이 페이지는 개발자가 광학 문자 인식 (OCR) 서비스를 사용하기 위해 Google Distributed Cloud (GDC) 에어 갭 프로젝트를 설정하는 데 도움이 됩니다. 이 프로세스에는 프로젝트 만들기, OCR API 사용 설정, 클라이언트 라이브러리 설치, 환경 변수 정의, 사용자 인증 정보 인증이 포함됩니다. Vertex AI를 처음 사용하는 경우 문자 인식 기능에 대해 자세히 알아보세요.
다음과 같이 GDC 콘솔과 gdcloud CLI를 사용하여 문자 인식 프로젝트를 설정합니다.
GDC 콘솔: OCR API를 사용 설정하고 서비스 상태와 엔드포인트를 확인합니다.
gdcloud CLI: OCR API와 상호작용하도록 서비스 계정을 구성하고, 클라이언트 라이브러리를 설치하고, API 요청을 인증합니다.
프로젝트 만들기
분산 클라우드 리소스 계층 구조 내에서 문자 인식 프로젝트를 만들면 공동작업자, 사용 설정된 API, 모니터링 도구, 결제 정보, 인증 사용자 인증 정보, 액세스 제어를 포함한 OCR 리소스가 정리됩니다.
[[["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"]],["최종 업데이트: 2025-09-05(UTC)"],[[["\u003cp\u003eThis page guides developers through setting up a Google Distributed Cloud (GDC) air-gapped project for the Optical Character Recognition (OCR) service, including creating a project and enabling the OCR API.\u003c/p\u003e\n"],["\u003cp\u003eDevelopers can utilize the GDC console to enable the OCR API and view service status, while the gdcloud CLI is used for configuring service accounts, installing client libraries, and authenticating API requests.\u003c/p\u003e\n"],["\u003cp\u003eTo access OCR features, the AI OCR Developer role must be granted to the user or service account by the Project IAM Admin, and the OCR pre-trained API must be enabled for the project.\u003c/p\u003e\n"],["\u003cp\u003eClient libraries, particularly for Python, are recommended for easier API interaction, and users should ensure the installed client library version matches the one specified by their GDC organization.\u003c/p\u003e\n"],["\u003cp\u003eSetting environment variables within a Python script, such as the service account keys filename, is necessary to make authorized API calls programmatically after installing the client library.\u003c/p\u003e\n"]]],[],null,["# Set up a character recognition project\n\nThis page helps developers set up a Google Distributed Cloud (GDC) air-gapped project to\nuse the Optical Character Recognition (OCR) service. This process includes creating a\nproject, enabling the OCR API, installing client libraries,\ndefining environment variables, and authenticating your credentials. If you are\nnew to Vertex AI, [learn more about character recognition features](/distributed-cloud/hosted/docs/latest/gdch/application/ao-user/vertex-ai-ocr).\n\nYou set up a character recognition project using the GDC console and\ngdcloud CLI as follows:\n\n- **GDC console**: Enable the OCR API and view the service status and endpoint.\n- **The gdcloud CLI**: Configure service accounts to interact with the OCR API, install client libraries, and authenticate API requests.\n\nCreate a project\n----------------\n\nCreating a character recognition project within your Distributed Cloud\n[resource hierarchy](/distributed-cloud/hosted/docs/latest/gdch/resources/resource-hierarchy)\norganizes your OCR resources, which include collaborators,\nenabled APIs, monitoring tools, billing information, authentication credentials,\nand access controls.\n\nTo create your project, see [Set up a project for Vertex AI](/distributed-cloud/hosted/docs/latest/gdch/application/ao-user/vertex-ai-set-up-project).\nYou need your project ID when making API calls.\n| **Tip:** Improve security, resource management, and cost tracking by isolating your experimental, testing, and production workloads in separate Distributed Cloud projects.\n\nRequest developer permissions\n-----------------------------\n\nYou must have the AI OCR Developer role in your project to access\noptical character recognition features and generate an API token for request\nauthentication and authorization.\n\nAsk your Project IAM Admin to grant the AI OCR Developer\n(`ai-ocr-developer`) role to your user or service account\nwithin your project namespace. For information about this role, see\n[Prepare IAM permissions](/distributed-cloud/hosted/docs/latest/gdch/application/ao-user/vertex-ai-ao-permissions).\n\nEnable the OCR API\n------------------\n\nYou must [enable the OCR pre-trained API](/distributed-cloud/hosted/docs/latest/gdch/application/ao-user/vertex-ai-enable-pre-trained-apis)\nfor your project. If enabled, you can [view the service status and endpoint for the OCR pre-trained API](/distributed-cloud/hosted/docs/latest/gdch/application/ao-user/vertex-ai-api-status).\n\nInstall client libraries\n------------------------\n\nClient libraries are available for the Python programming language. We recommend\nusing these client libraries to make calls to the OCR API\nbecause they make it easier to access APIs.\n\n[Install the OCR client library](/distributed-cloud/hosted/docs/latest/gdch/application/ao-user/vertex-ai-install-libraries)\nand follow these steps to ensure you have the correct version:\n\n1. Check if the OCR client library is installed and obtain\n the version number:\n\n pip freeze | grep vision\n\n If the client library is already installed, you obtain an output similar\n to the following example: \n\n google-cloud-vision==3.0.0\n\n The version number you obtain must match the client library at the\n following endpoint: \n\n https://\u003cvar translate=\"no\"\u003eGDC_URL\u003c/var\u003e/.well-known/static/client-libraries\n\n Replace \u003cvar translate=\"no\"\u003eGDC_URL\u003c/var\u003e with the\n URL of your organization in GDC.\n2. If the version numbers don't match, uninstall the client library:\n\n pip uninstall google-cloud-vision\n\n3. If you uninstalled the OCR client library, you must\n [reinstall it](/distributed-cloud/hosted/docs/latest/gdch/application/ao-user/vertex-ai-install-libraries)\n by specifying the filename corresponding to your operating system.\n\nSet your environment variables\n------------------------------\n\nAfter installing the OCR client library, you can interact\nwith the API from a Python script.\n\nIf you [set up a service account](/distributed-cloud/hosted/docs/latest/gdch/application/ao-user/vertex-ai-set-up-project#set-up-service)\nin your project to make authorized API calls programmatically, you can define\nenvironment variables in the Python script to access values such as the service\naccount keys when running.\n\nFollow these steps to set required environment variables on a Python script:\n\n1. [Create a JupyterLab notebook](/distributed-cloud/hosted/docs/latest/gdch/application/ao-user/vertex-ai-workbench#create-notebook)\n to interact with the OCR pre-trained API.\n\n2. Create a Python script on the JupyterLab notebook.\n\n3. Add the following code to the Python script:\n\n import os\n\n os.environ[\"GOOGLE_APPLICATION_CREDENTIALS\"] = \"\u003cvar translate=\"no\"\u003eAPPLICATION_DEFAULT_CREDENTIALS_FILENAME\u003c/var\u003e\"\n\n Replace \u003cvar translate=\"no\"\u003eAPPLICATION_DEFAULT_CREDENTIALS_FILENAME\u003c/var\u003e with\n the name of the JSON file that contains [the service account keys you created](/distributed-cloud/hosted/docs/latest/gdch/application/ao-user/vertex-ai-set-up-project#set-up-service)\n in the project, such as `my-service-key.json`.\n4. Save the Python script with a name, such as `vision.py`.\n\n5. Run the Python script to set the environment variables:\n\n python \u003cvar translate=\"no\"\u003e\u003cspan class=\"devsite-syntax-n\"\u003eSCRIPT_NAME\u003c/span\u003e\u003c/var\u003e\n\n Replace \u003cvar translate=\"no\"\u003eSCRIPT_NAME\u003c/var\u003e with the name you gave to your\n Python script, such as `vision.py`.\n\n| **Note:** Keep the script open when using the environment variables from Python or getting an authentication token.\n\nSet up authentication\n---------------------\n\nBefore you can start using the OCR API, you must authenticate\nyour client credentials and request account access to your project resources.\nFor more information, see [Authenticate API requests](/distributed-cloud/hosted/docs/latest/gdch/application/ao-user/vertex-ai-api-auth)."]]
