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docs(samples): add vision beta samples (#157)
* Vision beta samples * Vision beta samples * Vision beta samples * Vision beta samples * fixing tests * fixing tests * fixing tests * fixing tests * fixing tests
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‎automl/package.json

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"repository": "googleapis/nodejs-automl",
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"private": true,
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"scripts": {
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"test": "mocha --timeout 600000"
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"test": "mocha --timeout 600000 --recursive"
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},
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"dependencies": {
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"@google-cloud/automl": "^0.2.0",
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"mathjs": "^5.5.0",
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"yargs": "^13.2.1"
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"yargs": "^13.2.1",
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"execa":"^1.0.0"
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},
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"devDependencies": {
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"mocha": "^6.0.1",

‎automl/test/automlVisionObjectDetectionDataset.v1beta1.test.js

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/**
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* Copyright 2019, Google LLC
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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'use strict';
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const {assert} = require('chai');
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const cp = require('child_process');
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const execSync = cmd => cp.execSync(cmd, {encoding: 'utf-8'});
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/** Tests for AutoML Vision Object Detection "Dataset API" sample. */
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// TODO(developer): Before running the test cases,
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// set the environment variables PROJECT_ID, REGION_NAME and
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// change the value of datasetId
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const projectId = 'nodejs-docs-samples';
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const computeRegion = 'us-central1';
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const outputPath = 'gs://nodejs-docs-samples/VISION_OBJECT_DETECTION/';
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const datasetName = 'test_vision_create_dataset';
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const filter = 'imageObjectDetectionDatasetMetadata:*';
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const datasetId = 'ICN3946265060617537378';
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const importDataCsv = 'gs://nodejs-docs-samples-vcm/flowerTraindata20lines.csv';
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describe('Vision Object Detection DatasetAPI', () => {
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it.skip(`should create, import and delete a dataset`, async () => {
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// Create dataset
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let output = await execSync(
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`node vision/object-detection/create-dataset.v1beta1.js "${projectId}" "${computeRegion}" "${datasetName}"`
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);
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const parsedOut = output.split('\n');
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const outputDatasetId = parsedOut[1].split(':')[1].trim();
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assert.match(output, /Dataset display name:/);
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// Import data
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output = await execSync(
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`node vision/object-detection/import-data.v1beta1.js "${projectId}" "${computeRegion}" "${outputDatasetId}" "${importDataCsv}"`
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);
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assert.match(output, /Processing import.../);
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// Delete dataset
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output = await execSync(
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`node vision/object-detection/delete-dataset.v1beta1.js "${projectId}" "${computeRegion}" "${outputDatasetId}"`
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);
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assert.match(output, /Dataset delete details:/);
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});
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it.skip(`should list datasets`, async () => {
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// List datasets
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const output = await execSync(
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`node vision/object-detection/list-datasets.v1beta1.js "${projectId}" "${computeRegion}" "${filter}"`
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);
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assert.match(output, /List of datasets:/);
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});
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it.skip(`should get preexisting dataset`, async () => {
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// Get dataset
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const output = await execSync(
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`node vision/object-detection/get-dataset.v1beta1.js "${projectId}" "${computeRegion}" "${datasetId}"`
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);
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assert.match(output, /Dataset display name:/);
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});
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it.skip(`should export dataset`, async () => {
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// Export data
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const outputUri = outputPath + datasetId;
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const output = await execSync(
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`node vision/object-detection/export-data.v1beta1.js "${projectId}" "${computeRegion}" "${datasetId}" "${outputUri}"`
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);
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assert.match(output, /Processing export.../);
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});
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});

‎automl/test/automlVisionObjectDetectionModel.v1beta1.test.js

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/**
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* Copyright 2019, Google LLC
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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'use strict';
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const {assert} = require('chai');
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const cp = require('child_process');
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const execSync = cmd => cp.execSync(cmd, {encoding: 'utf-8'});
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/** Tests for AutoML Vision Object Detection "Model API" sample. */
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// TODO(developer): Before running the test cases,
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// set the environment variables PROJECT_ID, REGION_NAME and
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// change the value of datasetId, deployModelId and undeployModelId
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const projectId = 'nodejs-docs-samples';
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const computeRegion = 'us-central1';
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const filter = 'imageObjectDetectionModelMetadata:*';
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const datasetId = 'ICN3217071205693347964';
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const testModelName = 'birds2_201804101601_base';
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const deployModelId = 'IOD1728502647608049664';
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const undeployModelId = 'IOD3348109663601164288';
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describe(' Vision Object Detection ModelAPI', () => {
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it.skip(`should create a model`, async () => {
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let output = await execSync(
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`node vision/object-detection/create-model.v1beta1.js "${projectId}" "${computeRegion}" "${datasetId}" "${testModelName}"`
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);
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const operationName = output
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.split('\n')[0]
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.split(':')[1]
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.trim();
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assert.match(output, /Training started.../);
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output = await execSync(
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`node vision/object-detection/get-operation-status.v1beta1.js "${operationName}"`
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);
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assert.match(output, /Operation details:/);
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});
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it.skip(`should list models, get and delete a model. list, get and display model
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evaluations from preexisting models`, async () => {
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// List models
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let output = await execSync(
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`node vision/object-detection/list-models.v1beta1.js "${projectId}" "${computeRegion}" "${filter}"`
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);
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const parsedOut = output.split('\n');
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const outputModelId = parsedOut[3].split(':')[1].trim();
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assert.match(output, /List of models:/);
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// Get Model
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output = await execSync(
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`node vision/object-detection/get-model.v1beta1.js "${projectId}" "${computeRegion}" "${outputModelId}"`
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);
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assert.match(output, /Model name:/);
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// List model evaluation
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output = await execSync(
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`node vision/object-detection/list-model-evaluations.v1beta1.js "${projectId}" "${computeRegion}" "${outputModelId}"`
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);
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const parsedModelEvaluation = output.split('\n');
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const modelEvaluationId = parsedModelEvaluation[3].split(':')[1].trim();
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assert.match(output, /Model evaluation Id:/);
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// Get model evaluation
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output = await execSync(
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`node vision/object-detection/get-model-evaluation.v1beta1.js "${projectId}" "${computeRegion}" "${outputModelId}"` +
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` "${modelEvaluationId}"`
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);
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assert.match(output, /Model evaluation Id:/);
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// Display evaluation
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output = await execSync(
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`node vision/object-detection/display-evaluation.v1beta1.js "${projectId}" "${computeRegion}" "${outputModelId}" `
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);
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assert.match(output, /Model Evaluation ID:/);
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// Delete Model
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output = await execSync(
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`node vision/object-detection/delete-model.v1beta1.js "${projectId}" "${computeRegion}" "${outputModelId}"`
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);
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assert.match(output, /Model delete details:/);
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});
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it.skip(`should list and get operation status`, async () => {
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// List operation status
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let output = await execSync(
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`node vision/object-detection/list-operations-status.v1beta1.js`
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);
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const parsedOut = output.split('\n');
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const operationFullId = parsedOut[3].split(':')[1].trim();
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// Get operation status
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// Poll operation status, here confirming that operation is not complete yet
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output = await execSync(
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`node vision/object-detection/get-operation-status.v1beta1.js "${operationFullId}"`
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);
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assert.match(output, /Operation details:/);
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});
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it.skip(`should deploy the model`, async () => {
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// Deploy the model
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const output = await execSync(
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`node vision/object-detection/deploy-model.v1beta1.js "${projectId}" "${computeRegion}" ${deployModelId}`
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);
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assert.match(output, /Name:/);
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});
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it.skip(`should undeploy the model`, async () => {
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// Undeploy the model
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const output = await execSync(
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`node vision/object-detection/undeploy-model.v1beta1.js "${projectId}" "${computeRegion}" ${undeployModelId}`
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);
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assert.match(output, /Name:/);
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});
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});

‎automl/test/automlVisionObjectDetectionPredict.v1beta1.test.js

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/**
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* Copyright 2019, Google LLC
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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'use strict';
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const {assert} = require('chai');
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const execa = require('execa');
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/** Tests for AutoML Vision Object Detection "Prediction API" sample. */
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// TODO(developer): Before running the test cases,
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// set the environment variables PROJECT_ID, REGION_NAME and change the value of modelId
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const projectId = 'nodejs-docs-samples';
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const computeRegion = 'us-central1';
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const modelId = '';
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const filePath = './resource/songbird.jpg';
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const exec = async cmd => (await execa.shell(cmd)).stdout;
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describe.skip('Vision Object Detection PredictionAPI', () => {
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it(`should run prediction from preexisting model`, async () => {
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// Run prediction on 'salad.jpg' in resource folder
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const output = await exec(
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`node vision/object-detection/predict.v1beta1.js "${projectId}" "${computeRegion}" "${modelId}" "${filePath}"`
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);
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assert.match(output, /Prediction results:/);
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});
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});

‎automl/vision/object-detection/create-dataset.v1beta1.js

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/**
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* Copyright 2019, Google LLC
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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`use strict`;
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function main(
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projectId = 'YOUR_PROJECT_ID',
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computeRegion = 'YOUR_REGION_NAME',
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datasetName = 'YOUR_DATASET_NAME'
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) {
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// [START automl_vision_object_detection_create_dataset]
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/**
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* Demonstrates using the AutoML client to create a dataset.
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* TODO(developer): Uncomment the following lines before running the sample.
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*/
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// const projectId = '[PROJECT_ID]' e.g., "my-gcloud-project";
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// const computeRegion = '[REGION_NAME]' e.g., "us-central1";
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// const datasetName = '[DATASET_NAME]' e.g., "myDataset";
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//Imports the Google Cloud Automl library
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const {AutoMlClient} = require('@google-cloud/automl').v1beta1;
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// Instantiates a client
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const automlClient = new AutoMlClient();
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const util = require(`util`);
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async function createDataset() {
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// A resource that represents Google Cloud Platform location.
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const projectLocation = automlClient.locationPath(projectId, computeRegion);
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// Set dataset name and metadata.
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const myDataset = {
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displayName: datasetName,
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imageObjectDetectionDatasetMetadata: {},
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};
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// Create a dataset with the dataset metadata in the region.
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const [response] = await automlClient.createDataset({
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parent: projectLocation,
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dataset: myDataset,
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});
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//const dataset = response[0];
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// Display the dataset information.
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console.log(`Dataset name: ${response.name}`);
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console.log(`Dataset Id: ${response.name.split(`/`).pop(-1)}`);
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console.log(`Dataset display name: ${response.displayName}`);
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console.log(`Dataset example count: ${response.exampleCount}`);
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console.log(
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`Image object detection dataset metadata: ${util.inspect(
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response.imageObjectDetectionDatasetMetadata,
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false,
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null
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)}`
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);
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}
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createDataset();
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// [END automl_vision_object_detection_create_dataset]
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}
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main(...process.argv.slice(2));

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