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create_batch_prediction_job_video_object_tracking_sample.py
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create_batch_prediction_job_video_object_tracking_sample.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
#
# https://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.
# [START aiplatform_create_batch_prediction_job_video_object_tracking_sample]
from google.cloud import aiplatform
from google.protobuf import json_format
from google.protobuf.struct_pb2 import Value
def create_batch_prediction_job_video_object_tracking_sample(
project: str,
display_name: str,
model_name: str,
gcs_source_uri: str,
gcs_destination_output_uri_prefix: str,
location: str = "us-central1",
api_endpoint: str = "us-central1-aiplatform.googleapis.com",
):
# The AI Platform services require regional API endpoints.
client_options = {"api_endpoint": api_endpoint}
# Initialize client that will be used to create and send requests.
# This client only needs to be created once, and can be reused for multiple requests.
client = aiplatform.gapic.JobServiceClient(client_options=client_options)
model_parameters_dict = {"confidenceThreshold": 0.0}
model_parameters = json_format.ParseDict(model_parameters_dict, Value())
batch_prediction_job = {
"display_name": display_name,
# Format: 'projects/{project}/locations/{location}/models/{model_id}'
"model": model_name,
"model_parameters": model_parameters,
"input_config": {
"instances_format": "jsonl",
"gcs_source": {"uris": [gcs_source_uri]},
},
"output_config": {
"predictions_format": "jsonl",
"gcs_destination": {"output_uri_prefix": gcs_destination_output_uri_prefix},
},
}
parent = f"projects/{project}/locations/{location}"
response = client.create_batch_prediction_job(
parent=parent, batch_prediction_job=batch_prediction_job
)
print("response:", response)
# [END aiplatform_create_batch_prediction_job_video_object_tracking_sample]