRUVFRUVFRUVFRUVFRUVFRUVFRUX/wAARCASwBLADASIA
|
||||
AhEBAxEB/8QAGwABAAIDAQEAAAAAAAAAAAAAAAEDAgQFBgf/xABDEAEAAgECBAMECQIDBgUFAQAA
|
||||
AQIDBBEFEiExE0FRBiJhcRQjMkJSgZGhsWLBJDNyFSVTY3OSNEPR4fAHFjWCokT/xAAYAQEAAwEA
|
||||
AAAAAAAAAAAAAAAAAQIDBP/EACARAQEBAQADAQEBAQEBAAAAAAABAhEDITFBEjJRIhP/2gAMAwEA
|
||||
AhEDEQA/APqYAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
||||
AAAAAAKNTq8OkxzfNkisQC8eb1XtRNbzXT4q7eU2nu0MntRq/D8StMccvW29ZmdvgjsTyvZjxOLj
|
||||
+s8WLxn8TFPXs6Oj9oct7c14rkxz22nrB2I49KOdTjelmszfmpMeUxv/AA28OqwZ4icWWtt/SUi4
|
||||
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
||||
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAmdo3nsPNe0Pt
|
||||
Fh09Z0+DNWL7+9O/7A3eJcZppsV5raI27esvH6jX5ddM25p79Ilo59VbUZOe2Tm/PeGvfPfT2iKR
|
||||
PLv1+DO678XmW/a97U6TtOyzTbTF538/T9WjTNecm9a7126tqk3rSYxY5ta1plRZqZNXGjyZcPXl
|
||||
mZmsx+qjBrsuO16xM7eXRt04JrdTltk5OWJnfaWf0a2lty5MdZnfzSn+WOHiOutFpjHa9e8bQ2fp
|
||||
+alYy462pk7zXbuxjPesbRS0f6ZZV1ET1tErzXFLHo+A+1ddZf6NrI8PJHa1vN6iJi0bxMTHwfOa
|
||||
zhzd61v1846utwniM6DUdb3nBaNrVmd9vjC/ZVePYirBqMWppz4rxaPgtEAAAAAAAAAAAAAAAAAA
|
||||
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
||||
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAItaK1m09ojcHnvarjM8P0vh49+a/eY8ng9D
|
||||
h1fGM1rxjtGPfvbzdbjuTJxHX48cTPNltM/KsS9Dw7S49Jp6UpHaGe2vjz1y9J7LYK13vHWe7bj2
|
||||
ex1tvM80ekuxW3RnW3Vm6P5jRx8H0+OYmMcb+bapo8GKPdpC6bQwtdHU8JpWkdJ/JweL6e23iU67
|
||||
d4dubSqyVi9Zi0bwIs68XGp36TtEq7ZJmZmevzdbifCKWtbJinkt6eTgZPFw32t+sRurbWVzxs1y
|
||||
Rv6T8V1NZNPtfq0seTm+Kevr+SZuxXjvaPiV8N4viycto9HseG6+uu08W6Rkj7UPmFck1tE1nlmP
|
||||
Ld3eA8V8HVVi1pjq6Ma/pnqce/ERMTETHaUrKgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
||||
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
||||
AAAAAAAAAAAAAAAAADW19+TQ5p/p2bLS4v04Zmt5VjeQeJ4bjnLqsupv+Ka1+ERLv4reTmcNxcuC
|
||||
vy3l0qdI2hlr66sT02ot0ZV7qqrInruzrVZLGSZ37JjqgYTG0K5lbaFVhDT1Ub456RPweY4hixWi
|
||||
eSdpjvD1eWejz3FNHWYtkpvFo9EIseb3tS3SerOms22rfpPqZKzvvHSYUz70TExG6Gdbs2rljeJ/
|
||||
Mx5L0vEzPaelnOi98c9J2bFNTFpit47+a+PVUvx9T9nOIfT+GV5p3yY/ds67wvsXqpxau+G09Lx+
|
||||
r3TqrEAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
||||
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADV4ljnLw3U0jvO
|
||||
O0fs2lWqyUw6XLkyfYrWZkHldBEV09eveG3Fq1mI3jd4vPrOIaid8G9MP3Y38k6fNrt/rMk9Ou8s
|
||||
tfXXn49rGWInuy8SO/k5Gl1E3rG/fzbOe94wTy99mbRvTrMOOvNfJWsesywniukrG/jU6fF43WYN
|
||||
TmtEeJtEQ06aSmK2+bNtEd+qfSO17unF9Hmvy1y13XWyVmN4tExLxVK8PmNq5NrT58zawam+m/yc
|
||||
0Xj8NpRYSvQZ7xEOdqI3rPozxayNRXe0ct/ON03jmrKB5nV4q1yTO20Obmv4c+cx8HoeI6WZpNoj
|
||||
q83niYmYscU0r8aJ6T1n49zeJ+Meqm1drb9J+Kd5p136StGVem9l9TbHxLDFp7W7+sS+q1nesT6w
|
||||
+PcAzVjiGHftzQ+v4f8AJpv6On8jH9ZgIAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
||||
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
||||
AAAAAAAAAAABp8VrW/C9TW0ztOO3b5Nxp8VmI4bn37TWYB8f1HFtTfUfR9FWJmsdZ9I7MtJxDX5s
|
||||
d8ta1y0xzteaR2277rcuhycP12SceLxMeWNpjttHwlu8I0mfQ1y+D7k5YmJmY36T36Ka43z/AF1t
|
||||
cI1ds+qxVj7/AEej19PCw9HJ4NoK4OIU5Y35YmZdzVTGebVZabx5jJS+Tmns81rNLm1Wrzc9rVw4
|
||||
Yibbem72mXTTS0w0M3BvEta1bWrM95ie5EanY87wXgNOL6XPfxraXLhra/W28bR/dzYzarBqJxRe
|
||||
bzE7Rt5vWU9n8mPHOGmS0Ypnea1naJb+k9ncNLR7u2y/WcxXO4TOoyUrN6zD0FaW5Y3hu49FiwUi
|
||||
KxCvLMR0hlW0jn6ukWw3iXjOJzbDlneOj3GaN6zDzfFOH+LE7SRGo83XNSZ2lbG2/WfdlvaT2cy6
|
||||
rNFInlrv1mfJ37cK4PwTTxOoidRm2+/2/KFuyMp47XB4LivXiunrH2b2iH2qn2K/J8x4fGDNxTSZ
|
||||
9Nh8OviRvTyfT6xtWI+DeXs9MNZubypASqAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
||||
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
|
||||
AAAAAAAAAAAAOZx6/LoOWPvWiHTcf2hiZ0e8fc2mf1E5+vP/AEeuSd7RC2uKtI6QjHfeINTfwtPf
|
||||
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||||
2Q==`;
|
||||
|
|
|
|||
Loading…
Reference in New Issue