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使用 Amazon Rekognition 的示例 Amazon CLI
以下代码示例向您展示了如何使用 Amazon Command Line Interface 与 Amazon Rekognition 配合使用来执行操作和实现常见场景。
操作是大型程序的代码摘录，必须在上下文中运行。您可以通过操作了解如何调用单个服务函数，还可以通过函数相关场景和跨服务示例的上下文查看操作。
场景是展示如何通过在同一服务中调用多个函数来完成特定任务任务的代码示例。
每个示例都包含一个指向的链接 GitHub，您可以在其中找到有关如何在上下文中设置和运行代码的说明。
主题
操作
以下代码示例演示如何使用 compare-faces。
有关更多信息，请参阅比较图像中的人脸。
- Amazon CLI
-
比较两张图像中的人脸
以下
compare-faces命令将比较存储在 Amazon S3 存储桶中的两张图像中的人脸。aws rekognition compare-faces \ --source-image '{"S3Object":{"Bucket":"MyImageS3Bucket","Name":"source.jpg"}}' \ --target-image '{"S3Object":{"Bucket":"MyImageS3Bucket","Name":"target.jpg"}}'输出：
{ "UnmatchedFaces": [], "FaceMatches": [ { "Face": { "BoundingBox": { "Width": 0.12368916720151901, "Top": 0.16007372736930847, "Left": 0.5901257991790771, "Height": 0.25140416622161865 }, "Confidence": 100.0, "Pose": { "Yaw": -3.7351467609405518, "Roll": -0.10309021919965744, "Pitch": 0.8637830018997192 }, "Quality": { "Sharpness": 95.51618957519531, "Brightness": 65.29893493652344 }, "Landmarks": [ { "Y": 0.26721030473709106, "X": 0.6204193830490112, "Type": "eyeLeft" }, { "Y": 0.26831310987472534, "X": 0.6776827573776245, "Type": "eyeRight" }, { "Y": 0.3514654338359833, "X": 0.6241428852081299, "Type": "mouthLeft" }, { "Y": 0.35258132219314575, "X": 0.6713621020317078, "Type": "mouthRight" }, { "Y": 0.3140771687030792, "X": 0.6428444981575012, "Type": "nose" } ] }, "Similarity": 100.0 } ], "SourceImageFace": { "BoundingBox": { "Width": 0.12368916720151901, "Top": 0.16007372736930847, "Left": 0.5901257991790771, "Height": 0.25140416622161865 }, "Confidence": 100.0 } }有关更多信息，请参阅《Amazon Rekognition 开发人员指南》中的比较图像中的人脸。
-
有关 API 的详细信息，请参阅Amazon CLI 命令参考CompareFaces
中的。
-
以下代码示例演示如何使用 create-collection。
有关更多信息，请参阅创建集合。
- Amazon CLI
-
创建集合
以下
create-collection命令创建具有指定名称的集合。aws rekognition create-collection \ --collection-id "MyCollection"输出：
{ "CollectionArn": "aws:rekognition:us-west-2:123456789012:collection/MyCollection", "FaceModelVersion": "4.0", "StatusCode": 200 }有关更多信息，请参阅《Amazon Rekognition 开发人员指南》中的创建集合。
-
有关 API 的详细信息，请参阅Amazon CLI 命令参考CreateCollection
中的。
-
以下代码示例演示如何使用 create-stream-processor。
- Amazon CLI
-
创建新的流处理器
以下
create-stream-processor示例使用指定配置创建新的流处理器。aws rekognition create-stream-processor --name my-stream-processor\ --input '{"KinesisVideoStream":{"Arn":"arn:aws:kinesisvideo:us-west-2:123456789012:stream/macwebcam/1530559711205"}}'\ --stream-processor-output '{"KinesisDataStream":{"Arn":"arn:aws:kinesis:us-west-2:123456789012:stream/AmazonRekognitionRekStream"}}'\ --role-arn arn:aws:iam::123456789012:role/AmazonRekognitionDetect\ --settings '{"FaceSearch":{"CollectionId":"MyCollection","FaceMatchThreshold":85.5}}'输出：
{ "StreamProcessorArn": "arn:aws:rekognition:us-west-2:123456789012:streamprocessor/my-stream-processor" }有关更多信息，请参阅亚马逊 Rekognition 开发者指南中的使用流媒体视频。
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有关 API 的详细信息，请参阅Amazon CLI 命令参考CreateStreamProcessor
中的。
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以下代码示例演示如何使用 delete-collection。
有关更多信息，请参阅删除集合。
- Amazon CLI
-
删除集合
以下
delete-collection命令将删除指定的集合。aws rekognition delete-collection \ --collection-id MyCollection输出：
{ "StatusCode": 200 }有关更多信息，请参阅《Amazon Rekognition 开发人员指南》中的删除集合。
-
有关 API 的详细信息，请参阅Amazon CLI 命令参考DeleteCollection
中的。
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以下代码示例演示如何使用 delete-faces。
有关更多信息，请参阅从集中删除人脸。
- Amazon CLI
-
从集合中删除人脸
以下
delete-faces命令将从集合中删除指定的人脸。aws rekognition delete-faces \ --collection-id MyCollection --face-ids '["0040279c-0178-436e-b70a-e61b074e96b0"]'输出：
{ "DeletedFaces": [ "0040279c-0178-436e-b70a-e61b074e96b0" ] }有关更多信息，请参阅《Amazon Rekognition 开发人员指南》中的从集合中删除人脸。
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有关 API 的详细信息，请参阅Amazon CLI 命令参考DeleteFaces
中的。
-
以下代码示例演示如何使用 delete-stream-processor。
- Amazon CLI
-
删除流处理器
以下
delete-stream-processor命令删除指定的流处理器。aws rekognition delete-stream-processor \ --name my-stream-processor此命令不生成任何输出。
有关更多信息，请参阅亚马逊 Rekognition 开发者指南中的使用流媒体视频。
-
有关 API 的详细信息，请参阅Amazon CLI 命令参考DeleteStreamProcessor
中的。
-
以下代码示例演示如何使用 describe-collection。
有关更多信息，请参阅描述集合。
- Amazon CLI
-
描述集合
以下
describe-collection示例显示有关指定集合的详细信息。aws rekognition describe-collection \ --collection-id MyCollection输出：
{ "FaceCount": 200, "CreationTimestamp": 1569444828.274, "CollectionARN": "arn:aws:rekognition:us-west-2:123456789012:collection/MyCollection", "FaceModelVersion": "4.0" }有关更多信息，请参阅《Amazon Rekognition 开发人员指南》中的描述集合。
-
有关 API 的详细信息，请参阅Amazon CLI 命令参考DescribeCollection
中的。
-
以下代码示例演示如何使用 describe-stream-processor。
- Amazon CLI
-
获取有关流处理器的信息
以下
describe-stream-processor命令显示有关指定流处理器的详细信息。aws rekognition describe-stream-processor \ --name my-stream-processor输出：
{ "Status": "STOPPED", "Name": "my-stream-processor", "LastUpdateTimestamp": 1532449292.712, "Settings": { "FaceSearch": { "FaceMatchThreshold": 80.0, "CollectionId": "my-collection" } }, "RoleArn": "arn:aws:iam::123456789012:role/AmazonRekognitionDetectStream", "StreamProcessorArn": "arn:aws:rekognition:us-west-2:123456789012:streamprocessor/my-stream-processpr", "Output": { "KinesisDataStream": { "Arn": "arn:aws:kinesis:us-west-2:123456789012:stream/AmazonRekognitionRekStream" } }, "Input": { "KinesisVideoStream": { "Arn": "arn:aws:kinesisvideo:us-west-2:123456789012:stream/macwebcam/123456789012" } }, "CreationTimestamp": 1532449292.712 }有关更多信息，请参阅亚马逊 Rekognition 开发者指南中的使用流媒体视频。
-
有关 API 的详细信息，请参阅Amazon CLI 命令参考DescribeStreamProcessor
中的。
-
以下代码示例演示如何使用 detect-faces。
有关更多信息，请参阅检测图像中的人脸。
- Amazon CLI
-
检测图像中的人脸
以下
detect-faces命令将检测存储在 Amazon S3 存储桶中的指定图像中的人脸。aws rekognition detect-faces \ --image '{"S3Object":{"Bucket":"MyImageS3Bucket","Name":"MyFriend.jpg"}}' \ --attributes "ALL"输出：
{ "FaceDetails": [ { "Confidence": 100.0, "Eyeglasses": { "Confidence": 98.91107940673828, "Value": false }, "Sunglasses": { "Confidence": 99.7966537475586, "Value": false }, "Gender": { "Confidence": 99.56611633300781, "Value": "Male" }, "Landmarks": [ { "Y": 0.26721030473709106, "X": 0.6204193830490112, "Type": "eyeLeft" }, { "Y": 0.26831310987472534, "X": 0.6776827573776245, "Type": "eyeRight" }, { "Y": 0.3514654338359833, "X": 0.6241428852081299, "Type": "mouthLeft" }, { "Y": 0.35258132219314575, "X": 0.6713621020317078, "Type": "mouthRight" }, { "Y": 0.3140771687030792, "X": 0.6428444981575012, "Type": "nose" }, { "Y": 0.24662546813488007, "X": 0.6001564860343933, "Type": "leftEyeBrowLeft" }, { "Y": 0.24326619505882263, "X": 0.6303644776344299, "Type": "leftEyeBrowRight" }, { "Y": 0.23818562924861908, "X": 0.6146903038024902, "Type": "leftEyeBrowUp" }, { "Y": 0.24373626708984375, "X": 0.6640064716339111, "Type": "rightEyeBrowLeft" }, { "Y": 0.24877218902111053, "X": 0.7025929093360901, "Type": "rightEyeBrowRight" }, { "Y": 0.23938551545143127, "X": 0.6823262572288513, "Type": "rightEyeBrowUp" }, { "Y": 0.265746533870697, "X": 0.6112898588180542, "Type": "leftEyeLeft" }, { "Y": 0.2676128149032593, "X": 0.6317071914672852, "Type": "leftEyeRight" }, { "Y": 0.262735515832901, "X": 0.6201658248901367, "Type": "leftEyeUp" }, { "Y": 0.27025148272514343, "X": 0.6206279993057251, "Type": "leftEyeDown" }, { "Y": 0.268223375082016, "X": 0.6658390760421753, "Type": "rightEyeLeft" }, { "Y": 0.2672517001628876, "X": 0.687832236289978, "Type": "rightEyeRight" }, { "Y": 0.26383838057518005, "X": 0.6769183874130249, "Type": "rightEyeUp" }, { "Y": 0.27138751745224, "X": 0.676596462726593, "Type": "rightEyeDown" }, { "Y": 0.32283174991607666, "X": 0.6350004076957703, "Type": "noseLeft" }, { "Y": 0.3219289481639862, "X": 0.6567046642303467, "Type": "noseRight" }, { "Y": 0.3420318365097046, "X": 0.6450609564781189, "Type": "mouthUp" }, { "Y": 0.3664324879646301, "X": 0.6455618143081665, "Type": "mouthDown" }, { "Y": 0.26721030473709106, "X": 0.6204193830490112, "Type": "leftPupil" }, { "Y": 0.26831310987472534, "X": 0.6776827573776245, "Type": "rightPupil" }, { "Y": 0.26343393325805664, "X": 0.5946047306060791, "Type": "upperJawlineLeft" }, { "Y": 0.3543180525302887, "X": 0.6044883728027344, "Type": "midJawlineLeft" }, { "Y": 0.4084877669811249, "X": 0.6477024555206299, "Type": "chinBottom" }, { "Y": 0.3562754988670349, "X": 0.707981526851654, "Type": "midJawlineRight" }, { "Y": 0.26580461859703064, "X": 0.7234612107276917, "Type": "upperJawlineRight" } ], "Pose": { "Yaw": -3.7351467609405518, "Roll": -0.10309021919965744, "Pitch": 0.8637830018997192 }, "Emotions": [ { "Confidence": 8.74203109741211, "Type": "SURPRISED" }, { "Confidence": 2.501944065093994, "Type": "ANGRY" }, { "Confidence": 0.7378743290901184, "Type": "DISGUSTED" }, { "Confidence": 3.5296201705932617, "Type": "HAPPY" }, { "Confidence": 1.7162904739379883, "Type": "SAD" }, { "Confidence": 9.518536567687988, "Type": "CONFUSED" }, { "Confidence": 0.45474427938461304, "Type": "FEAR" }, { "Confidence": 72.79895782470703, "Type": "CALM" } ], "AgeRange": { "High": 48, "Low": 32 }, "EyesOpen": { "Confidence": 98.93987274169922, "Value": true }, "BoundingBox": { "Width": 0.12368916720151901, "Top": 0.16007372736930847, "Left": 0.5901257991790771, "Height": 0.25140416622161865 }, "Smile": { "Confidence": 93.4493179321289, "Value": false }, "MouthOpen": { "Confidence": 90.53053283691406, "Value": false }, "Quality": { "Sharpness": 95.51618957519531, "Brightness": 65.29893493652344 }, "Mustache": { "Confidence": 89.85221099853516, "Value": false }, "Beard": { "Confidence": 86.1991195678711, "Value": true } } ] }有关更多信息，请参阅《Amazon Rekognition 开发人员指南》中的检测图像中的人脸。
-
有关 API 的详细信息，请参阅Amazon CLI 命令参考DetectFaces
中的。
-
以下代码示例演示如何使用 detect-labels。
有关更多信息，请参阅检测图像中的标签。
- Amazon CLI
-
检测图像中的标签
以下
detect-labels示例将检测存储在 Amazon S3 存储桶中的图像中的场景和对象。aws rekognition detect-labels \ --image '{"S3Object":{"Bucket":"bucket","Name":"image"}}'输出：
{ "Labels": [ { "Instances": [], "Confidence": 99.15271759033203, "Parents": [ { "Name": "Vehicle" }, { "Name": "Transportation" } ], "Name": "Automobile" }, { "Instances": [], "Confidence": 99.15271759033203, "Parents": [ { "Name": "Transportation" } ], "Name": "Vehicle" }, { "Instances": [], "Confidence": 99.15271759033203, "Parents": [], "Name": "Transportation" }, { "Instances": [ { "BoundingBox": { "Width": 0.10616336017847061, "Top": 0.5039216876029968, "Left": 0.0037978808395564556, "Height": 0.18528179824352264 }, "Confidence": 99.15271759033203 }, { "BoundingBox": { "Width": 0.2429988533258438, "Top": 0.5251884460449219, "Left": 0.7309805154800415, "Height": 0.21577216684818268 }, "Confidence": 99.1286392211914 }, { "BoundingBox": { "Width": 0.14233611524105072, "Top": 0.5333095788955688, "Left": 0.6494812965393066, "Height": 0.15528248250484467 }, "Confidence": 98.48368072509766 }, { "BoundingBox": { "Width": 0.11086395382881165, "Top": 0.5354844927787781, "Left": 0.10355594009160995, "Height": 0.10271988064050674 }, "Confidence": 96.45606231689453 }, { "BoundingBox": { "Width": 0.06254628300666809, "Top": 0.5573825240135193, "Left": 0.46083059906959534, "Height": 0.053911514580249786 }, "Confidence": 93.65448760986328 }, { "BoundingBox": { "Width": 0.10105438530445099, "Top": 0.534368634223938, "Left": 0.5743985772132874, "Height": 0.12226245552301407 }, "Confidence": 93.06217193603516 }, { "BoundingBox": { "Width": 0.056389667093753815, "Top": 0.5235804319381714, "Left": 0.9427769780158997, "Height": 0.17163699865341187 }, "Confidence": 92.6864013671875 }, { "BoundingBox": { "Width": 0.06003860384225845, "Top": 0.5441341400146484, "Left": 0.22409997880458832, "Height": 0.06737709045410156 }, "Confidence": 90.4227066040039 }, { "BoundingBox": { "Width": 0.02848697081208229, "Top": 0.5107086896896362, "Left": 0, "Height": 0.19150497019290924 }, "Confidence": 86.65286254882812 }, { "BoundingBox": { "Width": 0.04067881405353546, "Top": 0.5566273927688599, "Left": 0.316415935754776, "Height": 0.03428703173995018 }, "Confidence": 85.36471557617188 }, { "BoundingBox": { "Width": 0.043411049991846085, "Top": 0.5394920110702515, "Left": 0.18293385207653046, "Height": 0.0893595889210701 }, "Confidence": 82.21705627441406 }, { "BoundingBox": { "Width": 0.031183116137981415, "Top": 0.5579366683959961, "Left": 0.2853088080883026, "Height": 0.03989990055561066 }, "Confidence": 81.0157470703125 }, { "BoundingBox": { "Width": 0.031113790348172188, "Top": 0.5504819750785828, "Left": 0.2580395042896271, "Height": 0.056484755128622055 }, "Confidence": 56.13441467285156 }, { "BoundingBox": { "Width": 0.08586374670267105, "Top": 0.5438792705535889, "Left": 0.5128012895584106, "Height": 0.08550430089235306 }, "Confidence": 52.37760925292969 } ], "Confidence": 99.15271759033203, "Parents": [ { "Name": "Vehicle" }, { "Name": "Transportation" } ], "Name": "Car" }, { "Instances": [], "Confidence": 98.9914321899414, "Parents": [], "Name": "Human" }, { "Instances": [ { "BoundingBox": { "Width": 0.19360728561878204, "Top": 0.35072067379951477, "Left": 0.43734854459762573, "Height": 0.2742200493812561 }, "Confidence": 98.9914321899414 }, { "BoundingBox": { "Width": 0.03801717236638069, "Top": 0.5010883808135986, "Left": 0.9155802130699158, "Height": 0.06597328186035156 }, "Confidence": 85.02790832519531 } ], "Confidence": 98.9914321899414, "Parents": [], "Name": "Person" }, { "Instances": [], "Confidence": 93.24951934814453, "Parents": [], "Name": "Machine" }, { "Instances": [ { "BoundingBox": { "Width": 0.03561960905790329, "Top": 0.6468243598937988, "Left": 0.7850857377052307, "Height": 0.08878646790981293 }, "Confidence": 93.24951934814453 }, { "BoundingBox": { "Width": 0.02217046171426773, "Top": 0.6149078607559204, "Left": 0.04757237061858177, "Height": 0.07136218994855881 }, "Confidence": 91.5025863647461 }, { "BoundingBox": { "Width": 0.016197510063648224, "Top": 0.6274210214614868, "Left": 0.6472989320755005, "Height": 0.04955997318029404 }, "Confidence": 85.14686584472656 }, { "BoundingBox": { "Width": 0.020207518711686134, "Top": 0.6348286867141724, "Left": 0.7295016646385193, "Height": 0.07059963047504425 }, "Confidence": 83.34547424316406 }, { "BoundingBox": { "Width": 0.020280985161662102, "Top": 0.6171894669532776, "Left": 0.08744934946298599, "Height": 0.05297485366463661 }, "Confidence": 79.9981460571289 }, { "BoundingBox": { "Width": 0.018318990245461464, "Top": 0.623889148235321, "Left": 0.6836880445480347, "Height": 0.06730121374130249 }, "Confidence": 78.87144470214844 }, { "BoundingBox": { "Width": 0.021310249343514442, "Top": 0.6167286038398743, "Left": 0.004064912907779217, "Height": 0.08317798376083374 }, "Confidence": 75.89361572265625 }, { "BoundingBox": { "Width": 0.03604431077837944, "Top": 0.7030032277107239, "Left": 0.9254803657531738, "Height": 0.04569442570209503 }, "Confidence": 64.402587890625 }, { "BoundingBox": { "Width": 0.009834849275648594, "Top": 0.5821820497512817, "Left": 0.28094568848609924, "Height": 0.01964157074689865 }, "Confidence": 62.79907989501953 }, { "BoundingBox": { "Width": 0.01475677452981472, "Top": 0.6137543320655823, "Left": 0.5950819253921509, "Height": 0.039063986390829086 }, "Confidence": 59.40483474731445 } ], "Confidence": 93.24951934814453, "Parents": [ { "Name": "Machine" } ], "Name": "Wheel" }, { "Instances": [], "Confidence": 92.61514282226562, "Parents": [], "Name": "Road" }, { "Instances": [], "Confidence": 92.37877655029297, "Parents": [ { "Name": "Person" } ], "Name": "Sport" }, { "Instances": [], "Confidence": 92.37877655029297, "Parents": [ { "Name": "Person" } ], "Name": "Sports" }, { "Instances": [ { "BoundingBox": { "Width": 0.12326609343290329, "Top": 0.6332163214683533, "Left": 0.44815489649772644, "Height": 0.058117982000112534 }, "Confidence": 92.37877655029297 } ], "Confidence": 92.37877655029297, "Parents": [ { "Name": "Person" }, { "Name": "Sport" } ], "Name": "Skateboard" }, { "Instances": [], "Confidence": 90.62931060791016, "Parents": [ { "Name": "Person" } ], "Name": "Pedestrian" }, { "Instances": [], "Confidence": 88.81334686279297, "Parents": [], "Name": "Asphalt" }, { "Instances": [], "Confidence": 88.81334686279297, "Parents": [], "Name": "Tarmac" }, { "Instances": [], "Confidence": 88.23201751708984, "Parents": [], "Name": "Path" }, { "Instances": [], "Confidence": 80.26520538330078, "Parents": [], "Name": "Urban" }, { "Instances": [], "Confidence": 80.26520538330078, "Parents": [ { "Name": "Building" }, { "Name": "Urban" } ], "Name": "Town" }, { "Instances": [], "Confidence": 80.26520538330078, "Parents": [], "Name": "Building" }, { "Instances": [], "Confidence": 80.26520538330078, "Parents": [ { "Name": "Building" }, { "Name": "Urban" } ], "Name": "City" }, { "Instances": [], "Confidence": 78.37934875488281, "Parents": [ { "Name": "Car" }, { "Name": "Vehicle" }, { "Name": "Transportation" } ], "Name": "Parking Lot" }, { "Instances": [], "Confidence": 78.37934875488281, "Parents": [ { "Name": "Car" }, { "Name": "Vehicle" }, { "Name": "Transportation" } ], "Name": "Parking" }, { "Instances": [], "Confidence": 74.37590026855469, "Parents": [ { "Name": "Building" }, { "Name": "Urban" }, { "Name": "City" } ], "Name": "Downtown" }, { "Instances": [], "Confidence": 69.84622955322266, "Parents": [ { "Name": "Road" } ], "Name": "Intersection" }, { "Instances": [], "Confidence": 57.68518829345703, "Parents": [ { "Name": "Sports Car" }, { "Name": "Car" }, { "Name": "Vehicle" }, { "Name": "Transportation" } ], "Name": "Coupe" }, { "Instances": [], "Confidence": 57.68518829345703, "Parents": [ { "Name": "Car" }, { "Name": "Vehicle" }, { "Name": "Transportation" } ], "Name": "Sports Car" }, { "Instances": [], "Confidence": 56.59492111206055, "Parents": [ { "Name": "Path" } ], "Name": "Sidewalk" }, { "Instances": [], "Confidence": 56.59492111206055, "Parents": [ { "Name": "Path" } ], "Name": "Pavement" }, { "Instances": [], "Confidence": 55.58770751953125, "Parents": [ { "Name": "Building" }, { "Name": "Urban" } ], "Name": "Neighborhood" } ], "LabelModelVersion": "2.0" }有关更多信息，请参阅《Amazon Rekognition 开发人员指南》中的检测图像中的标签。
-
有关 API 的详细信息，请参阅Amazon CLI 命令参考DetectLabels
中的。
-
以下代码示例演示如何使用 detect-moderation-labels。
有关更多信息，请参阅检测不适宜的图像。
- Amazon CLI
-
检测图像中不安全的内容
以下
detect-moderation-labels命令将检测存储在 Amazon S3 存储桶中的指定图像中不安全的内容。aws rekognition detect-moderation-labels \ --image "S3Object={Bucket=MyImageS3Bucket,Name=gun.jpg}"输出：
{ "ModerationModelVersion": "3.0", "ModerationLabels": [ { "Confidence": 97.29618072509766, "ParentName": "Violence", "Name": "Weapon Violence" }, { "Confidence": 97.29618072509766, "ParentName": "", "Name": "Violence" } ] }有关更多信息，请参阅《Amazon Rekognition 开发人员指南》中的检测不安全的图像。
-
有关 API 的详细信息，请参阅Amazon CLI 命令参考DetectModerationLabels
中的。
-
以下代码示例演示如何使用 detect-text。
有关更多信息，请参阅检测图像中的文本。
- Amazon CLI
-
检测图像中的文本
以下
detect-text命令将检测指定图像中的文本。aws rekognition detect-text \ --image '{"S3Object":{"Bucket":"MyImageS3Bucket","Name":"ExamplePicture.jpg"}}'输出：
{ "TextDetections": [ { "Geometry": { "BoundingBox": { "Width": 0.24624845385551453, "Top": 0.28288066387176514, "Left": 0.391388863325119, "Height": 0.022687450051307678 }, "Polygon": [ { "Y": 0.28288066387176514, "X": 0.391388863325119 }, { "Y": 0.2826388478279114, "X": 0.6376373171806335 }, { "Y": 0.30532628297805786, "X": 0.637677013874054 }, { "Y": 0.305568128824234, "X": 0.39142853021621704 } ] }, "Confidence": 94.35709381103516, "DetectedText": "ESTD 1882", "Type": "LINE", "Id": 0 }, { "Geometry": { "BoundingBox": { "Width": 0.33933889865875244, "Top": 0.32603850960731506, "Left": 0.34534579515457153, "Height": 0.07126858830451965 }, "Polygon": [ { "Y": 0.32603850960731506, "X": 0.34534579515457153 }, { "Y": 0.32633158564567566, "X": 0.684684693813324 }, { "Y": 0.3976001739501953, "X": 0.684575080871582 }, { "Y": 0.3973070979118347, "X": 0.345236212015152 } ] }, "Confidence": 99.95779418945312, "DetectedText": "BRAINS", "Type": "LINE", "Id": 1 }, { "Confidence": 97.22098541259766, "Geometry": { "BoundingBox": { "Width": 0.061079490929841995, "Top": 0.2843210697174072, "Left": 0.391391396522522, "Height": 0.021029088646173477 }, "Polygon": [ { "Y": 0.2843210697174072, "X": 0.391391396522522 }, { "Y": 0.2828207015991211, "X": 0.4524524509906769 }, { "Y": 0.3038259446620941, "X": 0.4534534513950348 }, { "Y": 0.30532634258270264, "X": 0.3923923969268799 } ] }, "DetectedText": "ESTD", "ParentId": 0, "Type": "WORD", "Id": 2 }, { "Confidence": 91.49320983886719, "Geometry": { "BoundingBox": { "Width": 0.07007007300853729, "Top": 0.2828207015991211, "Left": 0.5675675868988037, "Height": 0.02250562608242035 }, "Polygon": [ { "Y": 0.2828207015991211, "X": 0.5675675868988037 }, { "Y": 0.2828207015991211, "X": 0.6376376152038574 }, { "Y": 0.30532634258270264, "X": 0.6376376152038574 }, { "Y": 0.30532634258270264, "X": 0.5675675868988037 } ] }, "DetectedText": "1882", "ParentId": 0, "Type": "WORD", "Id": 3 }, { "Confidence": 99.95779418945312, "Geometry": { "BoundingBox": { "Width": 0.33933934569358826, "Top": 0.32633158564567566, "Left": 0.3453453481197357, "Height": 0.07127484679222107 }, "Polygon": [ { "Y": 0.32633158564567566, "X": 0.3453453481197357 }, { "Y": 0.32633158564567566, "X": 0.684684693813324 }, { "Y": 0.39759939908981323, "X": 0.6836836934089661 }, { "Y": 0.39684921503067017, "X": 0.3453453481197357 } ] }, "DetectedText": "BRAINS", "ParentId": 1, "Type": "WORD", "Id": 4 } ] }-
有关 API 的详细信息，请参阅Amazon CLI 命令参考DetectText
中的。
-
以下代码示例演示如何使用 disassociate-faces。
- Amazon CLI
-
aws rekognition disassociate-faces --face-ids list-of-face-ids --user-id user-id --collection-id collection-name --region region-name-
有关 API 的详细信息，请参阅Amazon CLI 命令参考DisassociateFaces
中的。
-
以下代码示例演示如何使用 get-celebrity-info。
- Amazon CLI
-
获取有关名人的信息
以下
get-celebrity-info命令显示有关指定名人的信息：id参数来自先前对recognize-celebrities的调用。aws rekognition get-celebrity-info --id nnnnnnn输出：
{ "Name": "Celeb A", "Urls": [ "www.imdb.com/name/aaaaaaaaa" ] }有关更多信息，请参阅《Amazon Rekognition 开发人员指南》中的获取有关名人的信息。
-
有关 API 的详细信息，请参阅Amazon CLI 命令参考GetCelebrityInfo
中的。
-
以下代码示例演示如何使用 get-celebrity-recognition。
- Amazon CLI
-
为了获得名人认可操作的结果
以下
get-celebrity-recognition命令显示您之前通过调用start-celebrity-recognition启动的名人识别操作的结果。aws rekognition get-celebrity-recognition \ --job-id 1234567890abcdef1234567890abcdef1234567890abcdef1234567890abcdef输出：
{ "NextToken": "3D01ClxlCiT31VsRDkAO3IybLb/h5AtDWSGuhYi+N1FIJwwPtAkuKzDhL2rV3GcwmNt77+12", "Celebrities": [ { "Timestamp": 0, "Celebrity": { "Confidence": 96.0, "Face": { "BoundingBox": { "Width": 0.70333331823349, "Top": 0.16750000417232513, "Left": 0.19555555284023285, "Height": 0.3956249952316284 }, "Landmarks": [ { "Y": 0.31031012535095215, "X": 0.441436767578125, "Type": "eyeLeft" }, { "Y": 0.3081788718700409, "X": 0.6437258720397949, "Type": "eyeRight" }, { "Y": 0.39542075991630554, "X": 0.5572493076324463, "Type": "nose" }, { "Y": 0.4597957134246826, "X": 0.4579732120037079, "Type": "mouthLeft" }, { "Y": 0.45688048005104065, "X": 0.6349081993103027, "Type": "mouthRight" } ], "Pose": { "Yaw": 8.943398475646973, "Roll": -2.0309247970581055, "Pitch": -0.5674862861633301 }, "Quality": { "Sharpness": 99.40211486816406, "Brightness": 89.47132110595703 }, "Confidence": 99.99861145019531 }, "Name": "CelebrityA", "Urls": [ "www.imdb.com/name/111111111" ], "Id": "nnnnnn" } }, { "Timestamp": 467, "Celebrity": { "Confidence": 99.0, "Face": { "BoundingBox": { "Width": 0.6877777576446533, "Top": 0.18437500298023224, "Left": 0.20555555820465088, "Height": 0.3868750035762787 }, "Landmarks": [ { "Y": 0.31895750761032104, "X": 0.4411413371562958, "Type": "eyeLeft" }, { "Y": 0.3140959143638611, "X": 0.6523157954216003, "Type": "eyeRight" }, { "Y": 0.4016456604003906, "X": 0.5682755708694458, "Type": "nose" }, { "Y": 0.46894142031669617, "X": 0.4597797095775604, "Type": "mouthLeft" }, { "Y": 0.46971091628074646, "X": 0.6286435127258301, "Type": "mouthRight" } ], "Pose": { "Yaw": 10.433465957641602, "Roll": -3.347442388534546, "Pitch": 1.3709543943405151 }, "Quality": { "Sharpness": 99.5531005859375, "Brightness": 88.5764389038086 }, "Confidence": 99.99148559570312 }, "Name": "Jane Celebrity", "Urls": [ "www.imdb.com/name/111111111" ], "Id": "nnnnnn" } } ], "JobStatus": "SUCCEEDED", "VideoMetadata": { "Format": "QuickTime / MOV", "FrameRate": 29.978118896484375, "Codec": "h264", "DurationMillis": 4570, "FrameHeight": 1920, "FrameWidth": 1080 } }有关更多信息，请参阅亚马逊 Rekognition 开发者指南中的识别存储视频中的名人。
-
有关 API 的详细信息，请参阅Amazon CLI 命令参考GetCelebrityRecognition
中的。
-
以下代码示例演示如何使用 get-content-moderation。
- Amazon CLI
-
获取不安全内容操作的结果
以下
get-content-moderation命令显示您之前通过调用启动的不安全内容操作的结果start-content-moderation。aws rekognition get-content-moderation \ --job-id 1234567890abcdef1234567890abcdef1234567890abcdef1234567890abcdef输出：
{ "NextToken": "dlhcKMHMzpCBGFukz6IO3JMcWiJAamCVhXHt3r6b4b5Tfbyw3q7o+Jeezt+ZpgfOnW9FCCgQ", "ModerationLabels": [ { "Timestamp": 0, "ModerationLabel": { "Confidence": 97.39583587646484, "ParentName": "", "Name": "Violence" } }, { "Timestamp": 0, "ModerationLabel": { "Confidence": 97.39583587646484, "ParentName": "Violence", "Name": "Weapon Violence" } } ], "JobStatus": "SUCCEEDED", "VideoMetadata": { "Format": "QuickTime / MOV", "FrameRate": 29.97515869140625, "Codec": "h264", "DurationMillis": 6039, "FrameHeight": 1920, "FrameWidth": 1080 } }有关更多信息，请参阅《亚马逊 Rek ognition 开发者指南》中的 “检测存储的不安全视频”。
-
有关 API 的详细信息，请参阅Amazon CLI 命令参考GetContentModeration
中的。
-
以下代码示例演示如何使用 get-face-detection。
- Amazon CLI
-
获取人脸检测操作的结果
以下
get-face-detection命令显示您之前通过调用启动的人脸检测操作的结果start-face-detection。aws rekognition get-face-detection \ --job-id 1234567890abcdef1234567890abcdef1234567890abcdef1234567890abcdef输出：
{ "Faces": [ { "Timestamp": 467, "Face": { "BoundingBox": { "Width": 0.1560753583908081, "Top": 0.13555361330509186, "Left": -0.0952017530798912, "Height": 0.6934483051300049 }, "Landmarks": [ { "Y": 0.4013825058937073, "X": -0.041750285774469376, "Type": "eyeLeft" }, { "Y": 0.41695496439933777, "X": 0.027979329228401184, "Type": "eyeRight" }, { "Y": 0.6375303268432617, "X": -0.04034662991762161, "Type": "mouthLeft" }, { "Y": 0.6497718691825867, "X": 0.013960429467260838, "Type": "mouthRight" }, { "Y": 0.5238034129142761, "X": 0.008022055961191654, "Type": "nose" } ], "Pose": { "Yaw": -58.07863998413086, "Roll": 1.9384294748306274, "Pitch": -24.66305160522461 }, "Quality": { "Sharpness": 83.14741516113281, "Brightness": 25.75942611694336 }, "Confidence": 87.7622299194336 } }, { "Timestamp": 967, "Face": { "BoundingBox": { "Width": 0.28559377789497375, "Top": 0.19436298310756683, "Left": 0.024553587660193443, "Height": 0.7216082215309143 }, "Landmarks": [ { "Y": 0.4650231599807739, "X": 0.16269078850746155, "Type": "eyeLeft" }, { "Y": 0.4843238294124603, "X": 0.2782580852508545, "Type": "eyeRight" }, { "Y": 0.71530681848526, "X": 0.1741468608379364, "Type": "mouthLeft" }, { "Y": 0.7310671210289001, "X": 0.26857468485832214, "Type": "mouthRight" }, { "Y": 0.582602322101593, "X": 0.2566150426864624, "Type": "nose" } ], "Pose": { "Yaw": 11.487052917480469, "Roll": 5.074230670928955, "Pitch": 15.396159172058105 }, "Quality": { "Sharpness": 73.32209777832031, "Brightness": 54.96497344970703 }, "Confidence": 99.99998474121094 } } ], "NextToken": "OzL223pDKy9116O/02KXRqFIEAwxjy4PkgYcm3hSo0rdysbXg5Ex0eFgTGEj0ADEac6S037U", "JobStatus": "SUCCEEDED", "VideoMetadata": { "Format": "QuickTime / MOV", "FrameRate": 29.970617294311523, "Codec": "h264", "DurationMillis": 6806, "FrameHeight": 1080, "FrameWidth": 1920 } }有关更多信息，请参阅亚马逊 Rek ognit ion 开发者指南中的检测存储视频中的人脸。
-
有关 API 的详细信息，请参阅Amazon CLI 命令参考GetFaceDetection
中的。
-
以下代码示例演示如何使用 get-face-search。
- Amazon CLI
-
获取人脸搜索操作的结果
以下
get-face-search命令显示您之前通过调用启动的人脸搜索操作的结果start-face-search。aws rekognition get-face-search \ --job-id 1234567890abcdef1234567890abcdef1234567890abcdef1234567890abcdef输出：
{ "Persons": [ { "Timestamp": 467, "FaceMatches": [], "Person": { "Index": 0, "Face": { "BoundingBox": { "Width": 0.1560753583908081, "Top": 0.13555361330509186, "Left": -0.0952017530798912, "Height": 0.6934483051300049 }, "Landmarks": [ { "Y": 0.4013825058937073, "X": -0.041750285774469376, "Type": "eyeLeft" }, { "Y": 0.41695496439933777, "X": 0.027979329228401184, "Type": "eyeRight" }, { "Y": 0.6375303268432617, "X": -0.04034662991762161, "Type": "mouthLeft" }, { "Y": 0.6497718691825867, "X": 0.013960429467260838, "Type": "mouthRight" }, { "Y": 0.5238034129142761, "X": 0.008022055961191654, "Type": "nose" } ], "Pose": { "Yaw": -58.07863998413086, "Roll": 1.9384294748306274, "Pitch": -24.66305160522461 }, "Quality": { "Sharpness": 83.14741516113281, "Brightness": 25.75942611694336 }, "Confidence": 87.7622299194336 } } }, { "Timestamp": 967, "FaceMatches": [ { "Face": { "BoundingBox": { "Width": 0.12368900328874588, "Top": 0.16007399559020996, "Left": 0.5901259779930115, "Height": 0.2514039874076843 }, "FaceId": "056a95fa-2060-4159-9cab-7ed4daa030fa", "ExternalImageId": "image3.jpg", "Confidence": 100.0, "ImageId": "08f8a078-8929-37fd-8e8f-aadf690e8232" }, "Similarity": 98.44476318359375 } ], "Person": { "Index": 1, "Face": { "BoundingBox": { "Width": 0.28559377789497375, "Top": 0.19436298310756683, "Left": 0.024553587660193443, "Height": 0.7216082215309143 }, "Landmarks": [ { "Y": 0.4650231599807739, "X": 0.16269078850746155, "Type": "eyeLeft" }, { "Y": 0.4843238294124603, "X": 0.2782580852508545, "Type": "eyeRight" }, { "Y": 0.71530681848526, "X": 0.1741468608379364, "Type": "mouthLeft" }, { "Y": 0.7310671210289001, "X": 0.26857468485832214, "Type": "mouthRight" }, { "Y": 0.582602322101593, "X": 0.2566150426864624, "Type": "nose" } ], "Pose": { "Yaw": 11.487052917480469, "Roll": 5.074230670928955, "Pitch": 15.396159172058105 }, "Quality": { "Sharpness": 73.32209777832031, "Brightness": 54.96497344970703 }, "Confidence": 99.99998474121094 } } } ], "NextToken": "5bkgcezyuaqhtWk3C8OTW6cjRghrwV9XDMivm5B3MXm+Lv6G+L+GejyFHPhoNa/ldXIC4c/d", "JobStatus": "SUCCEEDED", "VideoMetadata": { "Format": "QuickTime / MOV", "FrameRate": 29.970617294311523, "Codec": "h264", "DurationMillis": 6806, "FrameHeight": 1080, "FrameWidth": 1920 } }有关更多信息，请参阅亚马逊 Rek ognition 开发者指南中的在存储的视频中搜索人脸。
-
有关 API 的详细信息，请参阅Amazon CLI 命令参考GetFaceSearch
中的。
-
以下代码示例演示如何使用 get-label-detection。
- Amazon CLI
-
获取物体和场景检测操作的结果
以下
get-label-detection命令显示您之前通过调用启动的对象和场景检测操作的结果start-label-detection。aws rekognition get-label-detection \ --job-id 1234567890abcdef1234567890abcdef1234567890abcdef1234567890abcdef输出：
{ "Labels": [ { "Timestamp": 0, "Label": { "Instances": [], "Confidence": 50.19071578979492, "Parents": [ { "Name": "Person" }, { "Name": "Crowd" } ], "Name": "Audience" } }, { "Timestamp": 0, "Label": { "Instances": [], "Confidence": 55.74115753173828, "Parents": [ { "Name": "Room" }, { "Name": "Indoors" }, { "Name": "School" } ], "Name": "Classroom" } } ], "JobStatus": "SUCCEEDED", "LabelModelVersion": "2.0", "VideoMetadata": { "Format": "QuickTime / MOV", "FrameRate": 29.970617294311523, "Codec": "h264", "DurationMillis": 6806, "FrameHeight": 1080, "FrameWidth": 1920 }, "NextToken": "BMugzAi4L72IERzQdbpyMQuEFBsjlo5W0Yx3mfG+sR9mm98E1/CpObenspRfs/5FBQFs4X7G" }有关更多信息，请参阅亚马逊 Rekognition 开发者指南中的检测视频中的标签。
-
有关 API 的详细信息，请参阅Amazon CLI 命令参考GetLabelDetection
中的。
-
以下代码示例演示如何使用 get-person-tracking。
- Amazon CLI
-
获取人员路径分析操作的结果
以下
get-person-tracking命令显示您之前通过调用start-person-tracking启动的人员路径分析操作的结果。aws rekognition get-person-tracking \ --job-id 1234567890abcdef1234567890abcdef1234567890abcdef1234567890abcdef输出：
{ "Persons": [ { "Timestamp": 500, "Person": { "BoundingBox": { "Width": 0.4151041805744171, "Top": 0.07870370149612427, "Left": 0.0, "Height": 0.9212962985038757 }, "Index": 0 } }, { "Timestamp": 567, "Person": { "BoundingBox": { "Width": 0.4755208194255829, "Top": 0.07777778059244156, "Left": 0.0, "Height": 0.9194444417953491 }, "Index": 0 } } ], "NextToken": "D/vRIYNyhG79ugdta3f+8cRg9oSRo+HigGOuxRiYpTn0ExnqTi1CJektVAc4HrAXDv25eHYk", "JobStatus": "SUCCEEDED", "VideoMetadata": { "Format": "QuickTime / MOV", "FrameRate": 29.970617294311523, "Codec": "h264", "DurationMillis": 6806, "FrameHeight": 1080, "FrameWidth": 1920 } }有关更多信息，请参阅亚马逊 Rekognition 开发者指南中的人员路径。
-
有关 API 的详细信息，请参阅Amazon CLI 命令参考GetPersonTracking
中的。
-
以下代码示例演示如何使用 index-faces。
有关更多信息，请参阅将人脸添加到集合中。
- Amazon CLI
-
将人脸添加到集合
以下
index-faces命令将在图像中找到的人脸添加到指定的集合中。aws rekognition index-faces \ --image '{"S3Object":{"Bucket":"MyVideoS3Bucket","Name":"MyPicture.jpg"}}' \ --collection-id MyCollection \ --max-faces 1 \ --quality-filter "AUTO" \ --detection-attributes "ALL" \ --external-image-id "MyPicture.jpg"输出：
{ "FaceRecords": [ { "FaceDetail": { "Confidence": 99.993408203125, "Eyeglasses": { "Confidence": 99.11750030517578, "Value": false }, "Sunglasses": { "Confidence": 99.98249053955078, "Value": false }, "Gender": { "Confidence": 99.92769622802734, "Value": "Male" }, "Landmarks": [ { "Y": 0.26750367879867554, "X": 0.6202793717384338, "Type": "eyeLeft" }, { "Y": 0.26642778515815735, "X": 0.6787431836128235, "Type": "eyeRight" }, { "Y": 0.31361380219459534, "X": 0.6421601176261902, "Type": "nose" }, { "Y": 0.3495299220085144, "X": 0.6216195225715637, "Type": "mouthLeft" }, { "Y": 0.35194727778434753, "X": 0.669899046421051, "Type": "mouthRight" }, { "Y": 0.26844894886016846, "X": 0.6210268139839172, "Type": "leftPupil" }, { "Y": 0.26707562804222107, "X": 0.6817160844802856, "Type": "rightPupil" }, { "Y": 0.24834522604942322, "X": 0.6018546223640442, "Type": "leftEyeBrowLeft" }, { "Y": 0.24397172033786774, "X": 0.6172008514404297, "Type": "leftEyeBrowUp" }, { "Y": 0.24677404761314392, "X": 0.6339119076728821, "Type": "leftEyeBrowRight" }, { "Y": 0.24582654237747192, "X": 0.6619398593902588, "Type": "rightEyeBrowLeft" }, { "Y": 0.23973053693771362, "X": 0.6804757118225098, "Type": "rightEyeBrowUp" }, { "Y": 0.24441994726657867, "X": 0.6978968977928162, "Type": "rightEyeBrowRight" }, { "Y": 0.2695908546447754, "X": 0.6085202693939209, "Type": "leftEyeLeft" }, { "Y": 0.26716896891593933, "X": 0.6315826177597046, "Type": "leftEyeRight" }, { "Y": 0.26289820671081543, "X": 0.6202316880226135, "Type": "leftEyeUp" }, { "Y": 0.27123287320137024, "X": 0.6205548048019409, "Type": "leftEyeDown" }, { "Y": 0.2668408751487732, "X": 0.6663622260093689, "Type": "rightEyeLeft" }, { "Y": 0.26741549372673035, "X": 0.6910083889961243, "Type": "rightEyeRight" }, { "Y": 0.2614026665687561, "X": 0.6785826086997986, "Type": "rightEyeUp" }, { "Y": 0.27075251936912537, "X": 0.6789616942405701, "Type": "rightEyeDown" }, { "Y": 0.3211299479007721, "X": 0.6324167847633362, "Type": "noseLeft" }, { "Y": 0.32276326417922974, "X": 0.6558475494384766, "Type": "noseRight" }, { "Y": 0.34385165572166443, "X": 0.6444970965385437, "Type": "mouthUp" }, { "Y": 0.3671635091304779, "X": 0.6459195017814636, "Type": "mouthDown" } ], "Pose": { "Yaw": -9.54541015625, "Roll": -0.5709401965141296, "Pitch": 0.6045494675636292 }, "Emotions": [ { "Confidence": 39.90074157714844, "Type": "HAPPY" }, { "Confidence": 23.38753890991211, "Type": "CALM" }, { "Confidence": 5.840933322906494, "Type": "CONFUSED" } ], "AgeRange": { "High": 63, "Low": 45 }, "EyesOpen": { "Confidence": 99.80887603759766, "Value": true }, "BoundingBox": { "Width": 0.18562500178813934, "Top": 0.1618015021085739, "Left": 0.5575000047683716, "Height": 0.24770642817020416 }, "Smile": { "Confidence": 99.69740295410156, "Value": false }, "MouthOpen": { "Confidence": 99.97393798828125, "Value": false }, "Quality": { "Sharpness": 95.54405975341797, "Brightness": 63.867706298828125 }, "Mustache": { "Confidence": 97.05007934570312, "Value": false }, "Beard": { "Confidence": 87.34505462646484, "Value": false } }, "Face": { "BoundingBox": { "Width": 0.18562500178813934, "Top": 0.1618015021085739, "Left": 0.5575000047683716, "Height": 0.24770642817020416 }, "FaceId": "ce7ed422-2132-4a11-ab14-06c5c410f29f", "ExternalImageId": "example-image.jpg", "Confidence": 99.993408203125, "ImageId": "8d67061e-90d2-598f-9fbd-29c8497039c0" } } ], "UnindexedFaces": [], "FaceModelVersion": "3.0", "OrientationCorrection": "ROTATE_0" }有关更多信息，请参阅《Amazon Rekognition 开发人员指南》中的将人脸添加到集合中。
-
有关 API 的详细信息，请参阅Amazon CLI 命令参考IndexFaces
中的。
-
以下代码示例演示如何使用 list-collections。
有关更多信息，请参阅列出集合。
- Amazon CLI
-
列出可用的集合
以下
list-collections命令列出了 Amazon 账户中的可用集合。aws rekognition list-collections输出：
{ "FaceModelVersions": [ "2.0", "3.0", "3.0", "3.0", "4.0", "1.0", "3.0", "4.0", "4.0", "4.0" ], "CollectionIds": [ "MyCollection1", "MyCollection2", "MyCollection3", "MyCollection4", "MyCollection5", "MyCollection6", "MyCollection7", "MyCollection8", "MyCollection9", "MyCollection10" ] }有关更多信息，请参阅《Amazon Rekognition 开发人员指南》中的列出集合。
-
有关 API 的详细信息，请参阅Amazon CLI 命令参考ListCollections
中的。
-
以下代码示例演示如何使用 list-faces。
有关更多信息，请参阅列出集合中的人脸。
- Amazon CLI
-
列出集合中的人脸
以下
list-faces命令将列出指定集合中的人脸。aws rekognition list-faces \ --collection-id MyCollection输出：
{ "FaceModelVersion": "3.0", "Faces": [ { "BoundingBox": { "Width": 0.5216310024261475, "Top": 0.3256250023841858, "Left": 0.13394300639629364, "Height": 0.3918749988079071 }, "FaceId": "0040279c-0178-436e-b70a-e61b074e96b0", "ExternalImageId": "image1.jpg", "Confidence": 100.0, "ImageId": "f976e487-3719-5e2d-be8b-ea2724c26991" }, { "BoundingBox": { "Width": 0.5074880123138428, "Top": 0.3774999976158142, "Left": 0.18302799761295319, "Height": 0.3812499940395355 }, "FaceId": "086261e8-6deb-4bc0-ac73-ab22323cc38d", "ExternalImageId": "image2.jpg", "Confidence": 99.99930572509766, "ImageId": "ae1593b0-a8f6-5e24-a306-abf529e276fa" }, { "BoundingBox": { "Width": 0.5574039816856384, "Top": 0.37187498807907104, "Left": 0.14559100568294525, "Height": 0.4181250035762787 }, "FaceId": "11c4bd3c-19c5-4eb8-aecc-24feb93a26e1", "ExternalImageId": "image3.jpg", "Confidence": 99.99960327148438, "ImageId": "80739b4d-883f-5b78-97cf-5124038e26b9" }, { "BoundingBox": { "Width": 0.18562500178813934, "Top": 0.1618019938468933, "Left": 0.5575000047683716, "Height": 0.24770599603652954 }, "FaceId": "13692fe4-990a-4679-b14a-5ac23d135eab", "ExternalImageId": "image4.jpg", "Confidence": 99.99340057373047, "ImageId": "8df18239-9ad1-5acd-a46a-6581ff98f51b" }, { "BoundingBox": { "Width": 0.5307819843292236, "Top": 0.2862499952316284, "Left": 0.1564060002565384, "Height": 0.3987500071525574 }, "FaceId": "2eb5f3fd-e2a9-4b1c-a89f-afa0a518fe06", "ExternalImageId": "image5.jpg", "Confidence": 99.99970245361328, "ImageId": "3c314792-197d-528d-bbb6-798ed012c150" }, { "BoundingBox": { "Width": 0.5773710012435913, "Top": 0.34437501430511475, "Left": 0.12396000325679779, "Height": 0.4337500035762787 }, "FaceId": "57189455-42b0-4839-a86c-abda48b13174", "ExternalImageId": "image6.jpg", "Confidence": 100.0, "ImageId": "0aff2f37-e7a2-5dbc-a3a3-4ef6ec18eaa0" }, { "BoundingBox": { "Width": 0.5349419713020325, "Top": 0.29124999046325684, "Left": 0.16389399766921997, "Height": 0.40187498927116394 }, "FaceId": "745f7509-b1fa-44e0-8b95-367b1359638a", "ExternalImageId": "image7.jpg", "Confidence": 99.99979400634766, "ImageId": "67a34327-48d1-5179-b042-01e52ccfeada" }, { "BoundingBox": { "Width": 0.41499999165534973, "Top": 0.09187500178813934, "Left": 0.28083300590515137, "Height": 0.3112500011920929 }, "FaceId": "8d3cfc70-4ba8-4b36-9644-90fba29c2dac", "ExternalImageId": "image8.jpg", "Confidence": 99.99769592285156, "ImageId": "a294da46-2cb1-5cc4-9045-61d7ca567662" }, { "BoundingBox": { "Width": 0.48166701197624207, "Top": 0.20999999344348907, "Left": 0.21250000596046448, "Height": 0.36125001311302185 }, "FaceId": "bd4ceb4d-9acc-4ab7-8ef8-1c2d2ba0a66a", "ExternalImageId": "image9.jpg", "Confidence": 99.99949645996094, "ImageId": "5e1a7588-e5a0-5ee3-bd00-c642518dfe3a" }, { "BoundingBox": { "Width": 0.18562500178813934, "Top": 0.1618019938468933, "Left": 0.5575000047683716, "Height": 0.24770599603652954 }, "FaceId": "ce7ed422-2132-4a11-ab14-06c5c410f29f", "ExternalImageId": "image10.jpg", "Confidence": 99.99340057373047, "ImageId": "8d67061e-90d2-598f-9fbd-29c8497039c0" } ] }有关更多信息，请参阅《Amazon Rekognition 开发人员指南》中的列出集合中的人脸。
-
有关 API 的详细信息，请参阅Amazon CLI 命令参考ListFaces
中的。
-
以下代码示例演示如何使用 list-stream-processors。
- Amazon CLI
-
列出您账户中的流媒体处理器
以下
list-stream-processors命令列出了您账户中的流处理器以及每个流处理器的状态。aws rekognition list-stream-processors输出：
{ "StreamProcessors": [ { "Status": "STOPPED", "Name": "my-stream-processor" } ] }有关更多信息，请参阅亚马逊 Rekognition 开发者指南中的使用流媒体视频。
-
有关 API 的详细信息，请参阅Amazon CLI 命令参考ListStreamProcessors
中的。
-
以下代码示例演示如何使用 recognize-celebrities。
有关更多信息，请参阅识别图像中的名人。
- Amazon CLI
-
识别图像中的名人
以下
recognize-celebrities命令将识别存储在 Amazon S3 存储桶中的指定图像中的名人。aws rekognition recognize-celebrities \ --image "S3Object={Bucket=MyImageS3Bucket,Name=moviestars.jpg}"输出：
{ "UnrecognizedFaces": [ { "BoundingBox": { "Width": 0.14416666328907013, "Top": 0.07777778059244156, "Left": 0.625, "Height": 0.2746031880378723 }, "Confidence": 99.9990234375, "Pose": { "Yaw": 10.80408763885498, "Roll": -12.761146545410156, "Pitch": 10.96889877319336 }, "Quality": { "Sharpness": 94.1185531616211, "Brightness": 79.18367004394531 }, "Landmarks": [ { "Y": 0.18220913410186768, "X": 0.6702951788902283, "Type": "eyeLeft" }, { "Y": 0.16337193548679352, "X": 0.7188183665275574, "Type": "eyeRight" }, { "Y": 0.20739148557186127, "X": 0.7055801749229431, "Type": "nose" }, { "Y": 0.2889308035373688, "X": 0.687512218952179, "Type": "mouthLeft" }, { "Y": 0.2706988751888275, "X": 0.7250053286552429, "Type": "mouthRight" } ] } ], "CelebrityFaces": [ { "MatchConfidence": 100.0, "Face": { "BoundingBox": { "Width": 0.14000000059604645, "Top": 0.1190476194024086, "Left": 0.82833331823349, "Height": 0.2666666805744171 }, "Confidence": 99.99359130859375, "Pose": { "Yaw": -10.509642601013184, "Roll": -14.51749324798584, "Pitch": 13.799399375915527 }, "Quality": { "Sharpness": 78.74752044677734, "Brightness": 42.201324462890625 }, "Landmarks": [ { "Y": 0.2290833294391632, "X": 0.8709492087364197, "Type": "eyeLeft" }, { "Y": 0.20639978349208832, "X": 0.9153988361358643, "Type": "eyeRight" }, { "Y": 0.25417643785476685, "X": 0.8907724022865295, "Type": "nose" }, { "Y": 0.32729196548461914, "X": 0.8876466155052185, "Type": "mouthLeft" }, { "Y": 0.3115464746952057, "X": 0.9238573312759399, "Type": "mouthRight" } ] }, "Name": "Celeb A", "Urls": [ "www.imdb.com/name/aaaaaaaaa" ], "Id": "1111111" }, { "MatchConfidence": 97.0, "Face": { "BoundingBox": { "Width": 0.13333334028720856, "Top": 0.24920634925365448, "Left": 0.4449999928474426, "Height": 0.2539682686328888 }, "Confidence": 99.99979400634766, "Pose": { "Yaw": 6.557040691375732, "Roll": -7.316643714904785, "Pitch": 9.272967338562012 }, "Quality": { "Sharpness": 83.23492431640625, "Brightness": 78.83267974853516 }, "Landmarks": [ { "Y": 0.3625510632991791, "X": 0.48898839950561523, "Type": "eyeLeft" }, { "Y": 0.35366007685661316, "X": 0.5313721299171448, "Type": "eyeRight" }, { "Y": 0.3894785940647125, "X": 0.5173314809799194, "Type": "nose" }, { "Y": 0.44889405369758606, "X": 0.5020005702972412, "Type": "mouthLeft" }, { "Y": 0.4408611059188843, "X": 0.5351271629333496, "Type": "mouthRight" } ] }, "Name": "Celeb B", "Urls": [ "www.imdb.com/name/bbbbbbbbb" ], "Id": "2222222" }, { "MatchConfidence": 100.0, "Face": { "BoundingBox": { "Width": 0.12416666746139526, "Top": 0.2968254089355469, "Left": 0.2150000035762787, "Height": 0.23650793731212616 }, "Confidence": 99.99958801269531, "Pose": { "Yaw": 7.801797866821289, "Roll": -8.326810836791992, "Pitch": 7.844768047332764 }, "Quality": { "Sharpness": 86.93206024169922, "Brightness": 79.81291198730469 }, "Landmarks": [ { "Y": 0.4027804136276245, "X": 0.2575301229953766, "Type": "eyeLeft" }, { "Y": 0.3934555947780609, "X": 0.2956969439983368, "Type": "eyeRight" }, { "Y": 0.4309830069541931, "X": 0.2837020754814148, "Type": "nose" }, { "Y": 0.48186683654785156, "X": 0.26812544465065, "Type": "mouthLeft" }, { "Y": 0.47338807582855225, "X": 0.29905644059181213, "Type": "mouthRight" } ] }, "Name": "Celeb C", "Urls": [ "www.imdb.com/name/ccccccccc" ], "Id": "3333333" }, { "MatchConfidence": 97.0, "Face": { "BoundingBox": { "Width": 0.11916666477918625, "Top": 0.3698412775993347, "Left": 0.008333333767950535, "Height": 0.22698412835597992 }, "Confidence": 99.99999237060547, "Pose": { "Yaw": 16.38478660583496, "Roll": -1.0260354280471802, "Pitch": 5.975185394287109 }, "Quality": { "Sharpness": 83.23492431640625, "Brightness": 61.408443450927734 }, "Landmarks": [ { "Y": 0.4632347822189331, "X": 0.049406956881284714, "Type": "eyeLeft" }, { "Y": 0.46388113498687744, "X": 0.08722897619009018, "Type": "eyeRight" }, { "Y": 0.5020678639411926, "X": 0.0758260041475296, "Type": "nose" }, { "Y": 0.544157862663269, "X": 0.054029736667871475, "Type": "mouthLeft" }, { "Y": 0.5463630557060242, "X": 0.08464983850717545, "Type": "mouthRight" } ] }, "Name": "Celeb D", "Urls": [ "www.imdb.com/name/ddddddddd" ], "Id": "4444444" } ] }有关更多信息，请参阅《Amazon Rekognition 开发人员指南》中的识别图像中的名人。
-
有关 API 的详细信息，请参阅Amazon CLI 命令参考RecognizeCelebrities
中的。
-
以下代码示例演示如何使用 search-faces-by-image。
有关更多信息，请参阅搜索人脸（图像）。
- Amazon CLI
-
搜索集合中与图像中最大人脸匹配的人脸。
以下
search-faces-by-image命令将搜索集合中与指定图像中最大人脸相匹配的人脸。aws rekognition search-faces-by-image \ --image '{"S3Object":{"Bucket":"MyImageS3Bucket","Name":"ExamplePerson.jpg"}}' \ --collection-id MyFaceImageCollection { "SearchedFaceBoundingBox": { "Width": 0.18562500178813934, "Top": 0.1618015021085739, "Left": 0.5575000047683716, "Height": 0.24770642817020416 }, "SearchedFaceConfidence": 99.993408203125, "FaceMatches": [ { "Face": { "BoundingBox": { "Width": 0.18562500178813934, "Top": 0.1618019938468933, "Left": 0.5575000047683716, "Height": 0.24770599603652954 }, "FaceId": "ce7ed422-2132-4a11-ab14-06c5c410f29f", "ExternalImageId": "example-image.jpg", "Confidence": 99.99340057373047, "ImageId": "8d67061e-90d2-598f-9fbd-29c8497039c0" }, "Similarity": 99.97913360595703 }, { "Face": { "BoundingBox": { "Width": 0.18562500178813934, "Top": 0.1618019938468933, "Left": 0.5575000047683716, "Height": 0.24770599603652954 }, "FaceId": "13692fe4-990a-4679-b14a-5ac23d135eab", "ExternalImageId": "image3.jpg", "Confidence": 99.99340057373047, "ImageId": "8df18239-9ad1-5acd-a46a-6581ff98f51b" }, "Similarity": 99.97913360595703 }, { "Face": { "BoundingBox": { "Width": 0.41499999165534973, "Top": 0.09187500178813934, "Left": 0.28083300590515137, "Height": 0.3112500011920929 }, "FaceId": "8d3cfc70-4ba8-4b36-9644-90fba29c2dac", "ExternalImageId": "image2.jpg", "Confidence": 99.99769592285156, "ImageId": "a294da46-2cb1-5cc4-9045-61d7ca567662" }, "Similarity": 99.18069458007812 }, { "Face": { "BoundingBox": { "Width": 0.48166701197624207, "Top": 0.20999999344348907, "Left": 0.21250000596046448, "Height": 0.36125001311302185 }, "FaceId": "bd4ceb4d-9acc-4ab7-8ef8-1c2d2ba0a66a", "ExternalImageId": "image1.jpg", "Confidence": 99.99949645996094, "ImageId": "5e1a7588-e5a0-5ee3-bd00-c642518dfe3a" }, "Similarity": 98.66607666015625 }, { "Face": { "BoundingBox": { "Width": 0.5349419713020325, "Top": 0.29124999046325684, "Left": 0.16389399766921997, "Height": 0.40187498927116394 }, "FaceId": "745f7509-b1fa-44e0-8b95-367b1359638a", "ExternalImageId": "image9.jpg", "Confidence": 99.99979400634766, "ImageId": "67a34327-48d1-5179-b042-01e52ccfeada" }, "Similarity": 98.24278259277344 }, { "Face": { "BoundingBox": { "Width": 0.5307819843292236, "Top": 0.2862499952316284, "Left": 0.1564060002565384, "Height": 0.3987500071525574 }, "FaceId": "2eb5f3fd-e2a9-4b1c-a89f-afa0a518fe06", "ExternalImageId": "image10.jpg", "Confidence": 99.99970245361328, "ImageId": "3c314792-197d-528d-bbb6-798ed012c150" }, "Similarity": 98.10665893554688 }, { "Face": { "BoundingBox": { "Width": 0.5074880123138428, "Top": 0.3774999976158142, "Left": 0.18302799761295319, "Height": 0.3812499940395355 }, "FaceId": "086261e8-6deb-4bc0-ac73-ab22323cc38d", "ExternalImageId": "image6.jpg", "Confidence": 99.99930572509766, "ImageId": "ae1593b0-a8f6-5e24-a306-abf529e276fa" }, "Similarity": 98.10526275634766 }, { "Face": { "BoundingBox": { "Width": 0.5574039816856384, "Top": 0.37187498807907104, "Left": 0.14559100568294525, "Height": 0.4181250035762787 }, "FaceId": "11c4bd3c-19c5-4eb8-aecc-24feb93a26e1", "ExternalImageId": "image5.jpg", "Confidence": 99.99960327148438, "ImageId": "80739b4d-883f-5b78-97cf-5124038e26b9" }, "Similarity": 97.94659423828125 }, { "Face": { "BoundingBox": { "Width": 0.5773710012435913, "Top": 0.34437501430511475, "Left": 0.12396000325679779, "Height": 0.4337500035762787 }, "FaceId": "57189455-42b0-4839-a86c-abda48b13174", "ExternalImageId": "image8.jpg", "Confidence": 100.0, "ImageId": "0aff2f37-e7a2-5dbc-a3a3-4ef6ec18eaa0" }, "Similarity": 97.93476867675781 } ], "FaceModelVersion": "3.0" }有关更多信息，请参阅《Amazon Rekognition 开发人员指南》中的使用图像搜索人脸。
-
有关 API 的详细信息，请参阅Amazon CLI 命令参考SearchFacesByImage
中的。
-
以下代码示例演示如何使用 search-faces。
有关更多信息，请参阅搜索人脸（面容 ID）。
- Amazon CLI
-
搜索集合中与人脸 ID 匹配的人脸
以下
search-faces命令将搜索集合中与指定人脸 ID 相匹配的人脸。aws rekognition search-faces \ --face-id 8d3cfc70-4ba8-4b36-9644-90fba29c2dac \ --collection-id MyCollection输出：
{ "SearchedFaceId": "8d3cfc70-4ba8-4b36-9644-90fba29c2dac", "FaceModelVersion": "3.0", "FaceMatches": [ { "Face": { "BoundingBox": { "Width": 0.48166701197624207, "Top": 0.20999999344348907, "Left": 0.21250000596046448, "Height": 0.36125001311302185 }, "FaceId": "bd4ceb4d-9acc-4ab7-8ef8-1c2d2ba0a66a", "ExternalImageId": "image1.jpg", "Confidence": 99.99949645996094, "ImageId": "5e1a7588-e5a0-5ee3-bd00-c642518dfe3a" }, "Similarity": 99.30997467041016 }, { "Face": { "BoundingBox": { "Width": 0.18562500178813934, "Top": 0.1618019938468933, "Left": 0.5575000047683716, "Height": 0.24770599603652954 }, "FaceId": "ce7ed422-2132-4a11-ab14-06c5c410f29f", "ExternalImageId": "example-image.jpg", "Confidence": 99.99340057373047, "ImageId": "8d67061e-90d2-598f-9fbd-29c8497039c0" }, "Similarity": 99.24862670898438 }, { "Face": { "BoundingBox": { "Width": 0.18562500178813934, "Top": 0.1618019938468933, "Left": 0.5575000047683716, "Height": 0.24770599603652954 }, "FaceId": "13692fe4-990a-4679-b14a-5ac23d135eab", "ExternalImageId": "image3.jpg", "Confidence": 99.99340057373047, "ImageId": "8df18239-9ad1-5acd-a46a-6581ff98f51b" }, "Similarity": 99.24862670898438 }, { "Face": { "BoundingBox": { "Width": 0.5349419713020325, "Top": 0.29124999046325684, "Left": 0.16389399766921997, "Height": 0.40187498927116394 }, "FaceId": "745f7509-b1fa-44e0-8b95-367b1359638a", "ExternalImageId": "image9.jpg", "Confidence": 99.99979400634766, "ImageId": "67a34327-48d1-5179-b042-01e52ccfeada" }, "Similarity": 96.73158264160156 }, { "Face": { "BoundingBox": { "Width": 0.5307819843292236, "Top": 0.2862499952316284, "Left": 0.1564060002565384, "Height": 0.3987500071525574 }, "FaceId": "2eb5f3fd-e2a9-4b1c-a89f-afa0a518fe06", "ExternalImageId": "image10.jpg", "Confidence": 99.99970245361328, "ImageId": "3c314792-197d-528d-bbb6-798ed012c150" }, "Similarity": 96.48291015625 }, { "Face": { "BoundingBox": { "Width": 0.5074880123138428, "Top": 0.3774999976158142, "Left": 0.18302799761295319, "Height": 0.3812499940395355 }, "FaceId": "086261e8-6deb-4bc0-ac73-ab22323cc38d", "ExternalImageId": "image6.jpg", "Confidence": 99.99930572509766, "ImageId": "ae1593b0-a8f6-5e24-a306-abf529e276fa" }, "Similarity": 96.43287658691406 }, { "Face": { "BoundingBox": { "Width": 0.5574039816856384, "Top": 0.37187498807907104, "Left": 0.14559100568294525, "Height": 0.4181250035762787 }, "FaceId": "11c4bd3c-19c5-4eb8-aecc-24feb93a26e1", "ExternalImageId": "image5.jpg", "Confidence": 99.99960327148438, "ImageId": "80739b4d-883f-5b78-97cf-5124038e26b9" }, "Similarity": 95.25305938720703 }, { "Face": { "BoundingBox": { "Width": 0.5773710012435913, "Top": 0.34437501430511475, "Left": 0.12396000325679779, "Height": 0.4337500035762787 }, "FaceId": "57189455-42b0-4839-a86c-abda48b13174", "ExternalImageId": "image8.jpg", "Confidence": 100.0, "ImageId": "0aff2f37-e7a2-5dbc-a3a3-4ef6ec18eaa0" }, "Similarity": 95.22837829589844 } ] }有关更多信息，请参阅《Amazon Rekognition 开发人员指南》中的使用人脸 ID 搜索人脸。
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有关 API 的详细信息，请参阅Amazon CLI 命令参考SearchFaces
中的。
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以下代码示例演示如何使用 start-celebrity-recognition。
- Amazon CLI
-
开始在存储的视频中识别名人
以下
start-celebrity-recognition命令启动一项任务，在存储在 Amazon S3 存储桶中的指定视频文件中寻找名人。aws rekognition start-celebrity-recognition \ --video "S3Object={Bucket=MyVideoS3Bucket,Name=MyVideoFile.mpg}"输出：
{ "JobId": "1234567890abcdef1234567890abcdef1234567890abcdef1234567890abcdef" }有关更多信息，请参阅亚马逊 Rekognition 开发者指南中的识别存储视频中的名人。
-
有关 API 的详细信息，请参阅Amazon CLI 命令参考StartCelebrityRecognition
中的。
-
以下代码示例演示如何使用 start-content-moderation。
- Amazon CLI
-
开始识别存储视频中的不安全内容
以下
start-content-moderation命令启动一项任务，以检测存储在 Amazon S3 存储桶中的指定视频文件中的不安全内容。aws rekognition start-content-moderation \ --video "S3Object={Bucket=MyVideoS3Bucket,Name=MyVideoFile.mpg}"输出：
{ "JobId": "1234567890abcdef1234567890abcdef1234567890abcdef1234567890abcdef" }有关更多信息，请参阅《亚马逊 Rek ognition 开发者指南》中的 “检测存储的不安全视频”。
-
有关 API 的详细信息，请参阅Amazon CLI 命令参考StartContentModeration
中的。
-
以下代码示例演示如何使用 start-face-detection。
- Amazon CLI
-
检测视频中的人脸
以下
start-face-detection命令启动一项任务，以检测存储在 Amazon S3 存储桶中的指定视频文件中的人脸。aws rekognition start-face-detection --video "S3Object={Bucket=MyVideoS3Bucket,Name=MyVideoFile.mpg}"输出：
{ "JobId": "1234567890abcdef1234567890abcdef1234567890abcdef1234567890abcdef" }有关更多信息，请参阅亚马逊 Rek ognit ion 开发者指南中的检测存储视频中的人脸。
-
有关 API 的详细信息，请参阅Amazon CLI 命令参考StartFaceDetection
中的。
-
以下代码示例演示如何使用 start-face-search。
- Amazon CLI
-
在集合中搜索与视频中检测到的人脸相匹配的人脸
以下
start-face-search命令启动一项任务，在集合中搜索与 Amazon S3 存储桶中指定视频文件中检测到的人脸相匹配的人脸。aws rekognition start-face-search \ --video "S3Object={Bucket=MyVideoS3Bucket,Name=MyVideoFile.mpg}" \ --collection-id collection输出：
{ "JobId": "1234567890abcdef1234567890abcdef1234567890abcdef1234567890abcdef" }有关更多信息，请参阅亚马逊 Rek ognition 开发者指南中的在存储的视频中搜索人脸。
-
有关 API 的详细信息，请参阅Amazon CLI 命令参考StartFaceSearch
中的。
-
以下代码示例演示如何使用 start-label-detection。
- Amazon CLI
-
检测视频中的物体和场景
以下
start-label-detection命令启动一项任务，以检测存储在 Amazon S3 存储桶中的指定视频文件中的对象和场景。aws rekognition start-label-detection \ --video "S3Object={Bucket=MyVideoS3Bucket,Name=MyVideoFile.mpg}"输出：
{ "JobId": "1234567890abcdef1234567890abcdef1234567890abcdef1234567890abcdef" }有关更多信息，请参阅亚马逊 Rekognition 开发者指南中的检测视频中的标签。
-
有关 API 的详细信息，请参阅Amazon CLI 命令参考StartLabelDetection
中的。
-
以下代码示例演示如何使用 start-person-tracking。
- Amazon CLI
-
在存储的视频中开始人物路径
以下
start-person-tracking命令启动一项任务，以跟踪人们在 Amazon S3 存储桶中存储的指定视频文件中的路径。 :aws rekognition start-person-tracking \ --video "S3Object={Bucket=MyVideoS3Bucket,Name=MyVideoFile.mpg}"输出：
{ "JobId": "1234567890abcdef1234567890abcdef1234567890abcdef1234567890abcdef" }有关更多信息，请参阅亚马逊 Rekognition 开发者指南中的人员路径。
-
有关 API 的详细信息，请参阅Amazon CLI 命令参考StartPersonTracking
中的。
-
以下代码示例演示如何使用 start-stream-processor。
- Amazon CLI
-
启动流处理器
以下
start-stream-processor命令启动指定的视频流处理器。aws rekognition start-stream-processor \ --name my-stream-processor此命令不生成任何输出。
有关更多信息，请参阅亚马逊 Rekognition 开发者指南中的使用流媒体视频。
-
有关 API 的详细信息，请参阅Amazon CLI 命令参考StartStreamProcessor
中的。
-
以下代码示例演示如何使用 stop-stream-processor。
- Amazon CLI
-
停止正在运行的流处理器
以下
stop-stream-processor命令停止指定的正在运行的流处理器。aws rekognition stop-stream-processor \ --name my-stream-processor此命令不生成任何输出。
有关更多信息，请参阅亚马逊 Rekognition 开发者指南中的使用流媒体视频。
-
有关 API 的详细信息，请参阅Amazon CLI 命令参考StopStreamProcessor
中的。
-