automl: add vision object detection samples for atuoml ga [(#2614)](G…

…oogleCloudPlatform/python-docs-samples#2614)

* automl: add vision object detection samples for atuoml ga

* Update tests

* update test resource file used

* Consistently use double quotes

* Move test imports to top of file

* license year 2020

* Use centralized testing project for automl, improve comment with links to docs

Co-authored-by: Leah E. Cole <6719667+leahecole@users.noreply.github.com>

packages/google-cloud-automl/samples/snippets/vision_object_detection_create_dataset.py

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+# Copyright 2020 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.
+
+
+def create_dataset(project_id, display_name):
+    """Create a dataset."""
+    # [START automl_vision_object_detection_create_dataset]
+    from google.cloud import automl
+
+    # TODO(developer): Uncomment and set the following variables
+    # project_id = "YOUR_PROJECT_ID"
+    # display_name = "your_datasets_display_name"
+
+    client = automl.AutoMlClient()
+
+    # A resource that represents Google Cloud Platform location.
+    project_location = client.location_path(project_id, "us-central1")
+    metadata = automl.types.ImageObjectDetectionDatasetMetadata()
+    dataset = automl.types.Dataset(
+        display_name=display_name,
+        image_object_detection_dataset_metadata=metadata,
+    )
+
+    # Create a dataset with the dataset metadata in the region.
+    response = client.create_dataset(project_location, dataset)
+
+    created_dataset = response.result()
+
+    # Display the dataset information
+    print("Dataset name: {}".format(created_dataset.name))
+    print("Dataset id: {}".format(created_dataset.name.split("/")[-1]))
+    # [END automl_vision_object_detection_create_dataset]

packages/google-cloud-automl/samples/snippets/vision_object_detection_create_dataset_test.py

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+# Copyright 2020 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.
+
+import datetime
+import os
+
+from google.cloud import automl
+import pytest
+
+import vision_object_detection_create_dataset
+
+
+PROJECT_ID = os.environ["AUTOML_PROJECT_ID"]
+
+
+@pytest.mark.slow
+def test_vision_object_detection_create_dataset(capsys):
+    # create dataset
+    dataset_name = "test_" + datetime.datetime.now().strftime("%Y%m%d%H%M%S")
+    vision_object_detection_create_dataset.create_dataset(
+        PROJECT_ID, dataset_name
+    )
+    out, _ = capsys.readouterr()
+    assert "Dataset id: " in out
+
+    # Delete the created dataset
+    dataset_id = out.splitlines()[1].split()[2]
+    client = automl.AutoMlClient()
+    dataset_full_id = client.dataset_path(
+        PROJECT_ID, "us-central1", dataset_id
+    )
+    response = client.delete_dataset(dataset_full_id)
+    response.result()

packages/google-cloud-automl/samples/snippets/vision_object_detection_create_model.py

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+# Copyright 2020 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.
+
+
+def create_model(project_id, dataset_id, display_name):
+    """Create a model."""
+    # [START automl_vision_object_detection_create_model]
+    from google.cloud import automl
+
+    # TODO(developer): Uncomment and set the following variables
+    # project_id = "YOUR_PROJECT_ID"
+    # dataset_id = "YOUR_DATASET_ID"
+    # display_name = "your_models_display_name"
+
+    client = automl.AutoMlClient()
+
+    # A resource that represents Google Cloud Platform location.
+    project_location = client.location_path(project_id, "us-central1")
+    # Leave model unset to use the default base model provided by Google
+    # train_budget_milli_node_hours: The actual train_cost will be equal or
+    # less than this value.
+    # https://cloud.google.com/automl/docs/reference/rpc/google.cloud.automl.v1#imageobjectdetectionmodelmetadata
+    metadata = automl.types.ImageObjectDetectionModelMetadata(
+        train_budget_milli_node_hours=24000
+    )
+    model = automl.types.Model(
+        display_name=display_name,
+        dataset_id=dataset_id,
+        image_object_detection_model_metadata=metadata,
+    )
+
+    # Create a model with the model metadata in the region.
+    response = client.create_model(project_location, model)
+
+    print("Training operation name: {}".format(response.operation.name))
+    print("Training started...")
+    # [END automl_vision_object_detection_create_model]

packages/google-cloud-automl/samples/snippets/vision_object_detection_create_model_test.py

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+# Copyright 2020 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.
+
+import os
+
+from google.cloud import automl
+import pytest
+
+import vision_object_detection_create_model
+
+PROJECT_ID = os.environ["AUTOML_PROJECT_ID"]
+DATASET_ID = os.environ["OBJECT_DETECTION_DATASET_ID"]
+
+
+@pytest.mark.slow
+def test_vision_object_detection_create_model(capsys):
+    vision_object_detection_create_model.create_model(
+        PROJECT_ID, DATASET_ID, "object_test_create_model"
+    )
+    out, _ = capsys.readouterr()
+    assert "Training started" in out
+
+    # Cancel the operation
+    operation_id = out.split("Training operation name: ")[1].split("\n")[0]
+    client = automl.AutoMlClient()
+    client.transport._operations_client.cancel_operation(operation_id)

packages/google-cloud-automl/samples/snippets/vision_object_detection_deploy_model_node_count.py

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+# Copyright 2020 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.
+
+
+def deploy_model(project_id, model_id):
+    """Deploy a model with a specified node count."""
+    # [START automl_vision_object_detection_deploy_model_node_count]
+    from google.cloud import automl
+
+    # TODO(developer): Uncomment and set the following variables
+    # project_id = "YOUR_PROJECT_ID"
+    # model_id = "YOUR_MODEL_ID"
+
+    client = automl.AutoMlClient()
+    # Get the full path of the model.
+    model_full_id = client.model_path(project_id, "us-central1", model_id)
+
+    # node count determines the number of nodes to deploy the model on.
+    # https://cloud.google.com/automl/docs/reference/rpc/google.cloud.automl.v1#imageobjectdetectionmodeldeploymentmetadata
+    metadata = automl.types.ImageObjectDetectionModelDeploymentMetadata(
+        node_count=2
+    )
+    response = client.deploy_model(
+        model_full_id,
+        image_object_detection_model_deployment_metadata=metadata,
+    )
+
+    print("Model deployment finished. {}".format(response.result()))
+    # [END automl_vision_object_detection_deploy_model_node_count]

packages/google-cloud-automl/samples/snippets/vision_object_detection_deploy_model_node_count_test.py

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+# Copyright 2020 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.
+
+import os
+
+import pytest
+
+import vision_object_detection_deploy_model_node_count
+
+PROJECT_ID = os.environ["AUTOML_PROJECT_ID"]
+MODEL_ID = "0000000000000000000000"
+
+
+@pytest.mark.slow
+def test_object_detection_deploy_model_with_node_count(capsys):
+    # As model deployment can take a long time, instead try to deploy a
+    # nonexistent model and confirm that the model was not found, but other
+    # elements of the request were valid.
+    try:
+        vision_object_detection_deploy_model_node_count.deploy_model(
+            PROJECT_ID, MODEL_ID
+        )
+        out, _ = capsys.readouterr()
+        assert "The model does not exist" in out
+    except Exception as e:
+        assert "The model does not exist" in e.message

packages/google-cloud-automl/samples/snippets/vision_object_detection_predict.py

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+# Copyright 2020 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.
+
+
+def predict(project_id, model_id, file_path):
+    """Predict."""
+    # [START automl_vision_object_detection_predict]
+    from google.cloud import automl
+
+    # TODO(developer): Uncomment and set the following variables
+    # project_id = "YOUR_PROJECT_ID"
+    # model_id = "YOUR_MODEL_ID"
+    # file_path = "path_to_local_file.jpg"
+
+    prediction_client = automl.PredictionServiceClient()
+
+    # Get the full path of the model.
+    model_full_id = prediction_client.model_path(
+        project_id, "us-central1", model_id
+    )
+
+    # Read the file.
+    with open(file_path, "rb") as content_file:
+        content = content_file.read()
+
+    image = automl.types.Image(image_bytes=content)
+    payload = automl.types.ExamplePayload(image=image)
+
+    # params is additional domain-specific parameters.
+    # score_threshold is used to filter the result
+    # https://cloud.google.com/automl/docs/reference/rpc/google.cloud.automl.v1#predictrequest
+    params = {"score_threshold": "0.8"}
+
+    response = prediction_client.predict(model_full_id, payload, params)
+    print("Prediction results:")
+    for result in response.payload:
+        print("Predicted class name: {}".format(result.display_name))
+        print(
+            "Predicted class score: {}".format(
+                result.image_object_detection.score
+            )
+        )
+        bounding_box = result.image_object_detection.bounding_box
+        print("Normalized Vertices:")
+        for vertex in bounding_box.normalized_vertices:
+            print("\tX: {}, Y: {}".format(vertex.x, vertex.y))
+    # [END automl_vision_object_detection_predict]

packages/google-cloud-automl/samples/snippets/vision_object_detection_predict_test.py

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+# Copyright 2020 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.
+
+import os
+
+from google.cloud import automl
+import pytest
+
+import vision_object_detection_predict
+
+PROJECT_ID = os.environ["AUTOML_PROJECT_ID"]
+MODEL_ID = os.environ["OBJECT_DETECTION_MODEL_ID"]
+
+
+@pytest.fixture(scope="function")
+def verify_model_state():
+    client = automl.AutoMlClient()
+    model_full_id = client.model_path(PROJECT_ID, "us-central1", MODEL_ID)
+
+    model = client.get_model(model_full_id)
+    if model.deployment_state == automl.enums.Model.DeploymentState.UNDEPLOYED:
+        # Deploy model if it is not deployed
+        response = client.deploy_model(model_full_id)
+        response.result()
+
+
+def test_vision_object_detection_predict(capsys, verify_model_state):
+    verify_model_state
+    file_path = "resources/salad.jpg"
+    vision_object_detection_predict.predict(PROJECT_ID, MODEL_ID, file_path)
+    out, _ = capsys.readouterr()
+    assert "Predicted class name:" in out