Data Labeling Beta samples

datalabeling/README.rst

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+.. This file is automatically generated. Do not edit this file directly.
+
+Google Cloud Data Labeling Service Python Samples
+===============================================================================
+
+.. image:: https://gstatic.com/cloudssh/images/open-btn.png
+   :target: https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/GoogleCloudPlatform/python-docs-samples&page=editor&open_in_editor=datalabeling/README.rst
+
+
+This directory contains samples for Google Cloud Data Labeling Service. `Google Cloud Data Labeling Service`_ allows developers to request having human labelers label a collection of data that you plan to use to train a custom machine learning model.
+
+
+
+
+.. _Google Cloud Data Labeling Service: https://cloud.google.com/data-labeling/docs/
+
+Setup
+-------------------------------------------------------------------------------
+
+
+Authentication
+++++++++++++++
+
+This sample requires you to have authentication setup. Refer to the
+`Authentication Getting Started Guide`_ for instructions on setting up
+credentials for applications.
+
+.. _Authentication Getting Started Guide:
+    https://cloud.google.com/docs/authentication/getting-started
+
+Install Dependencies
+++++++++++++++++++++
+
+#. Clone python-docs-samples and change directory to the sample directory you want to use.
+
+    .. code-block:: bash
+
+        $ git clone https://github.com/GoogleCloudPlatform/python-docs-samples.git
+
+#. Install `pip`_ and `virtualenv`_ if you do not already have them. You may want to refer to the `Python Development Environment Setup Guide`_ for Google Cloud Platform for instructions.
+
+   .. _Python Development Environment Setup Guide:
+       https://cloud.google.com/python/setup
+
+#. Create a virtualenv. Samples are compatible with Python 2.7 and 3.4+.
+
+    .. code-block:: bash
+
+        $ virtualenv env
+        $ source env/bin/activate
+
+#. Install the dependencies needed to run the samples.
+
+    .. code-block:: bash
+
+        $ pip install -r requirements.txt
+
+.. _pip: https://pip.pypa.io/
+.. _virtualenv: https://virtualenv.pypa.io/
+
+
+
+The client library
+-------------------------------------------------------------------------------
+
+This sample uses the `Google Cloud Client Library for Python`_.
+You can read the documentation for more details on API usage and use GitHub
+to `browse the source`_ and  `report issues`_.
+
+.. _Google Cloud Client Library for Python:
+    https://googlecloudplatform.github.io/google-cloud-python/
+.. _browse the source:
+    https://github.com/GoogleCloudPlatform/google-cloud-python
+.. _report issues:
+    https://github.com/GoogleCloudPlatform/google-cloud-python/issues
+
+
+.. _Google Cloud SDK: https://cloud.google.com/sdk/

datalabeling/README.rst.in

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+# This file is used to generate README.rst
+
+product:
+  name: Google Cloud Data Labeling Service
+  short_name: Cloud Data Labeling
+  url: https://cloud.google.com/data-labeling/docs/
+  description: >
+    `Google Cloud Data Labeling Service`_ allows developers to request having
+    human labelers label a collection of data that you plan to use to train a
+    custom machine learning model.
+
+setup:
+- auth
+- install_deps
+
+cloud_client_library: true
+
+folder: datalabeling

datalabeling/create_annotation_spec_set.py

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+#!/usr/bin/env python
+
+# 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.
+
+import argparse
+
+
+# [START datalabeling_create_annotation_spec_set_beta]
+def create_annotation_spec_set(project_id):
+    """Creates a data labeling annotation spec set for the given
+    Google Cloud project.
+    """
+    from google.cloud import datalabeling_v1beta1 as datalabeling
+    client = datalabeling.DataLabelingServiceClient()
+
+    project_path = client.project_path(project_id)
+
+    annotation_spec_1 = datalabeling.types.AnnotationSpec(
+        display_name='label_1',
+        description='label_description_1'
+    )
+
+    annotation_spec_2 = datalabeling.types.AnnotationSpec(
+        display_name='label_2',
+        description='label_description_2'
+    )
+
+    annotation_spec_set = datalabeling.types.AnnotationSpecSet(
+        display_name='YOUR_ANNOTATION_SPEC_SET_DISPLAY_NAME',
+        description='YOUR_DESCRIPTION',
+        annotation_specs=[annotation_spec_1, annotation_spec_2]
+    )
+
+    response = client.create_annotation_spec_set(
+        project_path, annotation_spec_set)
+
+    # The format of the resource name:
+    # project_id/{project_id}/annotationSpecSets/{annotationSpecSets_id}
+    print('The annotation_spec_set resource name: {}'.format(response.name))
+    print('Display name: {}'.format(response.display_name))
+    print('Description: {}'.format(response.description))
+    print('Annotation specs:')
+    for annotation_spec in response.annotation_specs:
+        print('\tDisplay name: {}'.format(annotation_spec.display_name))
+        print('\tDescription: {}\n'.format(annotation_spec.description))
+
+    return response
+# [END datalabeling_create_annotation_spec_set_beta]
+
+
+if __name__ == '__main__':
+    parser = argparse.ArgumentParser(
+        description=__doc__,
+        formatter_class=argparse.RawDescriptionHelpFormatter
+    )
+
+    parser.add_argument(
+        '--project-id',
+        help='Project ID. Required.',
+        required=True
+    )
+
+    args = parser.parse_args()
+
+    create_annotation_spec_set(args.project_id)

datalabeling/create_annotation_spec_set_test.py

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+#!/usr/bin/env python
+
+# Copyright 2019 Google, Inc
+#
+# 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 create_annotation_spec_set
+from google.cloud import datalabeling_v1beta1 as datalabeling
+import pytest
+
+PROJECT_ID = os.getenv('GCLOUD_PROJECT')
+
+
+@pytest.mark.slow
+def test_create_annotation_spec_set(capsys):
+    response = create_annotation_spec_set.create_annotation_spec_set(
+        PROJECT_ID)
+    out, _ = capsys.readouterr()
+    assert 'The annotation_spec_set resource name:' in out
+
+    # Delete the created annotation spec set.
+    annotation_spec_set_name = response.name
+    client = datalabeling.DataLabelingServiceClient()
+    client.delete_annotation_spec_set(annotation_spec_set_name)

datalabeling/create_instruction.py

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+#!/usr/bin/env python
+
+# 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.
+
+import argparse
+
+
+# [START datalabeling_create_instruction_beta]
+def create_instruction(project_id, data_type, instruction_gcs_uri):
+    """ Creates a data labeling PDF instruction for the given Google Cloud
+    project. The PDF file should be uploaded to the project in
+    Google Cloud Storage.
+    """
+    from google.cloud import datalabeling_v1beta1 as datalabeling
+    client = datalabeling.DataLabelingServiceClient()
+
+    project_path = client.project_path(project_id)
+
+    pdf_instruction = datalabeling.types.PdfInstruction(
+        gcs_file_uri=instruction_gcs_uri)
+
+    instruction = datalabeling.types.Instruction(
+        display_name='YOUR_INSTRUCTION_DISPLAY_NAME',
+        description='YOUR_DESCRIPTION',
+        data_type=data_type,
+        pdf_instruction=pdf_instruction
+    )
+
+    operation = client.create_instruction(project_path, instruction)
+
+    result = operation.result()
+
+    # The format of the resource name:
+    # project_id/{project_id}/instruction/{instruction_id}
+    print('The instruction resource name: {}\n'.format(result.name))
+    print('Display name: {}'.format(result.display_name))
+    print('Description: {}'.format(result.description))
+    print('Create time:')
+    print('\tseconds: {}'.format(result.create_time.seconds))
+    print('\tnanos: {}'.format(result.create_time.nanos))
+    print('Data type: {}'.format(
+        datalabeling.enums.DataType(result.data_type).name))
+    print('Pdf instruction:')
+    print('\tGcs file uri: {}'.format(
+        result.pdf_instruction.gcs_file_uri))
+
+    return result
+# [END datalabeling_create_instruction_beta]
+
+
+if __name__ == '__main__':
+    parser = argparse.ArgumentParser(
+        description=__doc__,
+        formatter_class=argparse.RawDescriptionHelpFormatter
+    )
+
+    parser.add_argument(
+        '--project-id',
+        help='Project ID. Required.',
+        required=True
+    )
+
+    parser.add_argument(
+        '--data-type',
+        help='Data type. Only support IMAGE, VIDEO, TEXT and AUDIO. Required.',
+        required=True
+    )
+
+    parser.add_argument(
+        '--instruction-gcs-uri',
+        help='The URI of Google Cloud Storage of the instruction. Required.',
+        required=True
+    )
+
+    args = parser.parse_args()
+
+    create_instruction(
+        args.project_id,
+        args.data_type,
+        args.instruction_gcs_uri
+    )

datalabeling/create_instruction_test.py

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+#!/usr/bin/env python
+
+# Copyright 2019 Google, Inc
+#
+# 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 create_instruction
+from google.cloud import datalabeling_v1beta1 as datalabeling
+import pytest
+
+PROJECT_ID = os.getenv('GCLOUD_PROJECT')
+INSTRUCTION_GCS_URI = ('gs://cloud-samples-data/datalabeling'
+                       '/instruction/test.pdf')
+
+
+@pytest.mark.slow
+def test_create_instruction(capsys):
+    result = create_instruction.create_instruction(
+        PROJECT_ID,
+        'IMAGE',
+        INSTRUCTION_GCS_URI
+    )
+    out, _ = capsys.readouterr()
+    assert 'The instruction resource name: ' in out
+
+    # Delete the created instruction.
+    instruction_name = result.name
+    client = datalabeling.DataLabelingServiceClient()
+    client.delete_instruction(instruction_name)