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Automl ga vision classification [(#2612)](#2612)
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* automl: add vision classification samples for automl ga

* lint

* naming

* clean up samples and test

* lint

* Consistently use double quotes

* Move test imports to top of file

* Fix license year

* license year 2020, drop python2 unicode print
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nnegrey authored and busunkim96 committed Aug 11, 2020
1 parent 45567b6 commit 9b5f526
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3 changes: 1 addition & 2 deletions automl/snippets/get_model_evaluation_test.py
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import os

from google.cloud import automl
import pytest

import get_model_evaluation
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@pytest.fixture(scope="function")
def get_evaluation_id():
from google.cloud import automl

client = automl.AutoMlClient()
model_full_id = client.model_path(PROJECT_ID, "us-central1", MODEL_ID)
evaluation = None
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49 changes: 49 additions & 0 deletions automl/snippets/vision_classification_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_classification_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")
# Specify the classification type
# Types:
# MultiLabel: Multiple labels are allowed for one example.
# MultiClass: At most one label is allowed per example.
metadata = automl.types.ImageClassificationDatasetMetadata(
classification_type=automl.enums.ClassificationType.MULTILABEL
)
dataset = automl.types.Dataset(
display_name=display_name,
image_classification_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_classification_create_dataset]
44 changes: 44 additions & 0 deletions automl/snippets/vision_classification_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_classification_create_dataset


PROJECT_ID = os.environ["GCLOUD_PROJECT"]


@pytest.mark.slow
def test_create_dataset(capsys):
# create dataset
dataset_name = "test_" + datetime.datetime.now().strftime("%Y%m%d%H%M%S")
vision_classification_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()
45 changes: 45 additions & 0 deletions automl/snippets/vision_classification_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_classification_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
metadata = automl.types.ImageClassificationModelMetadata(
train_budget_milli_node_hours=24000
)
model = automl.types.Model(
display_name=display_name,
dataset_id=dataset_id,
image_classification_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_classification_create_model]
37 changes: 37 additions & 0 deletions automl/snippets/vision_classification_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_classification_create_model

PROJECT_ID = os.environ["GCLOUD_PROJECT"]
DATASET_ID = "ICN3946265060617537378"


@pytest.mark.slow
def test_vision_classification_create_model(capsys):
vision_classification_create_model.create_model(
PROJECT_ID, DATASET_ID, "classification_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)
36 changes: 36 additions & 0 deletions automl/snippets/vision_classification_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_classification_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)
metadata = automl.types.ImageClassificationModelDeploymentMetadata(
node_count=2
)
response = client.deploy_model(
model_full_id, image_classification_model_deployment_metadata=metadata
)

print("Model deployment finished. {}".format(response.result()))
# [END automl_vision_classification_deploy_model_node_count]
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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_classification_deploy_model_node_count

PROJECT_ID = os.environ["GCLOUD_PROJECT"]
MODEL_ID = "ICN0000000000000000000"


@pytest.mark.slow
def test_classification_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_classification_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
49 changes: 49 additions & 0 deletions automl/snippets/vision_classification_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_classification_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
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.classification.score))
# [END automl_vision_classification_predict]
43 changes: 43 additions & 0 deletions automl/snippets/vision_classification_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_classification_predict

PROJECT_ID = os.environ["GCLOUD_PROJECT"]
MODEL_ID = "ICN7383667271543079510"


@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_classification_predict(capsys, verify_model_state):
verify_model_state
file_path = "resources/test.png"
vision_classification_predict.predict(PROJECT_ID, MODEL_ID, file_path)
out, _ = capsys.readouterr()
assert "Predicted class name:" in out

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