Examples with BinaryFeature com.amplifyframework.predictions.models.BinaryFeature used on opensource projects

Example 1 with BinaryFeature

use of com.amplifyframework.predictions.models.BinaryFeature in project amplify-android by aws-amplify.

the class AWSRekognitionService method detectEntities.

private List<EntityDetails> detectEntities(ByteBuffer imageData) throws PredictionsException {
    DetectFacesRequest request = new DetectFacesRequest().withImage(new Image().withBytes(imageData)).withAttributes(Attribute.ALL.toString());
    // Detect entities in the given image via Amazon Rekognition
    final DetectFacesResult result;
    try {
        result = rekognition.detectFaces(request);
    } catch (AmazonClientException serviceException) {
        throw new PredictionsException("Amazon Rekognition encountered an error while detecting faces.", serviceException, "See attached service exception for more details.");
    }
    List<EntityDetails> entities = new ArrayList<>();
    for (FaceDetail face : result.getFaceDetails()) {
        // Extract details from face detection
        RectF box = RekognitionResultTransformers.fromBoundingBox(face.getBoundingBox());
        AgeRange ageRange = RekognitionResultTransformers.fromRekognitionAgeRange(face.getAgeRange());
        Pose pose = RekognitionResultTransformers.fromRekognitionPose(face.getPose());
        List<Landmark> landmarks = RekognitionResultTransformers.fromLandmarks(face.getLandmarks());
        List<BinaryFeature> features = RekognitionResultTransformers.fromFaceDetail(face);
        // Gender detection
        com.amazonaws.services.rekognition.model.Gender rekognitionGender = face.getGender();
        Gender amplifyGender = Gender.builder().value(GenderBinaryTypeAdapter.fromRekognition(rekognitionGender.getValue())).confidence(rekognitionGender.getConfidence()).build();
        // Emotion detection
        List<Emotion> emotions = new ArrayList<>();
        for (com.amazonaws.services.rekognition.model.Emotion rekognitionEmotion : face.getEmotions()) {
            EmotionType emotion = EmotionTypeAdapter.fromRekognition(rekognitionEmotion.getType());
            Emotion amplifyEmotion = Emotion.builder().value(emotion).confidence(rekognitionEmotion.getConfidence()).build();
            emotions.add(amplifyEmotion);
        }
        Collections.sort(emotions, Collections.reverseOrder());
        EntityDetails entity = EntityDetails.builder().box(box).ageRange(ageRange).pose(pose).gender(amplifyGender).landmarks(landmarks).emotions(emotions).features(features).build();
        entities.add(entity);
    }
    return entities;
}

Example 2 with BinaryFeature

use of com.amplifyframework.predictions.models.BinaryFeature in project amplify-android by aws-amplify.

the class RekognitionResultTransformersTest method testFaceDetailConversion.

/**
 * Tests that the individual attributes from Rekognition
 * face detail are properly converted to a list of binary
 * features that are compatible with Amplify's entity
 * details.
 */
@Test
public void testFaceDetailConversion() {
    FaceDetail faceDetail = new FaceDetail().withBeard(new Beard().withValue(random.nextBoolean()).withConfidence(random.nextFloat())).withSunglasses(new Sunglasses().withValue(random.nextBoolean()).withConfidence(random.nextFloat())).withSmile(new Smile().withValue(random.nextBoolean()).withConfidence(random.nextFloat())).withEyeglasses(new Eyeglasses().withValue(random.nextBoolean()).withConfidence(random.nextFloat())).withMustache(new Mustache().withValue(random.nextBoolean()).withConfidence(random.nextFloat())).withMouthOpen(new MouthOpen().withValue(random.nextBoolean()).withConfidence(random.nextFloat())).withEyesOpen(new EyeOpen().withValue(random.nextBoolean()).withConfidence(random.nextFloat()));
    List<BinaryFeature> features = RekognitionResultTransformers.fromFaceDetail(faceDetail);
    FeatureAssert.assertMatches(Arrays.asList(faceDetail.getBeard().getValue(), faceDetail.getSunglasses().getValue(), faceDetail.getSmile().getValue(), faceDetail.getEyeglasses().getValue(), faceDetail.getMustache().getValue(), faceDetail.getMouthOpen().getValue(), faceDetail.getEyesOpen().getValue()), features);
}