이미지 분류 단일 라벨을 위한 데이터 가져오기
컬렉션을 사용해 정리하기
내 환경설정을 기준으로 콘텐츠를 저장하고 분류하세요.
import_data 메서드를 사용하여 이미지 분류 단일 라벨을 위한 데이터를 가져옵니다.
코드 샘플
달리 명시되지 않는 한 이 페이지의 콘텐츠에는 Creative Commons Attribution 4.0 라이선스에 따라 라이선스가 부여되며, 코드 샘플에는 Apache 2.0 라이선스에 따라 라이선스가 부여됩니다. 자세한 내용은 Google Developers 사이트 정책을 참조하세요. 자바는 Oracle 및/또는 Oracle 계열사의 등록 상표입니다.
[[["이해하기 쉬움","easyToUnderstand","thumb-up"],["문제가 해결됨","solvedMyProblem","thumb-up"],["기타","otherUp","thumb-up"]],[["이해하기 어려움","hardToUnderstand","thumb-down"],["잘못된 정보 또는 샘플 코드","incorrectInformationOrSampleCode","thumb-down"],["필요한 정보/샘플이 없음","missingTheInformationSamplesINeed","thumb-down"],["번역 문제","translationIssue","thumb-down"],["기타","otherDown","thumb-down"]],[],[],[],null,["# Import data for image classification single label\n\nImports data for image classification single label using the import_data method.\n\nCode sample\n-----------\n\n### Python\n\n\nBefore trying this sample, follow the Python setup instructions in the\n[Vertex AI quickstart using\nclient libraries](/vertex-ai/docs/start/client-libraries).\n\n\nFor more information, see the\n[Vertex AI Python API\nreference documentation](/python/docs/reference/aiplatform/latest).\n\n\nTo authenticate to Vertex AI, set up Application Default Credentials.\nFor more information, see\n\n[Set up authentication for a local development environment](/docs/authentication/set-up-adc-local-dev-environment).\n\n from google.cloud import aiplatform\n\n\n def import_data_image_classification_single_label_sample(\n project: str,\n dataset_id: str,\n gcs_source_uri: str,\n location: str = \"us-central1\",\n api_endpoint: str = \"us-central1-aiplatform.googleapis.com\",\n timeout: int = 1800,\n ):\n # The AI Platform services require regional API endpoints.\n client_options = {\"api_endpoint\": api_endpoint}\n # Initialize client that will be used to create and send requests.\n # This client only needs to be created once, and can be reused for multiple requests.\n client = aiplatform.gapic.https://cloud.google.com/python/docs/reference/aiplatform/latest/google.cloud.aiplatform_v1.services.dataset_service.DatasetServiceClient.html(client_options=client_options)\n import_configs = [\n {\n \"gcs_source\": {\"uris\": [gcs_source_uri]},\n \"import_schema_uri\": \"gs://google-cloud-aiplatform/schema/dataset/ioformat/image_classification_single_label_io_format_1.0.0.yaml\",\n }\n ]\n name = client.https://cloud.google.com/python/docs/reference/aiplatform/latest/google.cloud.aiplatform_v1.services.dataset_service.DatasetServiceClient.html#google_cloud_aiplatform_v1_services_dataset_service_DatasetServiceClient_dataset_path(project=project, location=location, dataset=dataset_id)\n response = client.https://cloud.google.com/python/docs/reference/aiplatform/latest/google.cloud.aiplatform_v1.services.dataset_service.DatasetServiceClient.html#google_cloud_aiplatform_v1_services_dataset_service_DatasetServiceClient_import_data(name=name, import_configs=import_configs)\n print(\"Long running operation:\", response.operation.name)\n import_data_response = response.result(timeout=timeout)\n print(\"import_data_response:\", import_data_response)\n\nWhat's next\n-----------\n\n\nTo search and filter code samples for other Google Cloud products, see the\n[Google Cloud sample browser](/docs/samples?product=aiplatform)."]]