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Mendeteksi video tersimpan yang tidak pantas
Konten Amazon Rekognition Video yang tidak pantas atau menyinggung terdeteksi di dalam video yang disimpan adalah operasi tidak sinkron. Untuk mulai mendeteksi konten yang tidak pantas atau menyinggung, hubungi. StartContentModeration Amazon Rekognition Video menerbitkan status penyelesaian analisis video ke topik Amazon Simple Notification Service. Jika analisis video berhasil, hubungi GetContentModerationuntuk mendapatkan hasil analisis. Untuk informasi selengkapnya tentang memulai analisis video dan mendapatkan hasilnya, lihat Memanggil operasi Amazon Rekognition Video. Untuk daftar label moderasi di Amazon Rekognition, lihat Menggunakan moderasi gambar dan video. APIs
Prosedur ini diperluas pada kode di Menganalisis video yang disimpan dalam bucket Amazon S3 dengan Java atau Python () SDK, yang menggunakan antrean Amazon Simple Queue Service untuk mendapatkan status penyelesaian permintaan analisis video.
Untuk mendeteksi konten yang tidak pantas atau menyinggung dalam video yang disimpan di bucket Amazon S3 () SDK
Lakukan Menganalisis video yang disimpan dalam bucket Amazon S3 dengan Java atau Python () SDK.
Tambahkan kode berikut ke kelas VideoDetect yang Anda buat di langkah 1.
- Java
//Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
//PDX-License-Identifier: MIT-0 (For details, see https://github.com/awsdocs/amazon-rekognition-developer-guide/blob/master/LICENSE-SAMPLECODE.)
//Content moderation ==================================================================
private static void StartUnsafeContentDetection(String bucket, String video) throws Exception{
NotificationChannel channel= new NotificationChannel()
.withSNSTopicArn(snsTopicArn)
.withRoleArn(roleArn);
StartContentModerationRequest req = new StartContentModerationRequest()
.withVideo(new Video()
.withS3Object(new S3Object()
.withBucket(bucket)
.withName(video)))
.withNotificationChannel(channel);
StartContentModerationResult startModerationLabelDetectionResult = rek.startContentModeration(req);
startJobId=startModerationLabelDetectionResult.getJobId();
}
private static void GetUnsafeContentDetectionResults() throws Exception{
int maxResults=10;
String paginationToken=null;
GetContentModerationResult moderationLabelDetectionResult =null;
do{
if (moderationLabelDetectionResult !=null){
paginationToken = moderationLabelDetectionResult.getNextToken();
}
moderationLabelDetectionResult = rek.getContentModeration(
new GetContentModerationRequest()
.withJobId(startJobId)
.withNextToken(paginationToken)
.withSortBy(ContentModerationSortBy.TIMESTAMP)
.withMaxResults(maxResults));
VideoMetadata videoMetaData=moderationLabelDetectionResult.getVideoMetadata();
System.out.println("Format: " + videoMetaData.getFormat());
System.out.println("Codec: " + videoMetaData.getCodec());
System.out.println("Duration: " + videoMetaData.getDurationMillis());
System.out.println("FrameRate: " + videoMetaData.getFrameRate());
//Show moderated content labels, confidence and detection times
List<ContentModerationDetection> moderationLabelsInFrames=
moderationLabelDetectionResult.getModerationLabels();
for (ContentModerationDetection label: moderationLabelsInFrames) {
long seconds=label.getTimestamp()/1000;
System.out.print("Sec: " + Long.toString(seconds));
System.out.println(label.getModerationLabel().toString());
System.out.println();
}
} while (moderationLabelDetectionResult !=null && moderationLabelDetectionResult.getNextToken() != null);
}
Dalam fungsi main, ganti baris:
StartLabelDetection(bucket, video);
if (GetSQSMessageSuccess()==true)
GetLabelDetectionResults();
dengan:
StartUnsafeContentDetection(bucket, video);
if (GetSQSMessageSuccess()==true)
GetUnsafeContentDetectionResults();
- Java V2
-
Kode ini diambil dari GitHub repositori SDK contoh AWS Dokumentasi. Lihat contoh lengkapnya di sini.
import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.rekognition.RekognitionClient;
import software.amazon.awssdk.services.rekognition.model.NotificationChannel;
import software.amazon.awssdk.services.rekognition.model.S3Object;
import software.amazon.awssdk.services.rekognition.model.Video;
import software.amazon.awssdk.services.rekognition.model.StartContentModerationRequest;
import software.amazon.awssdk.services.rekognition.model.StartContentModerationResponse;
import software.amazon.awssdk.services.rekognition.model.RekognitionException;
import software.amazon.awssdk.services.rekognition.model.GetContentModerationResponse;
import software.amazon.awssdk.services.rekognition.model.GetContentModerationRequest;
import software.amazon.awssdk.services.rekognition.model.VideoMetadata;
import software.amazon.awssdk.services.rekognition.model.ContentModerationDetection;
import java.util.List;
/**
* Before running this Java V2 code example, set up your development
* environment, including your credentials.
*
* For more information, see the following documentation topic:
*
* https://docs.aws.amazon.com/sdk-for-java/latest/developer-guide/get-started.html
*/
public class VideoDetectInappropriate {
private static String startJobId = "";
public static void main(String[] args) {
final String usage = """
Usage: <bucket> <video> <topicArn> <roleArn>
Where:
bucket - The name of the bucket in which the video is located (for example, (for example, myBucket).\s
video - The name of video (for example, people.mp4).\s
topicArn - The ARN of the Amazon Simple Notification Service (Amazon SNS) topic.\s
roleArn - The ARN of the AWS Identity and Access Management (IAM) role to use.\s
""";
if (args.length != 4) {
System.out.println(usage);
System.exit(1);
}
String bucket = args[0];
String video = args[1];
String topicArn = args[2];
String roleArn = args[3];
Region region = Region.US_EAST_1;
RekognitionClient rekClient = RekognitionClient.builder()
.region(region)
.build();
NotificationChannel channel = NotificationChannel.builder()
.snsTopicArn(topicArn)
.roleArn(roleArn)
.build();
startModerationDetection(rekClient, channel, bucket, video);
getModResults(rekClient);
System.out.println("This example is done!");
rekClient.close();
}
public static void startModerationDetection(RekognitionClient rekClient,
NotificationChannel channel,
String bucket,
String video) {
try {
S3Object s3Obj = S3Object.builder()
.bucket(bucket)
.name(video)
.build();
Video vidOb = Video.builder()
.s3Object(s3Obj)
.build();
StartContentModerationRequest modDetectionRequest = StartContentModerationRequest.builder()
.jobTag("Moderation")
.notificationChannel(channel)
.video(vidOb)
.build();
StartContentModerationResponse startModDetectionResult = rekClient
.startContentModeration(modDetectionRequest);
startJobId = startModDetectionResult.jobId();
} catch (RekognitionException e) {
System.out.println(e.getMessage());
System.exit(1);
}
}
public static void getModResults(RekognitionClient rekClient) {
try {
String paginationToken = null;
GetContentModerationResponse modDetectionResponse = null;
boolean finished = false;
String status;
int yy = 0;
do {
if (modDetectionResponse != null)
paginationToken = modDetectionResponse.nextToken();
GetContentModerationRequest modRequest = GetContentModerationRequest.builder()
.jobId(startJobId)
.nextToken(paginationToken)
.maxResults(10)
.build();
// Wait until the job succeeds.
while (!finished) {
modDetectionResponse = rekClient.getContentModeration(modRequest);
status = modDetectionResponse.jobStatusAsString();
if (status.compareTo("SUCCEEDED") == 0)
finished = true;
else {
System.out.println(yy + " status is: " + status);
Thread.sleep(1000);
}
yy++;
}
finished = false;
// Proceed when the job is done - otherwise VideoMetadata is null.
VideoMetadata videoMetaData = modDetectionResponse.videoMetadata();
System.out.println("Format: " + videoMetaData.format());
System.out.println("Codec: " + videoMetaData.codec());
System.out.println("Duration: " + videoMetaData.durationMillis());
System.out.println("FrameRate: " + videoMetaData.frameRate());
System.out.println("Job");
List<ContentModerationDetection> mods = modDetectionResponse.moderationLabels();
for (ContentModerationDetection mod : mods) {
long seconds = mod.timestamp() / 1000;
System.out.print("Mod label: " + seconds + " ");
System.out.println(mod.moderationLabel().toString());
System.out.println();
}
} while (modDetectionResponse != null && modDetectionResponse.nextToken() != null);
} catch (RekognitionException | InterruptedException e) {
System.out.println(e.getMessage());
System.exit(1);
}
}
}
- Python
#Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#PDX-License-Identifier: MIT-0 (For details, see https://github.com/awsdocs/amazon-rekognition-developer-guide/blob/master/LICENSE-SAMPLECODE.)
# ============== Unsafe content ===============
def StartUnsafeContent(self):
response=self.rek.start_content_moderation(Video={'S3Object': {'Bucket': self.bucket, 'Name': self.video}},
NotificationChannel={'RoleArn': self.roleArn, 'SNSTopicArn': self.snsTopicArn})
self.startJobId=response['JobId']
print('Start Job Id: ' + self.startJobId)
def GetUnsafeContentResults(self):
maxResults = 10
paginationToken = ''
finished = False
while finished == False:
response = self.rek.get_content_moderation(JobId=self.startJobId,
MaxResults=maxResults,
NextToken=paginationToken,
SortBy="NAME",
AggregateBy="TIMESTAMPS")
print('Codec: ' + response['VideoMetadata']['Codec'])
print('Duration: ' + str(response['VideoMetadata']['DurationMillis']))
print('Format: ' + response['VideoMetadata']['Format'])
print('Frame rate: ' + str(response['VideoMetadata']['FrameRate']))
print()
for contentModerationDetection in response['ModerationLabels']:
print('Label: ' +
str(contentModerationDetection['ModerationLabel']['Name']))
print('Confidence: ' +
str(contentModerationDetection['ModerationLabel']['Confidence']))
print('Parent category: ' +
str(contentModerationDetection['ModerationLabel']['ParentName']))
print('Timestamp: ' + str(contentModerationDetection['Timestamp']))
print()
if 'NextToken' in response:
paginationToken = response['NextToken']
else:
finished = True
Dalam fungsi main, ganti baris:
analyzer.StartLabelDetection()
if analyzer.GetSQSMessageSuccess()==True:
analyzer.GetLabelDetectionResults()
dengan:
analyzer.StartUnsafeContent()
if analyzer.GetSQSMessageSuccess()==True:
analyzer.GetUnsafeContentResults()
Jalankan kode tersebut. Daftar label konten yang tidak pantas yang terdeteksi di video akan ditampilkan.
GetContentModeration respon operasi
Respons dari GetContentModeration adalah array,ModerationLabels, dari ContentModerationDetectionobjek. Array berisi elemen untuk setiap kali label konten yang tidak pantas terdeteksi. Dalam suatu ContentModerationDetectionObject objek, ModerationLabelberisi informasi untuk item yang terdeteksi dari konten yang tidak pantas atau menyinggung. Timestampadalah waktu, dalam milidetik dari awal video, ketika label terdeteksi. Label disusun secara hierarkis dengan cara yang sama seperti label yang terdeteksi oleh analisis citra konten yang tidak pantas. Untuk informasi selengkapnya, lihat Memoderasi konten.
Berikut ini adalah contoh respons dariGetContentModeration, diurutkan berdasarkan NAME dan dikumpulkan berdasarkan. TIMESTAMPS
{
"JobStatus": "SUCCEEDED",
"VideoMetadata": {
"Codec": "h264",
"DurationMillis": 54100,
"Format": "QuickTime / MOV",
"FrameRate": 30.0,
"FrameHeight": 462,
"FrameWidth": 884,
"ColorRange": "LIMITED"
},
"ModerationLabels": [
{
"Timestamp": 36000,
"ModerationLabel": {
"Confidence": 52.451576232910156,
"Name": "Alcohol",
"ParentName": "",
"TaxonomyLevel": 1
},
"ContentTypes": [
{
"Confidence": 99.9999008178711,
"Name": "Animated"
}
]
},
{
"Timestamp": 36000,
"ModerationLabel": {
"Confidence": 52.451576232910156,
"Name": "Alcoholic Beverages",
"ParentName": "Alcohol",
"TaxonomyLevel": 2
},
"ContentTypes": [
{
"Confidence": 99.9999008178711,
"Name": "Animated"
}
]
}
],
"ModerationModelVersion": "7.0",
"JobId": "a1b2c3d4...",
"Video": {
"S3Object": {
"Bucket": "bucket-name",
"Name": "video-name.mp4"
}
},
"GetRequestMetadata": {
"SortBy": "TIMESTAMP",
"AggregateBy": "TIMESTAMPS"
}
}
Berikut ini adalah contoh respons dariGetContentModeration, diurutkan berdasarkan NAME dan dikumpulkan berdasarkan. SEGMENTS
{
"JobStatus": "SUCCEEDED",
"VideoMetadata": {
"Codec": "h264",
"DurationMillis": 54100,
"Format": "QuickTime / MOV",
"FrameRate": 30.0,
"FrameHeight": 462,
"FrameWidth": 884,
"ColorRange": "LIMITED"
},
"ModerationLabels": [
{
"Timestamp": 0,
"ModerationLabel": {
"Confidence": 0.0003000000142492354,
"Name": "Alcohol Use",
"ParentName": "Alcohol",
"TaxonomyLevel": 2
},
"StartTimestampMillis": 0,
"EndTimestampMillis": 29520,
"DurationMillis": 29520,
"ContentTypes": [
{
"Confidence": 99.9999008178711,
"Name": "Illustrated"
},
{
"Confidence": 99.9999008178711,
"Name": "Animated"
}
]
}
],
"ModerationModelVersion": "7.0",
"JobId": "a1b2c3d4...",
"Video": {
"S3Object": {
"Bucket": "bucket-name",
"Name": "video-name.mp4"
}
},
"GetRequestMetadata": {
"SortBy": "TIMESTAMP",
"AggregateBy": "SEGMENTS"
}
}
