명령줄을 사용하여 동영상에 주석 추가

명령줄을 사용하여 동영상에 주석 추가

이 페이지에서는 소유한 프로젝트에서 curl을 사용해서 Video Intelligence API 요청을 수행하는 방법을 보여줍니다.

이 페이지의 단계를 따르거나 Google Cloud 교육 실습으로 빠른 시작을 사용할 수 있습니다.

실습에 사용해보기

시작하기 전에

1. Sign in to your Google Cloud account. If you're new to Google Cloud, create an account to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.

2. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

   Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

   Go to project selector

3. Google Cloud 프로젝트에 결제가 사용 설정되어 있는지 확인합니다.

4. Enable the required API.

   Enable the API

5. Create a service account:

   1. In the Google Cloud console, go to the Create service account page.

      Go to Create service account
   2. Select your project.

   3. In the Service account name field, enter a name. The Google Cloud console fills in the Service account ID field based on this name.

      In the Service account description field, enter a description. For example, Service account for quickstart.

   4. Click Create and continue.

   5. Click Done to finish creating the service account.

      Do not close your browser window. You will use it in the next step.

6. Create a service account key:

   1. In the Google Cloud console, click the email address for the service account that you created.
   2. Click Keys.
   3. Click Add key, and then click Create new key.
   4. Click Create. A JSON key file is downloaded to your computer.
   5. Click Close.

7. Set the environment variable GOOGLE_APPLICATION_CREDENTIALS to the path of the JSON file that contains your credentials. This variable applies only to your current shell session, so if you open a new session, set the variable again.

   Example: Linux or macOS

   export GOOGLE_APPLICATION_CREDENTIALS="KEY_PATH"

   Replace KEY_PATH with the path of the JSON file that contains your credentials.

   For example:

   export GOOGLE_APPLICATION_CREDENTIALS="/home/user/Downloads/service-account-file.json"

   Example: Windows

   For PowerShell:

   $env:GOOGLE_APPLICATION_CREDENTIALS="KEY_PATH"

   Replace KEY_PATH with the path of the JSON file that contains your credentials.

   For example:

   $env:GOOGLE_APPLICATION_CREDENTIALS="C:\Users\username\Downloads\service-account-file.json"

   For command prompt:

   set GOOGLE_APPLICATION_CREDENTIALS=KEY_PATH

   Replace KEY_PATH with the path of the JSON file that contains your credentials.

8. Install the Google Cloud CLI.

9. To initialize the gcloud CLI, run the following command:

   gcloud init

10. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

    Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

    Go to project selector

11. Google Cloud 프로젝트에 결제가 사용 설정되어 있는지 확인합니다.

12. Enable the required API.

    Enable the API

13. Create a service account:

    1. In the Google Cloud console, go to the Create service account page.

       Go to Create service account
    2. Select your project.

    3. In the Service account name field, enter a name. The Google Cloud console fills in the Service account ID field based on this name.

       In the Service account description field, enter a description. For example, Service account for quickstart.

    4. Click Create and continue.

    5. Click Done to finish creating the service account.

       Do not close your browser window. You will use it in the next step.

14. Create a service account key:

    1. In the Google Cloud console, click the email address for the service account that you created.
    2. Click Keys.
    3. Click Add key, and then click Create new key.
    4. Click Create. A JSON key file is downloaded to your computer.
    5. Click Close.

15. Set the environment variable GOOGLE_APPLICATION_CREDENTIALS to the path of the JSON file that contains your credentials. This variable applies only to your current shell session, so if you open a new session, set the variable again.

    Example: Linux or macOS

    export GOOGLE_APPLICATION_CREDENTIALS="KEY_PATH"

    Replace KEY_PATH with the path of the JSON file that contains your credentials.

    For example:

    export GOOGLE_APPLICATION_CREDENTIALS="/home/user/Downloads/service-account-file.json"

    Example: Windows

    For PowerShell:

    $env:GOOGLE_APPLICATION_CREDENTIALS="KEY_PATH"

    Replace KEY_PATH with the path of the JSON file that contains your credentials.

    For example:

    $env:GOOGLE_APPLICATION_CREDENTIALS="C:\Users\username\Downloads\service-account-file.json"

    For command prompt:

    set GOOGLE_APPLICATION_CREDENTIALS=KEY_PATH

    Replace KEY_PATH with the path of the JSON file that contains your credentials.

16. Install the Google Cloud CLI.

17. To initialize the gcloud CLI, run the following command:

    gcloud init

동영상에 주석 추가 요청 만들기

gcloud

gcloud CLI를 사용하여 분석할 동영상 경로에서 detect-labels 명령어를 호출합니다.

gcloud ml video detect-labels gs://YOUR_BUCKET/YOUR_OBJECT

명령줄

1. curl을 사용하여 videos:annotate 메서드에 대해 POST 요청을 수행합니다. gcloud auth application-default print-access-token 명령어를 사용하여 서비스 계정에 액세스 토큰을 붙여넣습니다.

   curl -X POST \
     -H "Authorization: Bearer "$(gcloud auth application-default print-access-token) \
     -H "Content-Type: application/json; charset=utf-8" \
     --data '{"inputUri":"gs://YOUR_BUCKET/YOUR_OBJECT","features":["LABEL_DETECTION"]}'\
     "https://videointelligence.googleapis.com/v1/videos:annotate"

2. Video Intelligence API가 요청을 처리하는 작업을 만듭니다. 응답에는 작업 이름이 포함됩니다.

   {
     "name": "projects/PROJECT_NUMBER/locations/LOCATION_ID/operations/OPERATION_ID"
   }

3. v1.operations 엔드포인트를 호출하고, 아래 예시의 OPERATION_NAME을 이전 단계에서 반환된 이름으로 바꿔서 작업에 대한 정보를 요청할 수 있습니다.

    curl -X GET \
      -H "Authorization: Bearer "$(gcloud auth application-default print-access-token) \
      https://videointelligence.googleapis.com/v1/OPERATION_NAME

4. 작업과 관련된 정보가 표시됩니다. 작업이 완료되면 done 필드가 포함되고 true로 설정됩니다.

   {
     "name": "projects/PROJECT_NUMBER/locations/LOCATION_ID/operations/OPERATION_ID",
     "metadata": {
     "@type": "type.googleapis.com/google.cloud.videointelligence.v1.AnnotateVideoProgress",
       "annotationProgress": [
         {
           "inputUri": "/YOUR_BUCKET/YOUR_OBJECT",
           "progressPercent": 100,
           "startTime": "2020-04-01T22:13:17.978847Z",
           "updateTime": "2020-04-01T22:13:29.576004Z"
         }
       ]
     },
     "done": true,
    ...
   }

요청을 잠시(보통 1분 정도) 기다리면 동일한 요청이 주석 결과를 반환합니다.

{
  "name": "projects/PROJECT_NUMBER/locations/LOCATION_ID/operations/OPERATION_ID",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.videointelligence.v1.AnnotateVideoProgress",
    "annotationProgress": [
      {
        "inputUri": "YOUR_BUCKET/YOUR_OBJECT",
        "progressPercent": 100,
        "startTime": "2020-04-01T22:13:17.978847Z",
        "updateTime": "2020-04-01T22:13:29.576004Z"
      }
    ]
  },
  "done": true,
  "response": {
    "@type": "type.googleapis.com/google.cloud.videointelligence.v1.AnnotateVideoResponse",
    "annotationResults": [
      {
        "inputUri": "/YOUR_BUCKET/YOUR_OBJECT",
        "segmentLabelAnnotations": [
          {
            "entity": {
              "entityId": "/m/07bsy",
              "description": "transport",
              "languageCode": "en-US"
            },
            "segments": [
              {
                "segment": {
                  "startTimeOffset": "0s",
                  "endTimeOffset": "38.757872s"
                },
                "confidence": 0.81231534
              }
            ]
          },
         {
          "entity": {
              "entityId": "/m/01n32",
              "description": "city",
              "languageCode": "en-US"
            },
            "categoryEntities": [
              {
                "entityId": "/m/043rvww",
                "description": "geographical feature",
                "languageCode": "en-US"
              }
            ],
            "segments": [
              {
                "segment": {
                  "startTimeOffset": "0s",
                  "endTimeOffset": "38.757872s"
                },
                "confidence": 0.3942462
              }
            ]
          },
          ...
          {
            "entity": {
              "entityId": "/m/06gfj",
              "description": "road",
              "languageCode": "en-US"
            },
            "segments": [
              {
                "segment": {
                  "startTimeOffset": "0s",
                  "endTimeOffset": "38.757872s"
                },
                "confidence": 0.86698604
              }
            ]
          }
        ]
      }
    ]
  }
}
   

수고하셨습니다. 첫 번째 요청을 Video Intelligence API에 보냈습니다.

삭제

불필요한 Google Cloud 요금이 청구되지 않게 하려면 Google Cloud Console을 사용하여 필요하지 않은 프로젝트를 삭제합니다.

다음 단계

• 방법 가이드를 진행합니다.
• 샘플 및 가이드를 진행합니다.
• 모든 API 호출에 대한 자세한 정보는 API 참조를 확인하세요.