@tensorflow-models/body-pix
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Pretrained BodyPix model in TensorFlow.js
45 lines • 2.3 kB
JavaScript
;
/**
* @license
* Copyright 2019 Google Inc. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
* =============================================================================
*/
Object.defineProperty(exports, "__esModule", { value: true });
var tf = require("@tensorflow/tfjs-core");
var argmax2d_1 = require("./argmax2d");
describe('argmax2d', function () {
it('x = [2, 2, 1]', function () {
var input = tf.tensor3d([1, 2, 0, 3], [2, 2, 1]);
var result = (0, argmax2d_1.argmax2d)(input);
var expectedResult = tf.tensor2d([1, 1], [1, 2], 'int32');
tf.test_util.expectArraysClose(result.dataSync(), expectedResult.dataSync());
});
it('x = [3, 3, 1]', function () {
var input1 = tf.tensor3d([1, 2, 0, 3, 4, -1, 2, 9, 6], [3, 3, 1]);
var input2 = tf.tensor3d([.5, .2, .9, 4.3, .2, .7, .6, -0.11, 1.4], [3, 3, 1]);
tf.test_util.expectArraysClose((0, argmax2d_1.argmax2d)(input1).dataSync(), tf.tensor2d([2, 1], [1, 2], 'int32').dataSync());
tf.test_util.expectArraysClose((0, argmax2d_1.argmax2d)(input2).dataSync(), tf.tensor2d([1, 0], [1, 2], 'int32').dataSync());
});
it('x = [3, 3, 3]', function () {
var input1 = tf.tensor3d([1, 2, 0, 3, 4, -1, 2, 9, 6], [3, 3, 1]);
var input2 = tf.tensor3d([.5, .2, .9, 4.3, .2, .7, .6, -.11, 1.4], [3, 3, 1]);
var input3 = tf.tensor3d([4, .2, .8, .1, 6, .6, .3, 11, .6], [3, 3, 1]);
var input = tf.concat([input1, input2, input3], 2);
var result = (0, argmax2d_1.argmax2d)(input);
var expectedResult = tf.tensor2d([2, 1, 1, 0, 2, 1], [3, 2], 'int32');
tf.test_util.expectArraysClose(result.dataSync(), expectedResult.dataSync());
});
});
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