video_intelligence

Example Airflow DAG that demonstrates operators for the Google Cloud Video Intelligence service in the Google Cloud Platform.

AI + Machine Learning


Providers:

Run this DAG

1. Install Astronomer CLISkip if you already have the CLI

2. Initate the project:

3. Copy and paste the code below into a file in the

dags
directory.

4. Add the following to your requirements.txt file:

5. Run the DAG:

#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you 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.
"""
Example Airflow DAG that demonstrates operators for the Google Cloud Video Intelligence service in the Google
Cloud Platform.
This DAG relies on the following OS environment variables:
* GCP_BUCKET_NAME - Google Cloud Storage bucket where the file exists.
"""
import os
from google.api_core.retry import Retry
from airflow import models
from airflow.operators.bash import BashOperator
from airflow.providers.google.cloud.operators.video_intelligence import (
CloudVideoIntelligenceDetectVideoExplicitContentOperator,
CloudVideoIntelligenceDetectVideoLabelsOperator,
CloudVideoIntelligenceDetectVideoShotsOperator,
)
from airflow.utils.dates import days_ago
# [START howto_operator_video_intelligence_os_args]
GCP_BUCKET_NAME = os.environ.get("GCP_VIDEO_INTELLIGENCE_BUCKET_NAME", "INVALID BUCKET NAME")
# [END howto_operator_video_intelligence_os_args]
# [START howto_operator_video_intelligence_other_args]
INPUT_URI = f"gs://{GCP_BUCKET_NAME}/video.mp4"
# [END howto_operator_video_intelligence_other_args]
with models.DAG(
"example_gcp_video_intelligence",
schedule_interval=None, # Override to match your needs
start_date=days_ago(1),
tags=['example'],
) as dag:
# [START howto_operator_video_intelligence_detect_labels]
detect_video_label = CloudVideoIntelligenceDetectVideoLabelsOperator(
input_uri=INPUT_URI,
output_uri=None,
video_context=None,
timeout=5,
task_id="detect_video_label",
)
# [END howto_operator_video_intelligence_detect_labels]
# [START howto_operator_video_intelligence_detect_labels_result]
detect_video_label_result = BashOperator(
bash_command="echo {{ task_instance.xcom_pull('detect_video_label')"
"['annotationResults'][0]['shotLabelAnnotations'][0]['entity']}}",
task_id="detect_video_label_result",
)
# [END howto_operator_video_intelligence_detect_labels_result]
# [START howto_operator_video_intelligence_detect_explicit_content]
detect_video_explicit_content = CloudVideoIntelligenceDetectVideoExplicitContentOperator(
input_uri=INPUT_URI,
output_uri=None,
video_context=None,
retry=Retry(maximum=10.0),
timeout=5,
task_id="detect_video_explicit_content",
)
# [END howto_operator_video_intelligence_detect_explicit_content]
# [START howto_operator_video_intelligence_detect_explicit_content_result]
detect_video_explicit_content_result = BashOperator(
bash_command="echo {{ task_instance.xcom_pull('detect_video_explicit_content')"
"['annotationResults'][0]['explicitAnnotation']['frames'][0]}}",
task_id="detect_video_explicit_content_result",
)
# [END howto_operator_video_intelligence_detect_explicit_content_result]
# [START howto_operator_video_intelligence_detect_video_shots]
detect_video_shots = CloudVideoIntelligenceDetectVideoShotsOperator(
input_uri=INPUT_URI,
output_uri=None,
video_context=None,
retry=Retry(maximum=10.0),
timeout=5,
task_id="detect_video_shots",
)
# [END howto_operator_video_intelligence_detect_video_shots]
# [START howto_operator_video_intelligence_detect_video_shots_result]
detect_video_shots_result = BashOperator(
bash_command="echo {{ task_instance.xcom_pull('detect_video_shots')"
"['annotationResults'][0]['shotAnnotations'][0]}}",
task_id="detect_video_shots_result",
)
# [END howto_operator_video_intelligence_detect_video_shots_result]
detect_video_label >> detect_video_label_result
detect_video_explicit_content >> detect_video_explicit_content_result
detect_video_shots >> detect_video_shots_result