Contoh Rekognition Amazon menggunakan AWS CLI - AWS SDKContoh Kode

Ada lebih banyak AWS SDK contoh yang tersedia di GitHub repo SDKContoh AWS Dokumen.

Terjemahan disediakan oleh mesin penerjemah. Jika konten terjemahan yang diberikan bertentangan dengan versi bahasa Inggris aslinya, utamakan versi bahasa Inggris.

Contoh Rekognition Amazon menggunakan AWS CLI

Contoh kode berikut menunjukkan cara melakukan tindakan dan mengimplementasikan skenario umum dengan menggunakan AWS Command Line Interface With Amazon Rekognition.

Tindakan adalah kutipan kode dari program yang lebih besar dan harus dijalankan dalam konteks. Sementara tindakan menunjukkan cara memanggil fungsi layanan individual, Anda dapat melihat tindakan dalam konteks dalam skenario terkait.

Setiap contoh menyertakan tautan ke kode sumber lengkap, di mana Anda dapat menemukan instruksi tentang cara mengatur dan menjalankan kode dalam konteks.

Tindakan

Contoh kode berikut menunjukkan cara menggunakancompare-faces.

Untuk informasi selengkapnya, lihat Membandingkan wajah dalam gambar.

AWS CLI

Untuk membandingkan wajah dalam dua gambar

compare-facesPerintah berikut membandingkan wajah dalam dua gambar yang disimpan dalam bucket Amazon S3.

aws rekognition compare-faces \ --source-image '{"S3Object":{"Bucket":"MyImageS3Bucket","Name":"source.jpg"}}' \ --target-image '{"S3Object":{"Bucket":"MyImageS3Bucket","Name":"target.jpg"}}'

Output:

{ "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 } }

Untuk informasi selengkapnya, lihat Membandingkan Wajah dalam Gambar di Panduan Pengembang Rekognition Amazon.

  • Untuk API detailnya, lihat CompareFacesdi Referensi AWS CLI Perintah.

Contoh kode berikut menunjukkan cara menggunakancreate-collection.

Untuk informasi selengkapnya, lihat Membuat koleksi.

AWS CLI

Untuk membuat koleksi

create-collectionPerintah berikut membuat koleksi dengan nama yang ditentukan.

aws rekognition create-collection \ --collection-id "MyCollection"

Output:

{ "CollectionArn": "aws:rekognition:us-west-2:123456789012:collection/MyCollection", "FaceModelVersion": "4.0", "StatusCode": 200 }

Untuk informasi selengkapnya, lihat Membuat Koleksi di Panduan Pengembang Rekognition Amazon.

Contoh kode berikut menunjukkan cara menggunakancreate-stream-processor.

AWS CLI

Untuk membuat prosesor aliran baru

create-stream-processorContoh berikut membuat prosesor aliran baru dengan konfigurasi yang ditentukan.

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}}'

Output:

{ "StreamProcessorArn": "arn:aws:rekognition:us-west-2:123456789012:streamprocessor/my-stream-processor" }

Untuk informasi selengkapnya, lihat Bekerja dengan Video Streaming di Panduan Pengembang Rekognition Amazon.

Contoh kode berikut menunjukkan cara menggunakandelete-collection.

Untuk informasi selengkapnya, lihat Menghapus koleksi.

AWS CLI

Untuk menghapus koleksi

delete-collectionPerintah berikut menghapus koleksi yang ditentukan.

aws rekognition delete-collection \ --collection-id MyCollection

Output:

{ "StatusCode": 200 }

Untuk informasi selengkapnya, lihat Menghapus Koleksi di Panduan Pengembang Rekognition Amazon.

Contoh kode berikut menunjukkan cara menggunakandelete-faces.

Untuk informasi selengkapnya, lihat Menghapus wajah dari koleksi.

AWS CLI

Untuk menghapus wajah dari koleksi

delete-facesPerintah berikut menghapus wajah yang ditentukan dari koleksi.

aws rekognition delete-faces \ --collection-id MyCollection --face-ids '["0040279c-0178-436e-b70a-e61b074e96b0"]'

Output:

{ "DeletedFaces": [ "0040279c-0178-436e-b70a-e61b074e96b0" ] }

Untuk informasi selengkapnya, lihat Menghapus Wajah dari Koleksi di Panduan Pengembang Rekognition Amazon.

  • Untuk API detailnya, lihat DeleteFacesdi Referensi AWS CLI Perintah.

Contoh kode berikut menunjukkan cara menggunakandelete-stream-processor.

AWS CLI

Untuk menghapus prosesor aliran

delete-stream-processorPerintah berikut menghapus prosesor aliran yang ditentukan.

aws rekognition delete-stream-processor \ --name my-stream-processor

Perintah ini tidak menghasilkan output.

Untuk informasi selengkapnya, lihat Bekerja dengan Video Streaming di Panduan Pengembang Rekognition Amazon.

Contoh kode berikut menunjukkan cara menggunakandescribe-collection.

Untuk informasi selengkapnya, lihat Menjelaskan koleksi.

AWS CLI

Untuk menggambarkan koleksi

describe-collectionContoh berikut menampilkan rincian tentang koleksi yang ditentukan.

aws rekognition describe-collection \ --collection-id MyCollection

Output:

{ "FaceCount": 200, "CreationTimestamp": 1569444828.274, "CollectionARN": "arn:aws:rekognition:us-west-2:123456789012:collection/MyCollection", "FaceModelVersion": "4.0" }

Untuk informasi selengkapnya, lihat Menjelaskan Koleksi di Panduan Pengembang Rekognition Amazon.

Contoh kode berikut menunjukkan cara menggunakandescribe-stream-processor.

AWS CLI

Untuk mendapatkan informasi tentang prosesor aliran

describe-stream-processorPerintah berikut menampilkan rincian tentang prosesor aliran yang ditentukan.

aws rekognition describe-stream-processor \ --name my-stream-processor

Output:

{ "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 }

Untuk informasi selengkapnya, lihat Bekerja dengan Video Streaming di Panduan Pengembang Rekognition Amazon.

Contoh kode berikut menunjukkan cara menggunakandetect-faces.

Untuk informasi selengkapnya, lihat Mendeteksi wajah dalam gambar.

AWS CLI

Untuk mendeteksi wajah dalam gambar

detect-facesPerintah berikut mendeteksi wajah dalam gambar tertentu yang disimpan dalam bucket Amazon S3.

aws rekognition detect-faces \ --image '{"S3Object":{"Bucket":"MyImageS3Bucket","Name":"MyFriend.jpg"}}' \ --attributes "ALL"

Output:

{ "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 } } ] }

Untuk informasi selengkapnya, lihat Mendeteksi Wajah dalam Gambar di Panduan Pengembang Rekognition Amazon.

  • Untuk API detailnya, lihat DetectFacesdi Referensi AWS CLI Perintah.

Contoh kode berikut menunjukkan cara menggunakandetect-labels.

Untuk informasi selengkapnya, lihat Mendeteksi label dalam gambar.

AWS CLI

Untuk mendeteksi label dalam gambar

detect-labelsContoh berikut mendeteksi adegan dan objek dalam gambar yang disimpan dalam bucket Amazon S3.

aws rekognition detect-labels \ --image '{"S3Object":{"Bucket":"bucket","Name":"image"}}'

Output:

{ "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" }

Untuk informasi selengkapnya, lihat Mendeteksi Label dalam Gambar di Panduan Pengembang Rekognition Amazon.

  • Untuk API detailnya, lihat DetectLabelsdi Referensi AWS CLI Perintah.

Contoh kode berikut menunjukkan cara menggunakandetect-moderation-labels.

Untuk informasi selengkapnya, lihat Mendeteksi gambar yang tidak pantas.

AWS CLI

Untuk mendeteksi konten yang tidak aman dalam gambar

detect-moderation-labelsPerintah berikut mendeteksi konten yang tidak aman dalam gambar tertentu yang disimpan dalam bucket Amazon S3.

aws rekognition detect-moderation-labels \ --image "S3Object={Bucket=MyImageS3Bucket,Name=gun.jpg}"

Output:

{ "ModerationModelVersion": "3.0", "ModerationLabels": [ { "Confidence": 97.29618072509766, "ParentName": "Violence", "Name": "Weapon Violence" }, { "Confidence": 97.29618072509766, "ParentName": "", "Name": "Violence" } ] }

Untuk informasi selengkapnya, lihat Mendeteksi Gambar Tidak Aman di Panduan Pengembang Rekognition Amazon.

Contoh kode berikut menunjukkan cara menggunakandetect-text.

Untuk informasi selengkapnya, lihat Mendeteksi teks dalam gambar.

AWS CLI

Untuk mendeteksi teks dalam gambar

detect-textPerintah berikut mendeteksi teks dalam gambar yang ditentukan.

aws rekognition detect-text \ --image '{"S3Object":{"Bucket":"MyImageS3Bucket","Name":"ExamplePicture.jpg"}}'

Output:

{ "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 } ] }
  • Untuk API detailnya, lihat DetectTextdi Referensi AWS CLI Perintah.

Contoh kode berikut menunjukkan cara menggunakandisassociate-faces.

AWS CLI
aws rekognition disassociate-faces --face-ids list-of-face-ids --user-id user-id --collection-id collection-name --region region-name

Contoh kode berikut menunjukkan cara menggunakanget-celebrity-info.

AWS CLI

Untuk mendapatkan informasi tentang selebriti

get-celebrity-infoPerintah berikut menampilkan informasi tentang selebriti yang ditentukan. idParameter berasal dari panggilan sebelumnya kerecognize-celebrities.

aws rekognition get-celebrity-info --id nnnnnnn

Output:

{ "Name": "Celeb A", "Urls": [ "www.imdb.com/name/aaaaaaaaa" ] }

Untuk informasi selengkapnya, lihat Mendapatkan Informasi Tentang Selebriti di Panduan Pengembang Rekognition Amazon.

Contoh kode berikut menunjukkan cara menggunakanget-celebrity-recognition.

AWS CLI

Untuk mendapatkan hasil operasi pengakuan selebriti

get-celebrity-recognitionPerintah berikut menampilkan hasil operasi pengenalan selebriti yang Anda mulai sebelumnya dengan menelepon. start-celebrity-recognition

aws rekognition get-celebrity-recognition \ --job-id 1234567890abcdef1234567890abcdef1234567890abcdef1234567890abcdef

Output:

{ "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 } }

Untuk informasi selengkapnya, lihat Mengenali Selebriti dalam Video Tersimpan di Panduan Pengembang Rekognition Amazon.

Contoh kode berikut menunjukkan cara menggunakanget-content-moderation.

AWS CLI

Untuk mendapatkan hasil operasi konten yang tidak aman

get-content-moderationPerintah berikut menampilkan hasil operasi konten tidak aman yang Anda mulai sebelumnya dengan meneleponstart-content-moderation.

aws rekognition get-content-moderation \ --job-id 1234567890abcdef1234567890abcdef1234567890abcdef1234567890abcdef

Output:

{ "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 } }

Untuk informasi selengkapnya, lihat Mendeteksi Video Tersimpan Tidak Aman di Panduan Pengembang Rekognition Amazon.

Contoh kode berikut menunjukkan cara menggunakanget-face-detection.

AWS CLI

Untuk mendapatkan hasil operasi deteksi wajah

get-face-detectionPerintah berikut menampilkan hasil operasi deteksi wajah yang Anda mulai sebelumnya dengan meneleponstart-face-detection.

aws rekognition get-face-detection \ --job-id 1234567890abcdef1234567890abcdef1234567890abcdef1234567890abcdef

Output:

{ "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 } }

Untuk informasi selengkapnya, lihat Mendeteksi Wajah dalam Video Tersimpan di Panduan Pengembang Rekognition Amazon.

Contoh kode berikut menunjukkan cara menggunakanget-face-search.

AWS CLI

Untuk mendapatkan hasil operasi pencarian wajah

get-face-searchPerintah berikut menampilkan hasil operasi pencarian wajah yang Anda mulai sebelumnya dengan meneleponstart-face-search.

aws rekognition get-face-search \ --job-id 1234567890abcdef1234567890abcdef1234567890abcdef1234567890abcdef

Output:

{ "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 } }

Untuk informasi selengkapnya, lihat Mencari Video Tersimpan untuk Wajah di Panduan Pengembang Rekognition Amazon.

  • Untuk API detailnya, lihat GetFaceSearchdi Referensi AWS CLI Perintah.

Contoh kode berikut menunjukkan cara menggunakanget-label-detection.

AWS CLI

Untuk mendapatkan hasil operasi deteksi objek dan adegan

get-label-detectionPerintah berikut menampilkan hasil operasi deteksi objek dan adegan yang Anda mulai sebelumnya dengan meneleponstart-label-detection.

aws rekognition get-label-detection \ --job-id 1234567890abcdef1234567890abcdef1234567890abcdef1234567890abcdef

Output:

{ "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" }

Untuk informasi selengkapnya, lihat Mendeteksi Label dalam Video di Panduan Pengembang Rekognition Amazon.

Contoh kode berikut menunjukkan cara menggunakanget-person-tracking.

AWS CLI

Untuk mendapatkan hasil dari operasi pathing orang

get-person-trackingPerintah berikut menampilkan hasil operasi pathing orang yang Anda mulai sebelumnya dengan meneleponstart-person-tracking.

aws rekognition get-person-tracking \ --job-id 1234567890abcdef1234567890abcdef1234567890abcdef1234567890abcdef

Output:

{ "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 } }

Untuk informasi selengkapnya, lihat People Pathing di Panduan Pengembang Rekognition Amazon.

Contoh kode berikut menunjukkan cara menggunakanindex-faces.

Untuk informasi selengkapnya, lihat Menambahkan wajah ke koleksi.

AWS CLI

Untuk menambahkan wajah ke koleksi

index-facesPerintah berikut menambahkan wajah yang ditemukan dalam gambar ke koleksi yang ditentukan.

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"

Output:

{ "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" }

Untuk informasi selengkapnya, lihat Menambahkan Wajah ke Koleksi di Panduan Pengembang Rekognition Amazon.

  • Untuk API detailnya, lihat IndexFacesdi Referensi AWS CLI Perintah.

Contoh kode berikut menunjukkan cara menggunakanlist-collections.

Untuk informasi selengkapnya, lihat Daftar koleksi.

AWS CLI

Untuk daftar koleksi yang tersedia

list-collectionsPerintah berikut mencantumkan koleksi yang tersedia di AWS akun.

aws rekognition list-collections

Output:

{ "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" ] }

Untuk informasi selengkapnya, lihat Daftar Koleksi di Panduan Pengembang Rekognition Amazon.

Contoh kode berikut menunjukkan cara menggunakanlist-faces.

Untuk informasi selengkapnya, lihat Daftar wajah dalam koleksi.

AWS CLI

Untuk membuat daftar wajah dalam koleksi

list-facesPerintah berikut mencantumkan wajah-wajah dalam koleksi yang ditentukan.

aws rekognition list-faces \ --collection-id MyCollection

Output:

{ "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" } ] }

Untuk informasi selengkapnya, lihat Daftar Wajah dalam Koleksi di Panduan Pengembang Rekognition Amazon.

  • Untuk API detailnya, lihat ListFacesdi Referensi AWS CLI Perintah.

Contoh kode berikut menunjukkan cara menggunakanlist-stream-processors.

AWS CLI

Untuk mencantumkan prosesor streaming di akun Anda

list-stream-processorsPerintah berikut mencantumkan prosesor aliran di akun Anda dan status masing-masing.

aws rekognition list-stream-processors

Output:

{ "StreamProcessors": [ { "Status": "STOPPED", "Name": "my-stream-processor" } ] }

Untuk informasi selengkapnya, lihat Bekerja dengan Video Streaming di Panduan Pengembang Rekognition Amazon.

Contoh kode berikut menunjukkan cara menggunakanrecognize-celebrities.

Untuk informasi selengkapnya, lihat Mengenali selebriti dalam sebuah gambar.

AWS CLI

Untuk mengenali selebriti dalam sebuah gambar

recognize-celebritiesPerintah berikut mengenali selebriti dalam gambar tertentu yang disimpan dalam bucket Amazon S3. :

aws rekognition recognize-celebrities \ --image "S3Object={Bucket=MyImageS3Bucket,Name=moviestars.jpg}"

Output:

{ "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" } ] }

Untuk informasi selengkapnya, lihat Mengenali Selebriti dalam Gambar di Panduan Pengembang Rekognition Amazon.

Contoh kode berikut menunjukkan cara menggunakansearch-faces-by-image.

Untuk informasi selengkapnya, lihat Mencari wajah (gambar).

AWS CLI

Untuk mencari wajah dalam koleksi yang cocok dengan wajah terbesar dalam sebuah gambar.

search-faces-by-imagePerintah berikut mencari wajah dalam koleksi yang cocok dengan wajah terbesar dalam gambar yang ditentukan. :

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" }

Untuk informasi selengkapnya, lihat Mencari Wajah Menggunakan Gambar di Panduan Pengembang Rekognition Amazon.

Contoh kode berikut menunjukkan cara menggunakansearch-faces.

Untuk informasi selengkapnya, lihat Mencari wajah (ID wajah).

AWS CLI

Untuk mencari wajah dalam koleksi yang cocok dengan ID wajah.

search-facesPerintah berikut mencari wajah dalam koleksi yang cocok dengan ID wajah yang ditentukan.

aws rekognition search-faces \ --face-id 8d3cfc70-4ba8-4b36-9644-90fba29c2dac \ --collection-id MyCollection

Output:

{ "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 } ] }

Untuk informasi selengkapnya, lihat Mencari Wajah Menggunakan ID Wajahnya di Panduan Pengembang Amazon Rekognition.

  • Untuk API detailnya, lihat SearchFacesdi Referensi AWS CLI Perintah.

Contoh kode berikut menunjukkan cara menggunakanstart-celebrity-recognition.

AWS CLI

Untuk memulai pengakuan selebriti dalam video yang disimpan

start-celebrity-recognitionPerintah berikut memulai pekerjaan untuk mencari selebriti dalam file video tertentu yang disimpan dalam bucket Amazon S3.

aws rekognition start-celebrity-recognition \ --video "S3Object={Bucket=MyVideoS3Bucket,Name=MyVideoFile.mpg}"

Output:

{ "JobId": "1234567890abcdef1234567890abcdef1234567890abcdef1234567890abcdef" }

Untuk informasi selengkapnya, lihat Mengenali Selebriti dalam Video Tersimpan di Panduan Pengembang Rekognition Amazon.

Contoh kode berikut menunjukkan cara menggunakanstart-content-moderation.

AWS CLI

Untuk memulai pengenalan konten yang tidak aman dalam video yang disimpan

start-content-moderationPerintah berikut memulai pekerjaan untuk mendeteksi konten yang tidak aman dalam file video tertentu yang disimpan dalam bucket Amazon S3.

aws rekognition start-content-moderation \ --video "S3Object={Bucket=MyVideoS3Bucket,Name=MyVideoFile.mpg}"

Output:

{ "JobId": "1234567890abcdef1234567890abcdef1234567890abcdef1234567890abcdef" }

Untuk informasi selengkapnya, lihat Mendeteksi Video Tersimpan Tidak Aman di Panduan Pengembang Rekognition Amazon.

Contoh kode berikut menunjukkan cara menggunakanstart-face-detection.

AWS CLI

Untuk mendeteksi wajah dalam video

start-face-detectionPerintah berikut memulai pekerjaan untuk mendeteksi wajah dalam file video tertentu yang disimpan dalam bucket Amazon S3.

aws rekognition start-face-detection --video "S3Object={Bucket=MyVideoS3Bucket,Name=MyVideoFile.mpg}"

Output:

{ "JobId": "1234567890abcdef1234567890abcdef1234567890abcdef1234567890abcdef" }

Untuk informasi selengkapnya, lihat Mendeteksi Wajah dalam Video Tersimpan di Panduan Pengembang Rekognition Amazon.

Contoh kode berikut menunjukkan cara menggunakanstart-face-search.

AWS CLI

Untuk mencari wajah dalam koleksi yang cocok dengan wajah yang terdeteksi dalam video

start-face-searchPerintah berikut memulai pekerjaan untuk mencari wajah dalam koleksi yang cocok dengan wajah yang terdeteksi dalam file video yang ditentukan dalam bucket Amazon S3.

aws rekognition start-face-search \ --video "S3Object={Bucket=MyVideoS3Bucket,Name=MyVideoFile.mpg}" \ --collection-id collection

Output:

{ "JobId": "1234567890abcdef1234567890abcdef1234567890abcdef1234567890abcdef" }

Untuk informasi selengkapnya, lihat Mencari Video Tersimpan untuk Wajah di Panduan Pengembang Rekognition Amazon.

Contoh kode berikut menunjukkan cara menggunakanstart-label-detection.

AWS CLI

Untuk mendeteksi objek dan adegan dalam video

start-label-detectionPerintah berikut memulai pekerjaan untuk mendeteksi objek dan adegan dalam file video tertentu yang disimpan dalam bucket Amazon S3.

aws rekognition start-label-detection \ --video "S3Object={Bucket=MyVideoS3Bucket,Name=MyVideoFile.mpg}"

Output:

{ "JobId": "1234567890abcdef1234567890abcdef1234567890abcdef1234567890abcdef" }

Untuk informasi selengkapnya, lihat Mendeteksi Label dalam Video di Panduan Pengembang Rekognition Amazon.

Contoh kode berikut menunjukkan cara menggunakanstart-person-tracking.

AWS CLI

Untuk memulai jalur orang dalam video yang disimpan

start-person-trackingPerintah berikut memulai pekerjaan untuk melacak jalur yang diambil orang di bagian video tertentu yang disimpan di bucket Amazon S3. :

aws rekognition start-person-tracking \ --video "S3Object={Bucket=MyVideoS3Bucket,Name=MyVideoFile.mpg}"

Output:

{ "JobId": "1234567890abcdef1234567890abcdef1234567890abcdef1234567890abcdef" }

Untuk informasi selengkapnya, lihat People Pathing di Panduan Pengembang Rekognition Amazon.

Contoh kode berikut menunjukkan cara menggunakanstart-stream-processor.

AWS CLI

Untuk memulai prosesor streaming

start-stream-processorPerintah berikut memulai prosesor aliran video yang ditentukan.

aws rekognition start-stream-processor \ --name my-stream-processor

Perintah ini tidak menghasilkan output.

Untuk informasi selengkapnya, lihat Bekerja dengan Video Streaming di Panduan Pengembang Rekognition Amazon.

Contoh kode berikut menunjukkan cara menggunakanstop-stream-processor.

AWS CLI

Untuk menghentikan prosesor aliran yang sedang berjalan

stop-stream-processorPerintah berikut menghentikan prosesor aliran berjalan yang ditentukan.

aws rekognition stop-stream-processor \ --name my-stream-processor

Perintah ini tidak menghasilkan output.

Untuk informasi selengkapnya, lihat Bekerja dengan Video Streaming di Panduan Pengembang Rekognition Amazon.