docs(samples): add video-intelligence beta samples (#156)

* Adding video-intelligence beta samples

* Skipping tests till fixed

automl/snippets/test/automlVideoIntelligenceClassificationDataset.v1beta1.test.js

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+/**
+ * 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 Video Intelligence Classification "Dataset API" sample. */
+
+const cmdDataset = 'node automlVideoIntelligenceDataset.js';
+
+// TODO(developer): Before running the test cases,
+// set the environment variables PROJECT_ID, REGION_NAME and
+// change the value of datasetId
+const projectId = process.env.PROJECT_ID;
+//const computeRegion = process.env.REGION_NAME;
+const bucket = projectId + '-video';
+const datasetName = 'test_video_dataset';
+const filter = 'videoClassificationDatasetMetadata:*';
+const datasetId = 'VCN1802794449273618432';
+const importDataCsv = 'gs://automl-video-demo-data/hmdb_split1.csv';
+
+const exec = async cmd => (await execa.shell(cmd)).stdout;
+
+describe.skip(`DatasetAPI`, () => {
+  it(`should create, import and delete a dataset`, async () => {
+    // Create dataset
+    let output = await exec(`${cmdDataset} create-dataset "${datasetName}"`);
+    const parsedOut = output.split('\n');
+    const outputDatasetId = parsedOut[1].split(':')[1].trim();
+    assert.match(output, /Dataset display name:/);
+
+    // Import data
+    output = await exec(
+      `${cmdDataset} import-data "${outputDatasetId}" "${importDataCsv}"`
+    );
+    assert.match(output, /Processing import.../);
+
+    // Delete dataset
+    output = await exec(`${cmdDataset} delete-dataset "${outputDatasetId}"`);
+    assert.match(output, /Dataset delete details:/);
+  });
+
+  it(`should list datasets`, async () => {
+    // List dataset
+    const output = await exec(`${cmdDataset} list-datasets "${filter}"`);
+    assert.match(output, /List of datasets:/);
+  });
+
+  it(`should get preexisting dataset`, async () => {
+    // Get dataset
+    const output = await exec(`${cmdDataset} get-dataset "${datasetId}"`);
+    assert.match(output, /Dataset display name:/);
+  });
+
+  it(`should export dataset`, async () => {
+    // Export data
+    const outputUri = 'gs://' + bucket + '/' + datasetId;
+    const output = await exec(
+      `${cmdDataset} export-data "${datasetId}" "${outputUri}"`
+    );
+    assert.match(output, /Processing export.../);
+  });
+});

automl/snippets/test/automlVideoIntelligenceClassificationModel.v1beta1.test.js

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+/**
+ * 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 Video Intelligence Classification "Model API" sample. */
+
+const cmdModel = 'node automlVideoIntelligenceModel.js';
+
+// TODO(developer): Before running the test cases,
+// set the environment variables PROJECT_ID, REGION_NAME and
+// change the values of datasetId
+//const projectId = process.env.PROJECT_ID;
+//const computeRegion = process.env.REGION_NAME;
+const filter = 'videoClassificationModelMetadata:*';
+const datasetId = 'VCN1653190499151904768';
+const testModelName = 'test_video_model';
+
+const exec = async cmd => (await execa.shell(cmd)).stdout;
+
+describe.skip(`Video Intelligence ModelAPI`, () => {
+  it(`should create a model`, async () => {
+    // Create model
+    let output = await exec(
+      `${cmdModel} create-model "${datasetId}" "${testModelName}"`
+    );
+    const operationName = output
+      .split('\n')[0]
+      .split(':')[1]
+      .trim();
+    assert.match(output, /Training started.../);
+
+    output = await exec(`${cmdModel} get-operation-status "${operationName}"`);
+    assert.match(output, /Operation details:/);
+  });
+
+  it(`should list models, get and delete a model. list, get and display model
+    evaluations from preexisting models`, async () => {
+    // List models
+    let output = await exec(`${cmdModel} list-models "${filter}"`);
+    const parsedOut = output.split('\n');
+    const ouputModelId = parsedOut[3].split(':')[1].trim();
+    assert.match(output, /List of models:/);
+
+    // Get model
+    output = await exec(`${cmdModel} get-model "${ouputModelId}"`);
+    assert.match(output, /Model name:/);
+
+    // List model evaluations
+    output = await exec(`${cmdModel} list-model-evaluations "${ouputModelId}"`);
+    const parsedModelEvaluation = output.split('\n');
+    const modelEvaluationId = parsedModelEvaluation[3].split(':')[1].trim();
+    assert.match(output, /Model evaluation Id:/);
+
+    // Get model evaluation
+    output = await exec(
+      `${cmdModel} get-model-evaluation "${ouputModelId}" ` +
+        `"${modelEvaluationId}"`
+    );
+    assert.match(output, /Model evaluation Id:/);
+
+    // Display evaluation
+    output = await exec(`${cmdModel} display-evaluation "${ouputModelId}"`);
+    assert.match(output, /Model Evaluation ID:/);
+
+    // Delete model
+    output = await exec(`${cmdModel} delete-model "${ouputModelId}"`);
+    assert.match(output, /Model delete details:/);
+  });
+
+  it(`should list and get operation status`, async () => {
+    // List operation status
+    let output = await exec(`${cmdModel} list-operations-status`);
+    const operationFullId = output
+      .split('\n')[3]
+      .split(':')[1]
+      .trim();
+    assert.match(output, /Operation details:/);
+
+    // Get operation status
+    // Poll operation status, here confirming that operation is not complete yet
+    output = await exec(
+      `${cmdModel} get-operation-status "${operationFullId}"`
+    );
+    assert.match(output, /Operation details:/);
+  });
+});

automl/snippets/test/automlVideoIntelligenceClassificationPredict.v1beta1.test.js

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+/**
+ * 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 Video Intelligence Classification "Prediction API" sample.
+ */
+
+const cmdPredict = 'node automlVideoIntelligencePrediction.js';
+
+// TODO(developer): Before running the test cases,
+// set the environment variables PROJECT_ID, REGION_NAME and
+// change the values of modelId, inputUri and outputUriPrefix
+//const projectId = process.env.PROJECT_ID;
+//const computeRegion = process.env.REGION_NAME;
+const modelId = 'VCN5018751611309129728';
+const inputUri = 'gs://video-intelligence/input-csv/annotateVideo.csv';
+const outputUriPrefix = 'gs://video-intelligence/';
+
+const exec = async cmd => (await execa.shell(cmd)).stdout;
+
+describe.skip(`Video Intelligence PredictionAPI`, () => {
+  it(`should run prediction from preexisting model`, async () => {
+    // Run prediction on 'annotate_video.csv' from gcs inputUri
+    const output = await exec(
+      `${cmdPredict} predict "${modelId}" "${inputUri}" "${outputUriPrefix}"`
+    );
+    assert.match(output, /Operation name:/);
+  });
+});

automl/snippets/video-intelligence/classification/create-dataset.v1beta1.js

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+/**
+ * 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`;
+async function main(
+  projectId = 'YOUR_PROJECT_ID',
+  computeRegion = 'YOUR_REGION_NAME',
+  datasetName = 'YOUR_DATASET_NAME'
+) {
+  // [START automl_video_intelligence_classification_create_dataset]
+  const automl = require(`@google-cloud/automl`);
+  const util = require(`util`);
+  const client = new automl.v1beta1.AutoMlClient();
+
+  /**
+   * 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”;
+
+  // A resource that represents Google Cloud Platform location.
+  const projectLocation = client.locationPath(projectId, computeRegion);
+
+  // Set dataset name and metadata.
+  const myDataset = {
+    displayName: datasetName,
+    videoClassificationDatasetMetadata: {},
+  };
+
+  // Create a dataset with the dataset metadata in the region.
+  client
+    .createDataset({parent: projectLocation, dataset: myDataset})
+    .then(responses => {
+      const dataset = responses[0];
+
+      // Display the dataset information.
+      console.log(`Dataset name: ${dataset.name}`);
+      console.log(`Dataset Id: ${dataset.name.split(`/`).pop(-1)}`);
+      console.log(`Dataset display name: ${dataset.displayName}`);
+      console.log(`Dataset example count: ${dataset.exampleCount}`);
+      console.log(
+        `Video classification dataset metadata: ${util.inspect(
+          dataset.videoClassificationDatasetMetadata,
+          false,
+          null
+        )}`
+      );
+    })
+    .catch(err => {
+      console.error(err);
+    });
+  // [END automl_video_intelligence_classification_create_dataset]
+}
+main(...process.argv.slice(2)).catch(console.error());

automl/snippets/video-intelligence/classification/create-model.v1beta1.js

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+/**
+ * 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`;
+async function main(
+  projectId = 'YOUR_PROJECT_ID',
+  computeRegion = 'YOUR_REGION_NAME',
+  datasetId = 'YOUR_DATASET_ID',
+  modelName = 'MODEL_NAME'
+) {
+  // [START automl_video_intelligence_classification_create_model]
+  const automl = require(`@google-cloud/automl`);
+  const client = new automl.v1beta1.AutoMlClient();
+
+  /**
+   * Demonstrates using the AutoML client to create a model.
+   * 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 datasetId = '[DATASET_ID]' e.g., "VCN7209576908164431872";
+  // const modelName = '[MODEL_NAME]' e.g., "myModel";
+
+  // A resource that represents Google Cloud Platform location.
+  const projectLocation = client.locationPath(projectId, computeRegion);
+
+  // Set datasetId, model name and model metadata for the dataset.
+  const myModel = {
+    displayName: modelName,
+    datasetId: datasetId,
+    videoClassificationModelMetadata: {},
+  };
+
+  // Create a model with the model metadata in the region.
+  client
+    .createModel({parent: projectLocation, model: myModel})
+    .then(responses => {
+      const initialApiResponse = responses[1];
+      console.log(`Training operation name: ${initialApiResponse.name}`);
+      console.log(`Training started...`);
+    })
+    .catch(err => {
+      console.error(err);
+    });
+  // [END automl_video_intelligence_classification_create_model]
+}
+main(...process.argv.slice(2)).catch(console.error());