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

automl/snippets/package.json

@@ -12,12 +12,13 @@
   "repository": "googleapis/nodejs-automl",
   "private": true,
   "scripts": {
-    "test": "mocha --timeout 600000"
+    "test": "mocha --timeout 600000 --recursive"
   },
   "dependencies": {
     "@google-cloud/automl": "^0.2.0",
     "mathjs": "^5.5.0",
-    "yargs": "^13.2.1"
+    "yargs": "^13.2.1",
+    "execa":"^1.0.0"
   },
   "devDependencies": {
     "mocha": "^6.0.1",

automl/snippets/test/automlVisionObjectDetectionDataset.v1beta1.test.js

@@ -0,0 +1,82 @@
+/**
+ * Copyright 2019, Google LLC
+ * 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.
+ */
+
+'use strict';
+
+const {assert} = require('chai');
+const cp = require('child_process');
+
+const execSync = cmd => cp.execSync(cmd, {encoding: 'utf-8'});
+
+/** Tests for AutoML Vision Object Detection "Dataset API" sample. */
+// TODO(developer): Before running the test cases,
+// set the environment variables PROJECT_ID, REGION_NAME and
+// change the value of datasetId
+const projectId = 'nodejs-docs-samples';
+const computeRegion = 'us-central1';
+const outputPath = 'gs://nodejs-docs-samples/VISION_OBJECT_DETECTION/';
+const datasetName = 'test_vision_create_dataset';
+const filter = 'imageObjectDetectionDatasetMetadata:*';
+const datasetId = 'ICN3946265060617537378';
+const importDataCsv = 'gs://nodejs-docs-samples-vcm/flowerTraindata20lines.csv';
+
+describe('Vision Object Detection DatasetAPI', () => {
+  it.skip(`should create, import and delete a dataset`, async () => {
+    // Create dataset
+    let output = await execSync(
+      `node vision/object-detection/create-dataset.v1beta1.js "${projectId}" "${computeRegion}" "${datasetName}"`
+    );
+    const parsedOut = output.split('\n');
+    const outputDatasetId = parsedOut[1].split(':')[1].trim();
+    assert.match(output, /Dataset display name:/);
+
+    // Import data
+    output = await execSync(
+      `node vision/object-detection/import-data.v1beta1.js "${projectId}" "${computeRegion}" "${outputDatasetId}" "${importDataCsv}"`
+    );
+    assert.match(output, /Processing import.../);
+
+    // Delete dataset
+    output = await execSync(
+      `node vision/object-detection/delete-dataset.v1beta1.js "${projectId}" "${computeRegion}" "${outputDatasetId}"`
+    );
+    assert.match(output, /Dataset delete details:/);
+  });
+
+  it.skip(`should list datasets`, async () => {
+    // List datasets
+    const output = await execSync(
+      `node vision/object-detection/list-datasets.v1beta1.js "${projectId}" "${computeRegion}" "${filter}"`
+    );
+    assert.match(output, /List of datasets:/);
+  });
+
+  it.skip(`should get preexisting dataset`, async () => {
+    // Get dataset
+    const output = await execSync(
+      `node vision/object-detection/get-dataset.v1beta1.js "${projectId}" "${computeRegion}" "${datasetId}"`
+    );
+    assert.match(output, /Dataset display name:/);
+  });
+
+  it.skip(`should export dataset`, async () => {
+    // Export data
+    const outputUri = outputPath + datasetId;
+    const output = await execSync(
+      `node vision/object-detection/export-data.v1beta1.js "${projectId}" "${computeRegion}" "${datasetId}" "${outputUri}"`
+    );
+    assert.match(output, /Processing export.../);
+  });
+});

automl/snippets/test/automlVisionObjectDetectionModel.v1beta1.test.js

@@ -0,0 +1,127 @@
+/**
+ * Copyright 2019, Google LLC
+ * 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.
+ */
+
+'use strict';
+
+const {assert} = require('chai');
+const cp = require('child_process');
+
+const execSync = cmd => cp.execSync(cmd, {encoding: 'utf-8'});
+
+/** Tests for AutoML Vision Object Detection "Model API" sample. */
+// TODO(developer): Before running the test cases,
+// set the environment variables PROJECT_ID, REGION_NAME and
+// change the value of datasetId, deployModelId and  undeployModelId
+const projectId = 'nodejs-docs-samples';
+const computeRegion = 'us-central1';
+const filter = 'imageObjectDetectionModelMetadata:*';
+const datasetId = 'ICN3217071205693347964';
+const testModelName = 'birds2_201804101601_base';
+const deployModelId = 'IOD1728502647608049664';
+const undeployModelId = 'IOD3348109663601164288';
+
+describe(' Vision Object Detection ModelAPI', () => {
+  it.skip(`should create a model`, async () => {
+    let output = await execSync(
+      `node vision/object-detection/create-model.v1beta1.js "${projectId}" "${computeRegion}" "${datasetId}" "${testModelName}"`
+    );
+    const operationName = output
+      .split('\n')[0]
+      .split(':')[1]
+      .trim();
+    assert.match(output, /Training started.../);
+
+    output = await execSync(
+      `node vision/object-detection/get-operation-status.v1beta1.js "${operationName}"`
+    );
+    assert.match(output, /Operation details:/);
+  });
+
+  it.skip(`should list models, get and delete a model. list, get and display model
+    evaluations from preexisting models`, async () => {
+    // List models
+    let output = await execSync(
+      `node vision/object-detection/list-models.v1beta1.js "${projectId}" "${computeRegion}" "${filter}"`
+    );
+    const parsedOut = output.split('\n');
+    const outputModelId = parsedOut[3].split(':')[1].trim();
+    assert.match(output, /List of models:/);
+
+    // Get Model
+    output = await execSync(
+      `node vision/object-detection/get-model.v1beta1.js "${projectId}" "${computeRegion}" "${outputModelId}"`
+    );
+    assert.match(output, /Model name:/);
+
+    // List model evaluation
+    output = await execSync(
+      `node vision/object-detection/list-model-evaluations.v1beta1.js "${projectId}" "${computeRegion}" "${outputModelId}"`
+    );
+    const parsedModelEvaluation = output.split('\n');
+    const modelEvaluationId = parsedModelEvaluation[3].split(':')[1].trim();
+    assert.match(output, /Model evaluation Id:/);
+
+    // Get model evaluation
+    output = await execSync(
+      `node vision/object-detection/get-model-evaluation.v1beta1.js "${projectId}" "${computeRegion}" "${outputModelId}"` +
+        ` "${modelEvaluationId}"`
+    );
+    assert.match(output, /Model evaluation Id:/);
+
+    // Display evaluation
+    output = await execSync(
+      `node vision/object-detection/display-evaluation.v1beta1.js "${projectId}" "${computeRegion}" "${outputModelId}" `
+    );
+    assert.match(output, /Model Evaluation ID:/);
+
+    // Delete Model
+    output = await execSync(
+      `node vision/object-detection/delete-model.v1beta1.js "${projectId}" "${computeRegion}" "${outputModelId}"`
+    );
+    assert.match(output, /Model delete details:/);
+  });
+
+  it.skip(`should list and get operation status`, async () => {
+    // List operation status
+    let output = await execSync(
+      `node vision/object-detection/list-operations-status.v1beta1.js`
+    );
+    const parsedOut = output.split('\n');
+    const operationFullId = parsedOut[3].split(':')[1].trim();
+
+    // Get operation status
+    // Poll operation status, here confirming that operation is not complete yet
+    output = await execSync(
+      `node vision/object-detection/get-operation-status.v1beta1.js "${operationFullId}"`
+    );
+    assert.match(output, /Operation details:/);
+  });
+
+  it.skip(`should deploy the model`, async () => {
+    // Deploy the model
+    const output = await execSync(
+      `node vision/object-detection/deploy-model.v1beta1.js "${projectId}" "${computeRegion}" ${deployModelId}`
+    );
+    assert.match(output, /Name:/);
+  });
+
+  it.skip(`should undeploy the model`, async () => {
+    // Undeploy the model
+    const output = await execSync(
+      `node vision/object-detection/undeploy-model.v1beta1.js "${projectId}" "${computeRegion}" ${undeployModelId}`
+    );
+    assert.match(output, /Name:/);
+  });
+});

automl/snippets/test/automlVisionObjectDetectionPredict.v1beta1.test.js

@@ -0,0 +1,40 @@
+/**
+ * Copyright 2019, Google LLC
+ * 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.
+ */
+
+'use strict';
+
+const {assert} = require('chai');
+const execa = require('execa');
+
+/** Tests for AutoML Vision Object Detection "Prediction API" sample. */
+
+// TODO(developer): Before running the test cases,
+// set the environment variables PROJECT_ID, REGION_NAME and change the value of modelId
+const projectId = 'nodejs-docs-samples';
+const computeRegion = 'us-central1';
+const modelId = '';
+const filePath = './resource/songbird.jpg';
+
+const exec = async cmd => (await execa.shell(cmd)).stdout;
+
+describe.skip('Vision Object Detection PredictionAPI', () => {
+  it(`should run prediction from preexisting model`, async () => {
+    // Run prediction on 'salad.jpg' in resource folder
+    const output = await exec(
+      `node vision/object-detection/predict.v1beta1.js "${projectId}" "${computeRegion}" "${modelId}" "${filePath}"`
+    );
+    assert.match(output, /Prediction results:/);
+  });
+});

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

@@ -0,0 +1,71 @@
+/**
+ * Copyright 2019, Google LLC
+ * 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.
+ */
+
+`use strict`;
+function main(
+  projectId = 'YOUR_PROJECT_ID',
+  computeRegion = 'YOUR_REGION_NAME',
+  datasetName = 'YOUR_DATASET_NAME'
+) {
+  // [START automl_vision_object_detection_create_dataset]
+  /**
+   * Demonstrates using the AutoML client to create a dataset.
+   * TODO(developer): Uncomment the following lines before running the sample.
+   */
+  // const projectId = '[PROJECT_ID]' e.g., "my-gcloud-project";
+  // const computeRegion = '[REGION_NAME]' e.g., "us-central1";
+  // const datasetName = '[DATASET_NAME]' e.g., "myDataset";
+
+  //Imports the Google Cloud Automl library
+  const {AutoMlClient} = require('@google-cloud/automl').v1beta1;
+
+  // Instantiates a client
+  const automlClient = new AutoMlClient();
+  const util = require(`util`);
+
+  async function createDataset() {
+    // A resource that represents Google Cloud Platform location.
+    const projectLocation = automlClient.locationPath(projectId, computeRegion);
+
+    // Set dataset name and metadata.
+    const myDataset = {
+      displayName: datasetName,
+      imageObjectDetectionDatasetMetadata: {},
+    };
+
+    // Create a dataset with the dataset metadata in the region.
+    const [response] = await automlClient.createDataset({
+      parent: projectLocation,
+      dataset: myDataset,
+    });
+
+    //const dataset = response[0];
+    // Display the dataset information.
+    console.log(`Dataset name: ${response.name}`);
+    console.log(`Dataset Id: ${response.name.split(`/`).pop(-1)}`);
+    console.log(`Dataset display name: ${response.displayName}`);
+    console.log(`Dataset example count: ${response.exampleCount}`);
+    console.log(
+      `Image object detection dataset metadata: ${util.inspect(
+        response.imageObjectDetectionDatasetMetadata,
+        false,
+        null
+      )}`
+    );
+  }
+  createDataset();
+  // [END automl_vision_object_detection_create_dataset]
+}
+main(...process.argv.slice(2));