@tensorflow-models/coco-ssd - npm Package Compare versions

Comparing version 2.2.0 to 2.2.1

dist/coco-ssd.es2017.esm.min.js

@@ -17,3 +17,3 @@ /**
  */
-import{loadGraphModel as a}from"@tensorflow/tfjs-converter";import*as e from"@tensorflow/tfjs-core";import{zeros as m,tidy as i,Tensor as d,browser as s,dispose as n,getBackend as l,setBackend as t,tensor2d as o,image as p}from"@tensorflow/tfjs-core";const r={1:{name:"/m/01g317",id:1,displayName:"person"},2:{name:"/m/0199g",id:2,displayName:"bicycle"},3:{name:"/m/0k4j",id:3,displayName:"car"},4:{name:"/m/04_sv",id:4,displayName:"motorcycle"},5:{name:"/m/05czz6l",id:5,displayName:"airplane"},6:{name:"/m/01bjv",id:6,displayName:"bus"},7:{name:"/m/07jdr",id:7,displayName:"train"},8:{name:"/m/07r04",id:8,displayName:"truck"},9:{name:"/m/019jd",id:9,displayName:"boat"},10:{name:"/m/015qff",id:10,displayName:"traffic light"},11:{name:"/m/01pns0",id:11,displayName:"fire hydrant"},13:{name:"/m/02pv19",id:13,displayName:"stop sign"},14:{name:"/m/015qbp",id:14,displayName:"parking meter"},15:{name:"/m/0cvnqh",id:15,displayName:"bench"},16:{name:"/m/015p6",id:16,displayName:"bird"},17:{name:"/m/01yrx",id:17,displayName:"cat"},18:{name:"/m/0bt9lr",id:18,displayName:"dog"},19:{name:"/m/03k3r",id:19,displayName:"horse"},20:{name:"/m/07bgp",id:20,displayName:"sheep"},21:{name:"/m/01xq0k1",id:21,displayName:"cow"},22:{name:"/m/0bwd_0j",id:22,displayName:"elephant"},23:{name:"/m/01dws",id:23,displayName:"bear"},24:{name:"/m/0898b",id:24,displayName:"zebra"},25:{name:"/m/03bk1",id:25,displayName:"giraffe"},27:{name:"/m/01940j",id:27,displayName:"backpack"},28:{name:"/m/0hnnb",id:28,displayName:"umbrella"},31:{name:"/m/080hkjn",id:31,displayName:"handbag"},32:{name:"/m/01rkbr",id:32,displayName:"tie"},33:{name:"/m/01s55n",id:33,displayName:"suitcase"},34:{name:"/m/02wmf",id:34,displayName:"frisbee"},35:{name:"/m/071p9",id:35,displayName:"skis"},36:{name:"/m/06__v",id:36,displayName:"snowboard"},37:{name:"/m/018xm",id:37,displayName:"sports ball"},38:{name:"/m/02zt3",id:38,displayName:"kite"},39:{name:"/m/03g8mr",id:39,displayName:"baseball bat"},40:{name:"/m/03grzl",id:40,displayName:"baseball glove"},41:{name:"/m/06_fw",id:41,displayName:"skateboard"},42:{name:"/m/019w40",id:42,displayName:"surfboard"},43:{name:"/m/0dv9c",id:43,displayName:"tennis racket"},44:{name:"/m/04dr76w",id:44,displayName:"bottle"},46:{name:"/m/09tvcd",id:46,displayName:"wine glass"},47:{name:"/m/08gqpm",id:47,displayName:"cup"},48:{name:"/m/0dt3t",id:48,displayName:"fork"},49:{name:"/m/04ctx",id:49,displayName:"knife"},50:{name:"/m/0cmx8",id:50,displayName:"spoon"},51:{name:"/m/04kkgm",id:51,displayName:"bowl"},52:{name:"/m/09qck",id:52,displayName:"banana"},53:{name:"/m/014j1m",id:53,displayName:"apple"},54:{name:"/m/0l515",id:54,displayName:"sandwich"},55:{name:"/m/0cyhj_",id:55,displayName:"orange"},56:{name:"/m/0hkxq",id:56,displayName:"broccoli"},57:{name:"/m/0fj52s",id:57,displayName:"carrot"},58:{name:"/m/01b9xk",id:58,displayName:"hot dog"},59:{name:"/m/0663v",id:59,displayName:"pizza"},60:{name:"/m/0jy4k",id:60,displayName:"donut"},61:{name:"/m/0fszt",id:61,displayName:"cake"},62:{name:"/m/01mzpv",id:62,displayName:"chair"},63:{name:"/m/02crq1",id:63,displayName:"couch"},64:{name:"/m/03fp41",id:64,displayName:"potted plant"},65:{name:"/m/03ssj5",id:65,displayName:"bed"},67:{name:"/m/04bcr3",id:67,displayName:"dining table"},70:{name:"/m/09g1w",id:70,displayName:"toilet"},72:{name:"/m/07c52",id:72,displayName:"tv"},73:{name:"/m/01c648",id:73,displayName:"laptop"},74:{name:"/m/020lf",id:74,displayName:"mouse"},75:{name:"/m/0qjjc",id:75,displayName:"remote"},76:{name:"/m/01m2v",id:76,displayName:"keyboard"},77:{name:"/m/050k8",id:77,displayName:"cell phone"},78:{name:"/m/0fx9l",id:78,displayName:"microwave"},79:{name:"/m/029bxz",id:79,displayName:"oven"},80:{name:"/m/01k6s3",id:80,displayName:"toaster"},81:{name:"/m/0130jx",id:81,displayName:"sink"},82:{name:"/m/040b_t",id:82,displayName:"refrigerator"},84:{name:"/m/0bt_c3",id:84,displayName:"book"},85:{name:"/m/01x3z",id:85,displayName:"clock"},86:{name:"/m/02s195",id:86,displayName:"vase"},87:{name:"/m/01lsmm",id:87,displayName:"scissors"},88:{name:"/m/0kmg4",id:88,displayName:"teddy bear"},89:{name:"/m/03wvsk",id:89,displayName:"hair drier"},90:{name:"/m/012xff",id:90,displayName:"toothbrush"}},y="2.2.0";async function c(a={}){if(null==e)throw new Error("Cannot find TensorFlow.js. If you are using a <script> tag, please also include @tensorflow/tfjs on the page before using this model.");const m=a.base||"lite_mobilenet_v2",i=a.modelUrl;if(-1===["mobilenet_v1","mobilenet_v2","lite_mobilenet_v2"].indexOf(m))throw new Error("ObjectDetection constructed with invalid base model "+m+". Valid names are 'mobilenet_v1', 'mobilenet_v2' and 'lite_mobilenet_v2'.");const d=new N(m,i);return await d.load(),d}class N{constructor(a,e){this.modelPath=e||`https://storage.googleapis.com/tfjs-models/savedmodel/${this.getPrefix(a)}/model.json`}getPrefix(a){return"lite_mobilenet_v2"===a?"ssd"+a:"ssd_"+a}async load(){this.model=await a(this.modelPath);const e=m([1,300,300,3],"int32"),i=await this.model.executeAsync(e);await Promise.all(i.map(a=>a.data())),i.map(a=>a.dispose()),e.dispose()}async infer(a,e,m){const r=i(()=>(a instanceof d||(a=s.fromPixels(a)),a.expandDims(0))),y=r.shape[1],c=r.shape[2],N=await this.model.executeAsync(r),b=N[0].dataSync(),f=N[1].dataSync();r.dispose(),n(N);const[h,u]=this.calculateMaxScores(b,N[0].shape[1],N[0].shape[2]),g=l();"webgl"===l()&&t("cpu");const k=i(()=>{const a=o(f,[N[1].shape[1],N[1].shape[3]]);return p.nonMaxSuppression(a,h,e,m,m)}),w=k.dataSync();return k.dispose(),g!==l()&&t(g),this.buildDetectedObjects(c,y,f,h,w,u)}buildDetectedObjects(a,e,m,i,d,s){const n=d.length,l=[];for(let t=0;t<n;t++){const n=[];for(let a=0;a<4;a++)n[a]=m[4*d[t]+a];const o=n[0]*e,p=n[1]*a,y=n[2]*e,c=n[3]*a;n[0]=p,n[1]=o,n[2]=c-p,n[3]=y-o,l.push({bbox:n,class:r[s[d[t]]+1].displayName,score:i[d[t]]})}return l}calculateMaxScores(a,e,m){const i=[],d=[];for(let s=0;s<e;s++){let e=Number.MIN_VALUE,n=-1;for(let i=0;i<m;i++)a[s*m+i]>e&&(e=a[s*m+i],n=i);i[s]=e,d[s]=n}return[i,d]}async detect(a,e=20,m=.5){return this.infer(a,e,m)}dispose(){null!=this.model&&this.model.dispose()}}export{N as ObjectDetection,c as load,y as version};
+!function(e,a){"object"==typeof exports&&"undefined"!=typeof module?a(exports,require("@tensorflow/tfjs-converter"),require("@tensorflow/tfjs-core")):"function"==typeof define&&define.amd?define(["exports","@tensorflow/tfjs-converter","@tensorflow/tfjs-core"],a):a((e=e||self).cocoSsd=e.cocoSsd||{},e.tf,e.tf)}(this,(function(e,a,m){"use strict";const i={1:{name:"/m/01g317",id:1,displayName:"person"},2:{name:"/m/0199g",id:2,displayName:"bicycle"},3:{name:"/m/0k4j",id:3,displayName:"car"},4:{name:"/m/04_sv",id:4,displayName:"motorcycle"},5:{name:"/m/05czz6l",id:5,displayName:"airplane"},6:{name:"/m/01bjv",id:6,displayName:"bus"},7:{name:"/m/07jdr",id:7,displayName:"train"},8:{name:"/m/07r04",id:8,displayName:"truck"},9:{name:"/m/019jd",id:9,displayName:"boat"},10:{name:"/m/015qff",id:10,displayName:"traffic light"},11:{name:"/m/01pns0",id:11,displayName:"fire hydrant"},13:{name:"/m/02pv19",id:13,displayName:"stop sign"},14:{name:"/m/015qbp",id:14,displayName:"parking meter"},15:{name:"/m/0cvnqh",id:15,displayName:"bench"},16:{name:"/m/015p6",id:16,displayName:"bird"},17:{name:"/m/01yrx",id:17,displayName:"cat"},18:{name:"/m/0bt9lr",id:18,displayName:"dog"},19:{name:"/m/03k3r",id:19,displayName:"horse"},20:{name:"/m/07bgp",id:20,displayName:"sheep"},21:{name:"/m/01xq0k1",id:21,displayName:"cow"},22:{name:"/m/0bwd_0j",id:22,displayName:"elephant"},23:{name:"/m/01dws",id:23,displayName:"bear"},24:{name:"/m/0898b",id:24,displayName:"zebra"},25:{name:"/m/03bk1",id:25,displayName:"giraffe"},27:{name:"/m/01940j",id:27,displayName:"backpack"},28:{name:"/m/0hnnb",id:28,displayName:"umbrella"},31:{name:"/m/080hkjn",id:31,displayName:"handbag"},32:{name:"/m/01rkbr",id:32,displayName:"tie"},33:{name:"/m/01s55n",id:33,displayName:"suitcase"},34:{name:"/m/02wmf",id:34,displayName:"frisbee"},35:{name:"/m/071p9",id:35,displayName:"skis"},36:{name:"/m/06__v",id:36,displayName:"snowboard"},37:{name:"/m/018xm",id:37,displayName:"sports ball"},38:{name:"/m/02zt3",id:38,displayName:"kite"},39:{name:"/m/03g8mr",id:39,displayName:"baseball bat"},40:{name:"/m/03grzl",id:40,displayName:"baseball glove"},41:{name:"/m/06_fw",id:41,displayName:"skateboard"},42:{name:"/m/019w40",id:42,displayName:"surfboard"},43:{name:"/m/0dv9c",id:43,displayName:"tennis racket"},44:{name:"/m/04dr76w",id:44,displayName:"bottle"},46:{name:"/m/09tvcd",id:46,displayName:"wine glass"},47:{name:"/m/08gqpm",id:47,displayName:"cup"},48:{name:"/m/0dt3t",id:48,displayName:"fork"},49:{name:"/m/04ctx",id:49,displayName:"knife"},50:{name:"/m/0cmx8",id:50,displayName:"spoon"},51:{name:"/m/04kkgm",id:51,displayName:"bowl"},52:{name:"/m/09qck",id:52,displayName:"banana"},53:{name:"/m/014j1m",id:53,displayName:"apple"},54:{name:"/m/0l515",id:54,displayName:"sandwich"},55:{name:"/m/0cyhj_",id:55,displayName:"orange"},56:{name:"/m/0hkxq",id:56,displayName:"broccoli"},57:{name:"/m/0fj52s",id:57,displayName:"carrot"},58:{name:"/m/01b9xk",id:58,displayName:"hot dog"},59:{name:"/m/0663v",id:59,displayName:"pizza"},60:{name:"/m/0jy4k",id:60,displayName:"donut"},61:{name:"/m/0fszt",id:61,displayName:"cake"},62:{name:"/m/01mzpv",id:62,displayName:"chair"},63:{name:"/m/02crq1",id:63,displayName:"couch"},64:{name:"/m/03fp41",id:64,displayName:"potted plant"},65:{name:"/m/03ssj5",id:65,displayName:"bed"},67:{name:"/m/04bcr3",id:67,displayName:"dining table"},70:{name:"/m/09g1w",id:70,displayName:"toilet"},72:{name:"/m/07c52",id:72,displayName:"tv"},73:{name:"/m/01c648",id:73,displayName:"laptop"},74:{name:"/m/020lf",id:74,displayName:"mouse"},75:{name:"/m/0qjjc",id:75,displayName:"remote"},76:{name:"/m/01m2v",id:76,displayName:"keyboard"},77:{name:"/m/050k8",id:77,displayName:"cell phone"},78:{name:"/m/0fx9l",id:78,displayName:"microwave"},79:{name:"/m/029bxz",id:79,displayName:"oven"},80:{name:"/m/01k6s3",id:80,displayName:"toaster"},81:{name:"/m/0130jx",id:81,displayName:"sink"},82:{name:"/m/040b_t",id:82,displayName:"refrigerator"},84:{name:"/m/0bt_c3",id:84,displayName:"book"},85:{name:"/m/01x3z",id:85,displayName:"clock"},86:{name:"/m/02s195",id:86,displayName:"vase"},87:{name:"/m/01lsmm",id:87,displayName:"scissors"},88:{name:"/m/0kmg4",id:88,displayName:"teddy bear"},89:{name:"/m/03wvsk",id:89,displayName:"hair drier"},90:{name:"/m/012xff",id:90,displayName:"toothbrush"}};class d{constructor(e,a){this.modelPath=a||`https://storage.googleapis.com/tfjs-models/savedmodel/${this.getPrefix(e)}/model.json`}getPrefix(e){return"lite_mobilenet_v2"===e?"ssd"+e:"ssd_"+e}async load(){this.model=await a.loadGraphModel(this.modelPath);const e=m.zeros([1,300,300,3],"int32"),i=await this.model.executeAsync(e);await Promise.all(i.map(e=>e.data())),i.map(e=>e.dispose()),e.dispose()}async infer(e,a,i){const d=m.tidy(()=>(e instanceof m.Tensor||(e=m.browser.fromPixels(e)),e.expandDims(0))),s=d.shape[1],n=d.shape[2],l=await this.model.executeAsync(d),t=l[0].dataSync(),o=l[1].dataSync();d.dispose(),m.dispose(l);const[p,r]=this.calculateMaxScores(t,l[0].shape[1],l[0].shape[2]),c=m.getBackend();"webgl"===m.getBackend()&&m.setBackend("cpu");const y=m.tidy(()=>{const e=m.tensor2d(o,[l[1].shape[1],l[1].shape[3]]);return m.image.nonMaxSuppression(e,p,a,i,i)}),N=y.dataSync();return y.dispose(),c!==m.getBackend()&&m.setBackend(c),this.buildDetectedObjects(n,s,o,p,N,r)}buildDetectedObjects(e,a,m,d,s,n){const l=s.length,t=[];for(let o=0;o<l;o++){const l=[];for(let e=0;e<4;e++)l[e]=m[4*s[o]+e];const p=l[0]*a,r=l[1]*e,c=l[2]*a,y=l[3]*e;l[0]=r,l[1]=p,l[2]=y-r,l[3]=c-p,t.push({bbox:l,class:i[n[s[o]]+1].displayName,score:d[s[o]]})}return t}calculateMaxScores(e,a,m){const i=[],d=[];for(let s=0;s<a;s++){let a=Number.MIN_VALUE,n=-1;for(let i=0;i<m;i++)e[s*m+i]>a&&(a=e[s*m+i],n=i);i[s]=a,d[s]=n}return[i,d]}async detect(e,a=20,m=.5){return this.infer(e,a,m)}dispose(){null!=this.model&&this.model.dispose()}}e.ObjectDetection=d,e.load=async function(e={}){if(null==m)throw new Error("Cannot find TensorFlow.js. If you are using a <script> tag, please also include @tensorflow/tfjs on the page before using this model.");const a=e.base||"lite_mobilenet_v2",i=e.modelUrl;if(-1===["mobilenet_v1","mobilenet_v2","lite_mobilenet_v2"].indexOf(a))throw new Error("ObjectDetection constructed with invalid base model "+a+". Valid names are 'mobilenet_v1', 'mobilenet_v2' and 'lite_mobilenet_v2'.");const s=new d(a,i);return await s.load(),s},e.version="2.2.1",Object.defineProperty(e,"__esModule",{value:!0})}));
 //# sourceMappingURL=coco-ssd.es2017.esm.min.js.map

dist/coco-ssd.js

@@ -496,3 +496,3 @@ /**
     // This code is auto-generated, do not modify this file!
-    var version = '2.2.0';
+    var version = '2.2.1';
 
@@ -499,0 +499,0 @@ /**

dist/coco-ssd.min.js

@@ -17,3 +17,3 @@ /**
  */
-!function(e,a){"object"==typeof exports&&"undefined"!=typeof module?a(exports,require("@tensorflow/tfjs-converter"),require("@tensorflow/tfjs-core")):"function"==typeof define&&define.amd?define(["exports","@tensorflow/tfjs-converter","@tensorflow/tfjs-core"],a):a((e=e||self).cocoSsd=e.cocoSsd||{},e.tf,e.tf)}(this,(function(e,a,i){"use strict";function n(e,a,i,n){return new(i||(i=Promise))((function(m,t){function d(e){try{o(n.next(e))}catch(e){t(e)}}function s(e){try{o(n.throw(e))}catch(e){t(e)}}function o(e){e.done?m(e.value):new i((function(a){a(e.value)})).then(d,s)}o((n=n.apply(e,a||[])).next())}))}function m(e,a){var i,n,m,t,d={label:0,sent:function(){if(1&m[0])throw m[1];return m[1]},trys:[],ops:[]};return t={next:s(0),throw:s(1),return:s(2)},"function"==typeof Symbol&&(t[Symbol.iterator]=function(){return this}),t;function s(t){return function(s){return function(t){if(i)throw new TypeError("Generator is already executing.");for(;d;)try{if(i=1,n&&(m=2&t[0]?n.return:t[0]?n.throw||((m=n.return)&&m.call(n),0):n.next)&&!(m=m.call(n,t[1])).done)return m;switch(n=0,m&&(t=[2&t[0],m.value]),t[0]){case 0:case 1:m=t;break;case 4:return d.label++,{value:t[1],done:!1};case 5:d.label++,n=t[1],t=[0];continue;case 7:t=d.ops.pop(),d.trys.pop();continue;default:if(!(m=d.trys,(m=m.length>0&&m[m.length-1])||6!==t[0]&&2!==t[0])){d=0;continue}if(3===t[0]&&(!m||t[1]>m[0]&&t[1]<m[3])){d.label=t[1];break}if(6===t[0]&&d.label<m[1]){d.label=m[1],m=t;break}if(m&&d.label<m[2]){d.label=m[2],d.ops.push(t);break}m[2]&&d.ops.pop(),d.trys.pop();continue}t=a.call(e,d)}catch(e){t=[6,e],n=0}finally{i=m=0}if(5&t[0])throw t[1];return{value:t[0]?t[1]:void 0,done:!0}}([t,s])}}}var t={1:{name:"/m/01g317",id:1,displayName:"person"},2:{name:"/m/0199g",id:2,displayName:"bicycle"},3:{name:"/m/0k4j",id:3,displayName:"car"},4:{name:"/m/04_sv",id:4,displayName:"motorcycle"},5:{name:"/m/05czz6l",id:5,displayName:"airplane"},6:{name:"/m/01bjv",id:6,displayName:"bus"},7:{name:"/m/07jdr",id:7,displayName:"train"},8:{name:"/m/07r04",id:8,displayName:"truck"},9:{name:"/m/019jd",id:9,displayName:"boat"},10:{name:"/m/015qff",id:10,displayName:"traffic light"},11:{name:"/m/01pns0",id:11,displayName:"fire hydrant"},13:{name:"/m/02pv19",id:13,displayName:"stop sign"},14:{name:"/m/015qbp",id:14,displayName:"parking meter"},15:{name:"/m/0cvnqh",id:15,displayName:"bench"},16:{name:"/m/015p6",id:16,displayName:"bird"},17:{name:"/m/01yrx",id:17,displayName:"cat"},18:{name:"/m/0bt9lr",id:18,displayName:"dog"},19:{name:"/m/03k3r",id:19,displayName:"horse"},20:{name:"/m/07bgp",id:20,displayName:"sheep"},21:{name:"/m/01xq0k1",id:21,displayName:"cow"},22:{name:"/m/0bwd_0j",id:22,displayName:"elephant"},23:{name:"/m/01dws",id:23,displayName:"bear"},24:{name:"/m/0898b",id:24,displayName:"zebra"},25:{name:"/m/03bk1",id:25,displayName:"giraffe"},27:{name:"/m/01940j",id:27,displayName:"backpack"},28:{name:"/m/0hnnb",id:28,displayName:"umbrella"},31:{name:"/m/080hkjn",id:31,displayName:"handbag"},32:{name:"/m/01rkbr",id:32,displayName:"tie"},33:{name:"/m/01s55n",id:33,displayName:"suitcase"},34:{name:"/m/02wmf",id:34,displayName:"frisbee"},35:{name:"/m/071p9",id:35,displayName:"skis"},36:{name:"/m/06__v",id:36,displayName:"snowboard"},37:{name:"/m/018xm",id:37,displayName:"sports ball"},38:{name:"/m/02zt3",id:38,displayName:"kite"},39:{name:"/m/03g8mr",id:39,displayName:"baseball bat"},40:{name:"/m/03grzl",id:40,displayName:"baseball glove"},41:{name:"/m/06_fw",id:41,displayName:"skateboard"},42:{name:"/m/019w40",id:42,displayName:"surfboard"},43:{name:"/m/0dv9c",id:43,displayName:"tennis racket"},44:{name:"/m/04dr76w",id:44,displayName:"bottle"},46:{name:"/m/09tvcd",id:46,displayName:"wine glass"},47:{name:"/m/08gqpm",id:47,displayName:"cup"},48:{name:"/m/0dt3t",id:48,displayName:"fork"},49:{name:"/m/04ctx",id:49,displayName:"knife"},50:{name:"/m/0cmx8",id:50,displayName:"spoon"},51:{name:"/m/04kkgm",id:51,displayName:"bowl"},52:{name:"/m/09qck",id:52,displayName:"banana"},53:{name:"/m/014j1m",id:53,displayName:"apple"},54:{name:"/m/0l515",id:54,displayName:"sandwich"},55:{name:"/m/0cyhj_",id:55,displayName:"orange"},56:{name:"/m/0hkxq",id:56,displayName:"broccoli"},57:{name:"/m/0fj52s",id:57,displayName:"carrot"},58:{name:"/m/01b9xk",id:58,displayName:"hot dog"},59:{name:"/m/0663v",id:59,displayName:"pizza"},60:{name:"/m/0jy4k",id:60,displayName:"donut"},61:{name:"/m/0fszt",id:61,displayName:"cake"},62:{name:"/m/01mzpv",id:62,displayName:"chair"},63:{name:"/m/02crq1",id:63,displayName:"couch"},64:{name:"/m/03fp41",id:64,displayName:"potted plant"},65:{name:"/m/03ssj5",id:65,displayName:"bed"},67:{name:"/m/04bcr3",id:67,displayName:"dining table"},70:{name:"/m/09g1w",id:70,displayName:"toilet"},72:{name:"/m/07c52",id:72,displayName:"tv"},73:{name:"/m/01c648",id:73,displayName:"laptop"},74:{name:"/m/020lf",id:74,displayName:"mouse"},75:{name:"/m/0qjjc",id:75,displayName:"remote"},76:{name:"/m/01m2v",id:76,displayName:"keyboard"},77:{name:"/m/050k8",id:77,displayName:"cell 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e=this,[4,a.loadGraphModel(this.modelPath)];case 1:return e.model=m.sent(),n=i.zeros([1,300,300,3],"int32"),[4,this.model.executeAsync(n)];case 2:return t=m.sent(),[4,Promise.all(t.map((function(e){return e.data()})))];case 3:return m.sent(),t.map((function(e){return e.dispose()})),n.dispose(),[2]}}))}))},e.prototype.infer=function(e,a,t){return n(this,void 0,void 0,(function(){var n,d,s,o,r,l,p,c,y,u,f,b;return m(this,(function(m){switch(m.label){case 0:return n=i.tidy((function(){return e instanceof i.Tensor||(e=i.browser.fromPixels(e)),e.expandDims(0)})),d=n.shape[1],s=n.shape[2],[4,this.model.executeAsync(n)];case 1:return o=m.sent(),r=o[0].dataSync(),l=o[1].dataSync(),n.dispose(),i.dispose(o),p=this.calculateMaxScores(r,o[0].shape[1],o[0].shape[2]),c=p[0],y=p[1],u=i.getBackend(),"webgl"===i.getBackend()&&i.setBackend("cpu"),f=i.tidy((function(){var e=i.tensor2d(l,[o[1].shape[1],o[1].shape[3]]);return i.image.nonMaxSuppression(e,c,a,t,t)})),b=f.dataSync(),f.dispose(),u!==i.getBackend()&&i.setBackend(u),[2,this.buildDetectedObjects(s,d,l,c,b,y)]}}))}))},e.prototype.buildDetectedObjects=function(e,a,i,n,m,d){for(var s=m.length,o=[],r=0;r<s;r++){for(var l=[],p=0;p<4;p++)l[p]=i[4*m[r]+p];var c=l[0]*a,y=l[1]*e,u=l[2]*a,f=l[3]*e;l[0]=y,l[1]=c,l[2]=f-y,l[3]=u-c,o.push({bbox:l,class:t[d[m[r]]+1].displayName,score:n[m[r]]})}return o},e.prototype.calculateMaxScores=function(e,a,i){for(var n=[],m=[],t=0;t<a;t++){for(var d=Number.MIN_VALUE,s=-1,o=0;o<i;o++)e[t*i+o]>d&&(d=e[t*i+o],s=o);n[t]=d,m[t]=s}return[n,m]},e.prototype.detect=function(e,a,i){return void 0===a&&(a=20),void 0===i&&(i=.5),n(this,void 0,void 0,(function(){return m(this,(function(n){return[2,this.infer(e,a,i)]}))}))},e.prototype.dispose=function(){null!=this.model&&this.model.dispose()},e}();e.ObjectDetection=d,e.load=function(e){return void 0===e&&(e={}),n(this,void 0,void 0,(function(){var a,n,t;return m(this,(function(m){switch(m.label){case 0:if(null==i)throw new Error("Cannot find TensorFlow.js. If you are using a <script> tag, please also include @tensorflow/tfjs on the page before using this model.");if(a=e.base||"lite_mobilenet_v2",n=e.modelUrl,-1===["mobilenet_v1","mobilenet_v2","lite_mobilenet_v2"].indexOf(a))throw new Error("ObjectDetection constructed with invalid base model "+a+". Valid names are 'mobilenet_v1', 'mobilenet_v2' and 'lite_mobilenet_v2'.");return[4,(t=new d(a,n)).load()];case 1:return m.sent(),[2,t]}}))}))},e.version="2.2.0",Object.defineProperty(e,"__esModule",{value:!0})}));
+!function(e,a){"object"==typeof exports&&"undefined"!=typeof module?a(exports,require("@tensorflow/tfjs-converter"),require("@tensorflow/tfjs-core")):"function"==typeof define&&define.amd?define(["exports","@tensorflow/tfjs-converter","@tensorflow/tfjs-core"],a):a((e=e||self).cocoSsd=e.cocoSsd||{},e.tf,e.tf)}(this,(function(e,a,i){"use strict";function n(e,a,i,n){return new(i||(i=Promise))((function(m,t){function d(e){try{o(n.next(e))}catch(e){t(e)}}function s(e){try{o(n.throw(e))}catch(e){t(e)}}function o(e){e.done?m(e.value):new i((function(a){a(e.value)})).then(d,s)}o((n=n.apply(e,a||[])).next())}))}function m(e,a){var i,n,m,t,d={label:0,sent:function(){if(1&m[0])throw m[1];return m[1]},trys:[],ops:[]};return t={next:s(0),throw:s(1),return:s(2)},"function"==typeof Symbol&&(t[Symbol.iterator]=function(){return this}),t;function s(t){return function(s){return function(t){if(i)throw new TypeError("Generator is already 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t={1:{name:"/m/01g317",id:1,displayName:"person"},2:{name:"/m/0199g",id:2,displayName:"bicycle"},3:{name:"/m/0k4j",id:3,displayName:"car"},4:{name:"/m/04_sv",id:4,displayName:"motorcycle"},5:{name:"/m/05czz6l",id:5,displayName:"airplane"},6:{name:"/m/01bjv",id:6,displayName:"bus"},7:{name:"/m/07jdr",id:7,displayName:"train"},8:{name:"/m/07r04",id:8,displayName:"truck"},9:{name:"/m/019jd",id:9,displayName:"boat"},10:{name:"/m/015qff",id:10,displayName:"traffic light"},11:{name:"/m/01pns0",id:11,displayName:"fire hydrant"},13:{name:"/m/02pv19",id:13,displayName:"stop sign"},14:{name:"/m/015qbp",id:14,displayName:"parking 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i.image.nonMaxSuppression(e,c,a,t,t)})),b=f.dataSync(),f.dispose(),u!==i.getBackend()&&i.setBackend(u),[2,this.buildDetectedObjects(s,d,l,c,b,y)]}}))}))},e.prototype.buildDetectedObjects=function(e,a,i,n,m,d){for(var s=m.length,o=[],r=0;r<s;r++){for(var l=[],p=0;p<4;p++)l[p]=i[4*m[r]+p];var c=l[0]*a,y=l[1]*e,u=l[2]*a,f=l[3]*e;l[0]=y,l[1]=c,l[2]=f-y,l[3]=u-c,o.push({bbox:l,class:t[d[m[r]]+1].displayName,score:n[m[r]]})}return o},e.prototype.calculateMaxScores=function(e,a,i){for(var n=[],m=[],t=0;t<a;t++){for(var d=Number.MIN_VALUE,s=-1,o=0;o<i;o++)e[t*i+o]>d&&(d=e[t*i+o],s=o);n[t]=d,m[t]=s}return[n,m]},e.prototype.detect=function(e,a,i){return void 0===a&&(a=20),void 0===i&&(i=.5),n(this,void 0,void 0,(function(){return m(this,(function(n){return[2,this.infer(e,a,i)]}))}))},e.prototype.dispose=function(){null!=this.model&&this.model.dispose()},e}();e.ObjectDetection=d,e.load=function(e){return void 0===e&&(e={}),n(this,void 0,void 0,(function(){var a,n,t;return m(this,(function(m){switch(m.label){case 0:if(null==i)throw new Error("Cannot find TensorFlow.js. If you are using a <script> tag, please also include @tensorflow/tfjs on the page before using this model.");if(a=e.base||"lite_mobilenet_v2",n=e.modelUrl,-1===["mobilenet_v1","mobilenet_v2","lite_mobilenet_v2"].indexOf(a))throw new Error("ObjectDetection constructed with invalid base model "+a+". Valid names are 'mobilenet_v1', 'mobilenet_v2' and 'lite_mobilenet_v2'.");return[4,(t=new d(a,n)).load()];case 1:return m.sent(),[2,t]}}))}))},e.version="2.2.1",Object.defineProperty(e,"__esModule",{value:!0})}));
 //# sourceMappingURL=coco-ssd.min.js.map

dist/coco-ssd.node.js

@@ -497,3 +497,3 @@ /**
 // This code is auto-generated, do not modify this file!
-var version = '2.2.0';
+var version = '2.2.1';
 
@@ -500,0 +500,0 @@ /**

dist/version.d.ts

 /** @license See the LICENSE file. */
-declare const version = "2.2.0";
+declare const version = "2.2.1";
 export { version };

dist/version.js

@@ -5,4 +5,4 @@ "use strict";
 // This code is auto-generated, do not modify this file!
-var version = '2.2.0';
+var version = '2.2.1';
 exports.version = version;
 //# sourceMappingURL=version.js.map

package.json

 {
   "name": "@tensorflow-models/coco-ssd",
-  "version": "2.2.0",
+  "version": "2.2.1",
   "description": "Object detection model (coco-ssd) in TensorFlow.js",
@@ -5,0 +5,0 @@ "main": "dist/coco-ssd.node.js",

rollup.config.js

@@ -151,3 +151,3 @@ /**
       output: {
-        format: flatEsmFormat,
+        format: umdFormat,
         name,
@@ -154,0 +154,0 @@ extend,

New alerts

Minified code

Quality

This package contains minified code. This may be harmless in some cases where minified code is included in packaged libraries, however packages on npm should not minify code.

Found 1 instance in 1 package

Fixed alerts

Deprecated

Maintenance

The maintainer of the package marked it as deprecated. This could indicate that a single version should not be used, or that the package is no longer maintained and any new vulnerabilities will not be fixed.

Found 1 instance in 1 package

Improved metrics

Total package byte prevSize

206967

increased by0.12%

Lines of code

2667

increased by0.04%

Number of high maintenance alerts

0

decreased by-100%

Worsened metrics

Number of low quality alerts

3

increased by50%

No dependency changes