如何使用Google AutoML Vision Python API to update_dataset

pip install google-cloud-automl

from google.cloud import automl_v1beta1 as automl
from google.protobuf import field_mask_pb2

# 设置项目ID和区域
project_id = "your-project-id"
compute_region = "us-central1"
dataset_id = "your-dataset-id"

# 初始化AutoML客户端
client = automl.AutoMlClient()

# 构建数据集的完整路径
dataset_full_id = client.dataset_path(project_id, compute_region, dataset_id)

# 获取现有的数据集
dataset = client.get_dataset(name=dataset_full_id)

# 更新数据集的描述
dataset.display_name = "Updated Dataset Name"
dataset.description = "Updated description for the dataset."

# 创建FieldMask来指定要更新的字段
update_mask = field_mask_pb2.FieldMask(paths=["display_name", "description"])

# 更新数据集
response = client.update_dataset(dataset=dataset, update_mask=update_mask)

print("Dataset updated. Name: {}, Description: {}".format(response.display_name, response.description))

export GOOGLE_APPLICATION_CREDENTIALS="path/to/your-service-account-file.json"