**Shot change analysis** detects shot changes in a video. This section demonstrates a few ways to analyze a video for shot changes. Here is an example of performing video analysis for shot changes on a file located in Cloud Storage. *Looking for something more in-depth? Check out our detailed [Python tutorial](https://docs.cloud.google.com/video-intelligence/docs/shot_detection).* ### REST ## Send video annotation request The following shows how to send a POST request to the [`videos:annotate`](https://docs.cloud.google.com/video-intelligence/docs/reference/rest/v1/videos/annotate) method. The example uses the Google Cloud CLI to create an access token. For instructions on installing the gcloud CLI, see the [Video Intelligence API Quickstart](https://docs.cloud.google.com/video-intelligence/docs/quickstarts). Before using any of the request data, make the following replacements: - INPUT_URI: a Cloud Storage bucket that contains the file you want to annotate, including the file name. Must start with `gs://`. - PROJECT_NUMBER: The numeric identifier for your Google Cloud project HTTP method and URL: ``` POST https://videointelligence.googleapis.com/v1/videos:annotate ``` Request JSON body: ``` { "inputUri": "INPUT_URI", "features": ["SHOT_CHANGE_DETECTION"] } ``` To send your request, expand one of these options: #### curl (Linux, macOS, or Cloud Shell) > [!NOTE] > **Note:** The following command assumes that you have logged in to the `gcloud` CLI with your user account by running [`gcloud init`](https://docs.cloud.google.com/sdk/gcloud/reference/init) or [`gcloud auth login`](https://docs.cloud.google.com/sdk/gcloud/reference/auth/login) , or by using [Cloud Shell](https://docs.cloud.google.com/shell/docs), which automatically logs you into the `gcloud` CLI . You can check the currently active account by running [`gcloud auth list`](https://docs.cloud.google.com/sdk/gcloud/reference/auth/list). Save the request body in a file named `request.json`, and execute the following command: ``` curl -X POST \ -H "Authorization: Bearer $(gcloud auth print-access-token)" \ -H "x-goog-user-project: PROJECT_NUMBER" \ -H "Content-Type: application/json; charset=utf-8" \ -d @request.json \ "https://videointelligence.googleapis.com/v1/videos:annotate" ``` #### PowerShell (Windows) > [!NOTE] > **Note:** The following command assumes that you have logged in to the `gcloud` CLI with your user account by running [`gcloud init`](https://docs.cloud.google.com/sdk/gcloud/reference/init) or [`gcloud auth login`](https://docs.cloud.google.com/sdk/gcloud/reference/auth/login) . You can check the currently active account by running [`gcloud auth list`](https://docs.cloud.google.com/sdk/gcloud/reference/auth/list). Save the request body in a file named `request.json`, and execute the following command: ``` $cred = gcloud auth print-access-token $headers = @{ "Authorization" = "Bearer $cred"; "x-goog-user-project" = "PROJECT_NUMBER" } Invoke-WebRequest ` -Method POST ` -Headers $headers ` -ContentType: "application/json; charset=utf-8" ` -InFile request.json ` -Uri "https://videointelligence.googleapis.com/v1/videos:annotate" | Select-Object -Expand Content ``` You should receive a JSON response similar to the following: #### Response ``` { "name": "projects/PROJECT_NUMBER/locations/LOCATION_ID/operations/OPERATION_ID" } ``` If the response is successful, the Video Intelligence API returns the `name` for your operation. The above shows an example of such a response, where `project-name` is the name of your project and `operation-id` is the ID of the long running operation created for the request.
- PROJECT_NUMBER: the number of your project - LOCATION_ID: the Cloud region where annotation should take place. Supported cloud regions are: `us-east1`, `us-west1`, `europe-west1`, `asia-east1`. If no region is specified, a region will be determined based on video file location. - OPERATION_ID: the ID of the long running operation created for the request and provided in the response when you started the operation, for example `12345....` ## Get annotation results To retrieve the result of the operation, make a [GET](https://docs.cloud.google.com/video-intelligence/docs/reference/rest/v1/projects.locations.operations/get) request, using the operation name returned from the call to [`videos:annotate`](https://docs.cloud.google.com/video-intelligence/docs/reference/rest/v1/videos/annotate), as shown in the following example. Before using any of the request data, make the following replacements: - OPERATION_NAME: the name of the operation as returned by Video Intelligence API. The operation name has the format `projects/PROJECT_NUMBER/locations/LOCATION_ID/operations/OPERATION_ID` - PROJECT_NUMBER: The numeric identifier for your Google Cloud project HTTP method and URL: ``` GET https://videointelligence.googleapis.com/v1/OPERATION_NAME ``` To send your request, expand one of these options: #### curl (Linux, macOS, or Cloud Shell) > [!NOTE] > **Note:** The following command assumes that you have logged in to the `gcloud` CLI with your user account by running [`gcloud init`](https://docs.cloud.google.com/sdk/gcloud/reference/init) or [`gcloud auth login`](https://docs.cloud.google.com/sdk/gcloud/reference/auth/login) , or by using [Cloud Shell](https://docs.cloud.google.com/shell/docs), which automatically logs you into the `gcloud` CLI . You can check the currently active account by running [`gcloud auth list`](https://docs.cloud.google.com/sdk/gcloud/reference/auth/list). Execute the following command: ``` curl -X GET \ -H "Authorization: Bearer $(gcloud auth print-access-token)" \ -H "x-goog-user-project: PROJECT_NUMBER" \ "https://videointelligence.googleapis.com/v1/OPERATION_NAME" ``` #### PowerShell (Windows) > [!NOTE] > **Note:** The following command assumes that you have logged in to the `gcloud` CLI with your user account by running [`gcloud init`](https://docs.cloud.google.com/sdk/gcloud/reference/init) or [`gcloud auth login`](https://docs.cloud.google.com/sdk/gcloud/reference/auth/login) . You can check the currently active account by running [`gcloud auth list`](https://docs.cloud.google.com/sdk/gcloud/reference/auth/list). Execute the following command: ``` $cred = gcloud auth print-access-token $headers = @{ "Authorization" = "Bearer $cred"; "x-goog-user-project" = "PROJECT_NUMBER" } Invoke-WebRequest ` -Method GET ` -Headers $headers ` -Uri "https://videointelligence.googleapis.com/v1/OPERATION_NAME" | Select-Object -Expand Content ``` You should receive a JSON response similar to the following: #### Response ``` { "inputUri": "/demomaker/gbikes_dinosaur.mp4", "shotAnnotations": [ { "startTimeOffset": "0s", "endTimeOffset": "5.167104s" }, { "startTimeOffset": "5.236736s", "endTimeOffset": "10.072064s" }, { "startTimeOffset": "10.106880s", "endTimeOffset": "28.139520s" }, { "startTimeOffset": "28.174336s", "endTimeOffset": "42.768384s" } ] } ``` Shot detection annotations are returned as a `shotAnnotations` list. Note: The **done** field is only returned when its value is **True** . It's not included in responses for which the operation has not completed.
## Download annotation results Copy the annotation from the source to the destination bucket: (see [Copy files and objects](https://docs.cloud.google.com/sdk/gcloud/reference/storage/cp)) `gcloud storage cp gcs_uri gs://my-bucket` Note: If the output gcs uri is provided by the user, then the annotation is stored in that gcs uri. ### Go func shotChangeURI(w io.Writer, file string) error { ctx := context.Background() client, err := video.NewClient(ctx) if err != nil { return err } defer client.Close() op, err := client.AnnotateVideo(ctx, &videopb.AnnotateVideoRequest{ Features: []videopb.Feature{ videopb.Feature_SHOT_CHANGE_DETECTION, }, InputUri: file, }) if err != nil { return err } resp, err := op.Wait(ctx) if err != nil { return err } // A single video was processed. Get the first result. result := resp.AnnotationResults[0].ShotAnnotations for _, shot := range result { start, _ := ptypes.Duration(shot.StartTimeOffset) end, _ := ptypes.Duration(shot.EndTimeOffset) fmt.Fprintf(w, "Shot: %s to %s\n", start, end) } return nil } ### Java To authenticate to Video Intelligence, set up Application Default Credentials. For more information, see [Set up authentication for a local development environment](https://docs.cloud.google.com/docs/authentication/set-up-adc-local-dev-environment). // Instantiate a com.google.cloud.videointelligence.v1.VideoIntelligenceServiceClient try (VideoIntelligenceServiceClient client = VideoIntelligenceServiceClient.create()) { // Provide path to file hosted on GCS as "gs://bucket-name/..." AnnotateVideoRequest request = AnnotateVideoRequest.newBuilder() .setInputUri(gcsUri) .addFeatures(Feature.SHOT_CHANGE_DETECTION) .build(); // Create an operation that will contain the response when the operation completes. OperationFuture response = client.annotateVideoAsync(request); System.out.println("Waiting for operation to complete..."); // Print detected shot changes and their location ranges in the analyzed video. for (VideoAnnotationResults result : response.get().getAnnotationResultsList()) { if (result.getShotAnnotationsCount() > 0) { System.out.println("Shots: "); for (VideoSegment segment : result.getShotAnnotationsList()) { double startTime = segment.getStartTimeOffset().getSeconds() + segment.getStartTimeOffset().getNanos() / 1e9; double endTime = segment.getEndTimeOffset().getSeconds() + segment.getEndTimeOffset().getNanos() / 1e9; System.out.printf("Location: %.3f:%.3f\n", startTime, endTime); } } else { System.out.println("No shot changes detected in " + gcsUri); } } } ### Node.js To authenticate to Video Intelligence, set up Application Default Credentials. For more information, see [Set up authentication for a local development environment](https://docs.cloud.google.com/docs/authentication/set-up-adc-local-dev-environment). // Imports the Google Cloud Video Intelligence library const video = require('https://docs.cloud.google.com/nodejs/docs/reference/video-intelligence/latest/overview.html').v1; // Creates a client const client = new video.https://docs.cloud.google.com/nodejs/docs/reference/video-intelligence/latest/overview.html(); /** * TODO(developer): Uncomment the following line before running the sample. */ // const gcsUri = 'GCS URI of file to analyze, e.g. gs://my-bucket/my-video.mp4'; const request = { inputUri: gcsUri, features: ['SHOT_CHANGE_DETECTION'], }; // Detects camera shot changes const [operation] = await client.annotateVideo(request); console.log('Waiting for operation to complete...'); const [operationResult] = await operation.promise(); // Gets shot changes const shotChanges = operationResult.annotationResults[0].shotAnnotations; console.log('Shot changes:'); if (shotChanges.length === 1) { console.log('The entire video is one shot.'); } else { shotChanges.forEach((shot, shotIdx) => { console.log(`Scene ${shotIdx} occurs from:`); if (shot.startTimeOffset === undefined) { shot.startTimeOffset = {}; } if (shot.endTimeOffset === undefined) { shot.endTimeOffset = {}; } if (shot.startTimeOffset.seconds === undefined) { shot.startTimeOffset.seconds = 0; } if (shot.startTimeOffset.nanos === undefined) { shot.startTimeOffset.nanos = 0; } if (shot.endTimeOffset.seconds === undefined) { shot.endTimeOffset.seconds = 0; } if (shot.endTimeOffset.nanos === undefined) { shot.endTimeOffset.nanos = 0; } console.log( `\tStart: ${shot.startTimeOffset.seconds}` + `.${(shot.startTimeOffset.nanos / 1e6).toFixed(0)}s` ); console.log( `\tEnd: ${shot.endTimeOffset.seconds}.` + `${(shot.endTimeOffset.nanos / 1e6).toFixed(0)}s` ); }); } ### Python For more information on installing and using the Video Intelligence API Client Library for Python, refer to [Video Intelligence API Client Libraries](https://docs.cloud.google.com/video-intelligence/docs/reference/libraries). """Detects camera shot changes.""" video_client = videointelligence.VideoIntelligenceServiceClient() features = [videointelligence.Feature.SHOT_CHANGE_DETECTION] operation = video_client.annotate_video( request={"features": features, "input_uri": path} ) print("\nProcessing video for shot change annotations:") result = operation.result(timeout=90) print("\nFinished processing.") # first result is retrieved because a single video was processed for i, shot in enumerate(result.annotation_results[0].shot_annotations): start_time = ( shot.start_time_offset.seconds + shot.start_time_offset.microseconds / 1e6 ) end_time = ( shot.end_time_offset.seconds + shot.end_time_offset.microseconds / 1e6 ) print("\tShot {}: {} to {}".format(i, start_time, end_time)) ### Additional languages **C#** : Please follow the [C# setup instructions](https://docs.cloud.google.com/video-intelligence/docs/libraries) on the client libraries page and then visit the [Video Intelligence reference documentation for .NET.](https://googleapis.github.io/google-cloud-dotnet/docs/Google.Cloud.VideoIntelligence.V1/index.html) **PHP** : Please follow the [PHP setup instructions](https://docs.cloud.google.com/video-intelligence/docs/libraries) on the client libraries page and then visit the [Video Intelligence reference documentation for PHP.](https://docs.cloud.google.com/php/docs/reference/cloud-videointelligence/latest) **Ruby** : Please follow the [Ruby setup instructions](https://docs.cloud.google.com/video-intelligence/docs/libraries) on the client libraries page and then visit the [Video Intelligence reference documentation for Ruby.](https://googleapis.dev/ruby/google-cloud-video_intelligence/latest/Google/Cloud/VideoIntelligence/V1.html)