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upgrade bodypix to 3.0 api (#565)
* upgrade to 3.0 api ; * fix lint
1 parent b0ffa58 commit 66dc36b

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+1713
-587
lines changed

‎body-pix/demos/index.js

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@@ -14,6 +14,7 @@
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* limitations under the License.
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* =============================================================================
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*/
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import '@tensorflow/tfjs-backend-webgl';
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import * as bodyPix from '@tensorflow-models/body-pix';
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import dat from 'dat.gui';
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import Stats from 'stats.js';

‎body-pix/demos/package.json

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@@ -9,10 +9,11 @@
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"node": ">=8.9.0"
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},
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"dependencies": {
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"@tensorflow-models/body-pix": "2.0.2",
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"@tensorflow-models/body-pix": "file:../dist",
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"@tensorflow-models/posenet": "^2.1.3",
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"@tensorflow/tfjs-converter": "~1.2.1",
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"@tensorflow/tfjs-core": "~1.2.1",
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"@tensorflow/tfjs-backend-webgl": "~3.0.0-rc.1",
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"@tensorflow/tfjs-converter": "~3.0.0-rc.1",
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"@tensorflow/tfjs-core": "~3.0.0-rc.1",
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"stats.js": "0.17.0"
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},
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"scripts": {
@@ -54,4 +55,4 @@
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"eslintIgnore": [
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"dist/"
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]
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}
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}

‎body-pix/demos/yarn.lock

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Original file line numberDiff line numberDiff line change
@@ -742,31 +742,48 @@
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"@parcel/utils" "^1.11.0"
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physical-cpu-count "^2.0.0"
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"@tensorflow-models/[email protected]":
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version "2.0.2"
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resolved "https://registry.yarnpkg.com/@tensorflow-models/body-pix/-/body-pix-2.0.2.tgz#3c2c787a9621bbc40d4e20e23aad8b7e69f8c9c5"
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"@tensorflow-models/body-pix@file:../dist":
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version "0.0.0"
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"@tensorflow-models/posenet@^2.1.3":
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version "2.1.3"
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resolved "https://registry.yarnpkg.com/@tensorflow-models/posenet/-/posenet-2.1.3.tgz#09633e6e6e41d6c00d2ee7633632fb9322651463"
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version "1.2.7"
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"@tensorflow/[email protected]":
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version "3.0.0-rc.1"
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resolved "https://registry.yarnpkg.com/@tensorflow/tfjs-backend-cpu/-/tfjs-backend-cpu-3.0.0-rc.1.tgz#b02e05706b2d91ab601e7eb397b6ea60ac0a9e2e"
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dependencies:
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"@types/seedrandom" "2.4.27"
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seedrandom "2.4.3"
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"@tensorflow/tfjs-core@~1.2.1":
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version "1.2.8"
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"@tensorflow/tfjs-backend-webgl@~3.0.0-rc.1":
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version "3.0.0-rc.1"
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resolved "https://registry.yarnpkg.com/@tensorflow/tfjs-backend-webgl/-/tfjs-backend-webgl-3.0.0-rc.1.tgz#21aacedcef687d2bb075c7951ac9e4f57faa79e6"
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dependencies:
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"@tensorflow/tfjs-backend-cpu" "3.0.0-rc.1"
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"@types/offscreencanvas" "~2019.3.0"
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"@types/seedrandom" "2.4.27"
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"@types/webgl-ext" "0.0.30"
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"@types/webgl2" "0.0.5"
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seedrandom "2.4.3"
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"@tensorflow/tfjs-converter@~3.0.0-rc.1":
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version "3.0.0-rc.1"
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resolved "https://registry.yarnpkg.com/@tensorflow/tfjs-converter/-/tfjs-converter-3.0.0-rc.1.tgz#a15eb72ade80f7ae0e6403020763be0c5af6f2f7"
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"@tensorflow/tfjs-core@~3.0.0-rc.1":
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version "3.0.0-rc.1"
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resolved "https://registry.yarnpkg.com/@tensorflow/tfjs-core/-/tfjs-core-3.0.0-rc.1.tgz#0b5316871eef2a4c8aa149d154e6ea6bbc7b631e"
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dependencies:
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"@types/offscreencanvas" "~2019.3.0"
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"@types/seedrandom" "2.4.27"
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"@types/webgl-ext" "0.0.30"
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"@types/webgl2" "0.0.4"
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node-fetch "~2.1.2"
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node-fetch "~2.6.1"
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seedrandom "2.4.3"
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"@types/offscreencanvas@~2019.3.0":
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resolved "https://registry.yarnpkg.com/@types/webgl-ext/-/webgl-ext-0.0.30.tgz#0ce498c16a41a23d15289e0b844d945b25f0fb9d"
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integrity sha512-LKVgNmBxN0BbljJrVUwkxwRYqzsAEPcZOe6S2T6ZaBDIrFp0qu4FNlpc5sM1tGbXUYFgdVQIoeLk1Y1UoblyEg==
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"@types/[email protected].4":
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version "0.0.4"
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resolved "https://registry.yarnpkg.com/@types/webgl2/-/webgl2-0.0.4.tgz#c3b0f9d6b465c66138e84e64cb3bdf8373c2c279"
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"@types/[email protected].5":
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version "0.0.5"
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resolved "https://registry.yarnpkg.com/@types/webgl2/-/webgl2-0.0.5.tgz#dd925e20ab8ace80eb4b1e46fda5b109c508fb0d"
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abab@^2.0.0:
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version "2.0.2"
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resolved "https://registry.yarnpkg.com/node-addon-api/-/node-addon-api-1.7.1.tgz#cf813cd69bb8d9100f6bdca6755fc268f54ac492"
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node-fetch@~2.1.2:
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version "2.1.2"
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resolved "https://registry.yarnpkg.com/node-fetch/-/node-fetch-2.1.2.tgz#ab884e8e7e57e38a944753cec706f788d1768bb5"
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integrity sha1-q4hOjn5X44qUR1POxwb3iNF2i7U=
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node-fetch@~2.6.1:
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version "2.6.1"
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resolved "https://registry.yarnpkg.com/node-fetch/-/node-fetch-2.6.1.tgz#045bd323631f76ed2e2b55573394416b639a0052"
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integrity sha512-V4aYg89jEoVRxRb2fJdAg8FHvI7cEyYdVAh94HH0UIK8oJxUfkjlDQN9RbMx+bEjP7+ggMiFRprSti032Oipxw==
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node-forge@^0.7.1:
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version "0.7.6"

‎body-pix/karma.conf.js

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* =============================================================================
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*/
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const karmaTypescriptConfig = {
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tsconfig: 'tsconfig.test.json',
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// Disable coverage reports and instrumentation by default for tests
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coverageOptions: {instrumentation: false},
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reports: {},
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bundlerOptions: {
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sourceMap: true, // Process any non es5 code through
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// karma-typescript-es6-transform (babel)
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acornOptions: {ecmaVersion: 8},
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transforms: [
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require('karma-typescript-es6-transform')({
29+
presets: [
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// ensure we get es5 by adding IE 11 as a target
31+
['@babel/env', {'targets': {'ie': '11'}, 'loose': true}]
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]
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}),
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]
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}
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};
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module.exports = function(config) {
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config.set({
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frameworks: ['jasmine', 'karma-typescript'],
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files: [
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{pattern: './node_modules/@babel/polyfill/dist/polyfill.js'},
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'src/setup_test.ts', // Setup the environment for the tests.
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{pattern: 'src/**/*.ts'}
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],
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preprocessors: {
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'**/*.ts': ['karma-typescript'],
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},
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karmaTypescriptConfig:
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{tsconfig: 'tsconfig.test.json', compilerOptions: {module: 'commonjs'}},
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karmaTypescriptConfig,
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reporters: ['progress', 'karma-typescript'],
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browsers: ['Chrome'],
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browserStack: {

‎body-pix/package.json

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"url": "https://github.com/tensorflow/tfjs-models.git"
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},
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"peerDependencies": {
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"@tensorflow/tfjs-converter": "^1.3.1",
17-
"@tensorflow/tfjs-core": "^1.3.1"
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"@tensorflow/tfjs-backend-webgl": "^3.0.0-rc.1",
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"@tensorflow/tfjs-converter": "^3.0.0-rc.1",
18+
"@tensorflow/tfjs-core": "^3.0.0-rc.1"
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},
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"devDependencies": {
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"@tensorflow/tfjs-converter": "^1.3.1",
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"@tensorflow/tfjs-core": "^1.3.1",
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"@babel/polyfill": "^7.8.7",
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"@tensorflow/tfjs-backend-webgl": "^3.0.0-rc.1",
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"@tensorflow/tfjs-converter": "^3.0.0-rc.1",
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"@tensorflow/tfjs-core": "^3.0.0-rc.1",
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"@types/jasmine": "~2.5.53",
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"jasmine": "~3.2.0",
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"jasmine-core": "~3.1.0",
@@ -27,7 +30,8 @@
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"karma-chrome-launcher": "~2.2.0",
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"karma-firefox-launcher": "~1.1.0",
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"karma-jasmine": "~1.1.1",
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"karma-typescript": "~4.0.0",
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"karma-typescript": "~5.2.0",
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"karma-typescript-es6-transform": "^5.0.2",
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"rimraf": "~2.6.2",
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"rollup": "~0.58.2",
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"rollup-plugin-node-resolve": "~3.3.0",

‎body-pix/src/base_model.ts

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7272
partOffsets: tf.Tensor3D
7373
} {
7474
return tf.tidy(() => {
75-
const asFloat = this.preprocessInput(input.toFloat());
76-
const asBatch = asFloat.expandDims(0);
75+
const asFloat = this.preprocessInput(tf.cast(input, 'float32'));
76+
const asBatch = tf.expandDims(asFloat, 0);
7777
const results = this.model.predict(asBatch) as tf.Tensor4D[];
78-
const results3d: tf.Tensor3D[] = results.map(y => y.squeeze([0]));
78+
const results3d: tf.Tensor3D[] = results.map(y => tf.squeeze(y, [0]));
7979
const namedResults = this.nameOutputResults(results3d);
8080

8181
return {
82-
heatmapScores: namedResults.heatmap.sigmoid(),
82+
heatmapScores: tf.sigmoid(namedResults.heatmap),
8383
offsets: namedResults.offsets,
8484
displacementFwd: namedResults.displacementFwd,
8585
displacementBwd: namedResults.displacementBwd,

‎body-pix/src/body_pix_model.ts

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479479
APPLY_SIGMOID_ACTIVATION);
480480

481481
return {
482-
segmentation:
483-
toMaskTensor(scaledSegmentScores.squeeze(), segmentationThreshold),
482+
segmentation: toMaskTensor(
483+
tf.squeeze(scaledSegmentScores), segmentationThreshold),
484484
heatmapScores,
485485
offsets,
486486
displacementFwd,
@@ -640,7 +640,7 @@ export class BodyPix {
640640
}
641641

642642
const segmentation = toMaskTensor(
643-
scaledSegmentScores.squeeze(), config.segmentationThreshold);
643+
tf.squeeze(scaledSegmentScores), config.segmentationThreshold);
644644

645645
return {
646646
segmentation,
@@ -766,7 +766,7 @@ export class BodyPix {
766766
[[padding.top, padding.bottom], [padding.left, padding.right]],
767767
APPLY_SIGMOID_ACTIVATION);
768768
const segmentation =
769-
toMaskTensor(scaledSegmentScores.squeeze(), segmentationThreshold);
769+
toMaskTensor(tf.squeeze(scaledSegmentScores), segmentationThreshold);
770770
return {
771771
partSegmentation:
772772
decodePartSegmentation(segmentation, scaledPartHeatmapScore),
@@ -928,7 +928,7 @@ export class BodyPix {
928928

929929
const scaledLongOffsets = longOffsets;
930930
const segmentation = toMaskTensor(
931-
scaledSegmentScores.squeeze(), config.segmentationThreshold);
931+
tf.squeeze(scaledSegmentScores), config.segmentationThreshold);
932932
const partSegmentation =
933933
decodeOnlyPartSegmentation(scaledPartSegmentationScores);
934934
return {

‎body-pix/src/decode_part_map.ts

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@@ -25,15 +25,15 @@ import * as tf from '@tensorflow/tfjs-core';
2525
*/
2626
function toFlattenedOneHotPartMap(partHeatmapScores: tf.Tensor3D): tf.Tensor2D {
2727
const numParts = partHeatmapScores.shape[2];
28-
const partMapLocations = partHeatmapScores.argMax(2);
28+
const partMapLocations = tf.argMax(partHeatmapScores, 2);
2929

30-
const partMapFlattened = partMapLocations.reshape([-1]);
30+
const partMapFlattened = tf.reshape(partMapLocations, [-1]);
3131

3232
return tf.oneHot(partMapFlattened, numParts) as tf.Tensor2D;
3333
}
3434

3535
function clipByMask2d(image: tf.Tensor2D, mask: tf.Tensor2D): tf.Tensor2D {
36-
return image.mul(mask);
36+
return tf.mul(image, mask);
3737
}
3838

3939
/**
@@ -53,7 +53,8 @@ export function toMaskTensor(
5353
segmentScores: tf.Tensor2D, threshold: number): tf.Tensor2D {
5454
return tf.tidy(
5555
() =>
56-
(segmentScores.greater(tf.scalar(threshold)).toInt() as tf.Tensor2D));
56+
(tf.cast(tf.greater(
57+
segmentScores, tf.scalar(threshold)), 'int32') as tf.Tensor2D));
5758
}
5859

5960
/**
@@ -77,18 +78,18 @@ export function decodePartSegmentation(
7778
const [partMapHeight, partMapWidth, numParts] = partHeatmapScores.shape;
7879
return tf.tidy(() => {
7980
const flattenedMap = toFlattenedOneHotPartMap(partHeatmapScores);
80-
const partNumbers = tf.range(0, numParts, 1, 'int32').expandDims(1);
81+
const partNumbers = tf.expandDims(tf.range(0, numParts, 1, 'int32'), 1);
8182

8283
const partMapFlattened =
83-
flattenedMap.matMul(partNumbers as tf.Tensor2D).toInt();
84+
tf.cast(tf.matMul(flattenedMap, partNumbers as tf.Tensor2D), 'int32');
8485

85-
const partMap = partMapFlattened.reshape([partMapHeight, partMapWidth]);
86+
const partMap = tf.reshape(partMapFlattened, [partMapHeight, partMapWidth]);
8687

87-
const partMapShiftedUpForClipping = partMap.add(tf.scalar(1, 'int32'));
88+
const partMapShiftedUpForClipping = tf.add(partMap, tf.scalar(1, 'int32'));
8889

89-
return clipByMask2d(
90+
return tf.sub(clipByMask2d(
9091
partMapShiftedUpForClipping as tf.Tensor2D, segmentationMask)
91-
.sub(tf.scalar(1, 'int32'));
92+
, tf.scalar(1, 'int32'));
9293
});
9394
}
9495

@@ -97,11 +98,11 @@ export function decodeOnlyPartSegmentation(partHeatmapScores: tf.Tensor3D):
9798
const [partMapHeight, partMapWidth, numParts] = partHeatmapScores.shape;
9899
return tf.tidy(() => {
99100
const flattenedMap = toFlattenedOneHotPartMap(partHeatmapScores);
100-
const partNumbers = tf.range(0, numParts, 1, 'int32').expandDims(1);
101+
const partNumbers = tf.expandDims(tf.range(0, numParts, 1, 'int32'), 1);
101102

102103
const partMapFlattened =
103-
flattenedMap.matMul(partNumbers as tf.Tensor2D).toInt();
104+
tf.cast(tf.matMul(flattenedMap, partNumbers as tf.Tensor2D), 'int32');
104105

105-
return partMapFlattened.reshape([partMapHeight, partMapWidth]);
106+
return tf.reshape(partMapFlattened, [partMapHeight, partMapWidth]);
106107
});
107108
}

‎body-pix/src/mobilenet.ts

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -22,7 +22,7 @@ import {BaseModel} from './base_model';
2222
export class MobileNet extends BaseModel {
2323
preprocessInput(input: tf.Tensor3D): tf.Tensor3D {
2424
// Normalize the pixels [0, 255] to be between [-1, 1].
25-
return tf.tidy(() => tf.div(input, 127.5).sub(1.0));
25+
return tf.tidy(() => tf.sub(tf.div(input, 127.5), 1.0));
2626
}
2727

2828
nameOutputResults(results: tf.Tensor3D[]) {

‎body-pix/src/multi_person/decode_instance_masks.ts

Lines changed: 4 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -26,16 +26,15 @@ import {decodeMultipleMasksWebGl} from './decode_multiple_masks_webgl';
2626
export function toPersonKSegmentation(
2727
segmentation: tf.Tensor2D, k: number): tf.Tensor2D {
2828
return tf.tidy(
29-
() => (segmentation.equal(tf.scalar(k)).toInt() as tf.Tensor2D));
29+
() => (tf.cast(tf.equal(
30+
segmentation, tf.scalar(k)), 'int32') as tf.Tensor2D));
3031
}
3132

3233
export function toPersonKPartSegmentation(
3334
segmentation: tf.Tensor2D, bodyParts: tf.Tensor2D, k: number): tf.Tensor2D {
3435
return tf.tidy(
35-
() => segmentation.equal(tf.scalar(k))
36-
.toInt()
37-
.mul(bodyParts.add(1))
38-
.sub(1));
36+
() => tf.sub(tf.mul(tf.cast(tf.equal(
37+
segmentation, tf.scalar(k)), 'int32'), tf.add(bodyParts, 1)), 1));
3938
}
4039

4140
function isWebGlBackend() {

‎body-pix/src/multi_person/decode_multiple_masks_webgl.ts

Lines changed: 4 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -16,6 +16,7 @@
1616
*/
1717

1818
import * as tf from '@tensorflow/tfjs-core';
19+
import * as tf_webgl from '@tensorflow/tfjs-backend-webgl';
1920

2021
import {NUM_KEYPOINTS} from '../keypoints';
2122
import {Padding, Pose} from '../types';
@@ -33,7 +34,7 @@ export function decodeMultipleMasksWebGl(
3334
const [outHeight, outWidth] = longOffsets.shape.slice(0, 2);
3435

3536
const shapedLongOffsets: tf.Tensor4D =
36-
longOffsets.reshape([outHeight, outWidth, 2, NUM_KEYPOINTS]);
37+
tf.reshape(longOffsets, [outHeight, outWidth, 2, NUM_KEYPOINTS]);
3738

3839
// Make pose tensor of shape [MAX_NUM_PEOPLE, NUM_KEYPOINTS, 3] where
3940
// the last 3 coordinates correspond to the score, h and w coordinate of that
@@ -58,7 +59,7 @@ export function decodeMultipleMasksWebGl(
5859

5960
const {top: padT, left: padL} = padding;
6061

61-
const program: tf.webgl.GPGPUProgram = {
62+
const program: tf_webgl.GPGPUProgram = {
6263
variableNames: ['segmentation', 'longOffsets', 'poses'],
6364
outputShape: [origHeight, origWidth],
6465
userCode: `
@@ -154,7 +155,7 @@ export function decodeMultipleMasksWebGl(
154155
}
155156
`
156157
};
157-
const webglBackend = tf.backend() as tf.webgl.MathBackendWebGL;
158+
const webglBackend = tf.backend() as tf_webgl.MathBackendWebGL;
158159
return webglBackend.compileAndRun(
159160
program, [segmentation, shapedLongOffsets, posesTensor]);
160161
}

‎body-pix/src/resnet.ts

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -23,7 +23,7 @@ const imageNetMean = [-123.15, -115.90, -103.06];
2323

2424
export class ResNet extends BaseModel {
2525
preprocessInput(input: tf.Tensor3D): tf.Tensor3D {
26-
return input.add(imageNetMean);
26+
return tf.add(input, imageNetMean);
2727
}
2828

2929
nameOutputResults(results: tf.Tensor3D[]) {

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