Rekognition

Protocol: JSON 1.1 (X-Amz-Target: RekognitionService.*) Endpoint: POST http://localhost:4566/

Supported Actions

Action	Description
DetectLabels	Detect objects, scenes, and concepts in an image
DetectFaces	Detect faces in an image and their attributes
DetectText	Detect text in an image
CompareFaces	Compare a face in a source image with faces in a target image
DetectModerationLabels	Detect unsafe or inappropriate content in an image

Emulation Behavior

• Stub responses: every action returns a fixed, AWS-shaped response — no real image analysis is performed. Image/SourceImage/TargetImage content is accepted but never decoded, the same way Textract accepts Document without reading it.
• Content-listing operations return one canned entry: DetectLabels and DetectText always report a single stub label/text detection, matching the Textract stub's block-hierarchy convention.
• Face/moderation operations return empty results: DetectFaces, CompareFaces, and DetectModerationLabels always report nothing found (empty FaceDetails/FaceMatches/ModerationLabels) rather than fabricating biometric attributes or a moderation flag for content that was never analyzed — an honest "nothing detected" response, matching the Comprehend PII-detection stub's precedent.
• Real input validation: Image (or SourceImage/TargetImage for CompareFaces) is required, must be a JSON structure, and must specify Bytes (string-typed) or S3Object (structure-typed) — matching AWS's own modeling and rejecting wrong JSON types as SerializationException. This is protocol compatibility, not content analysis.
• Intentional deviations: Bytes's content is not validated as well-formed base64 (the S3Object shape has no required members in AWS's own model, so its fields aren't validated either), and supplying both Bytes and S3Object is accepted rather than rejected — nothing in the Rekognition API model declares that combination invalid, and the stub never reads either field's content regardless.
• Out of scope: face-collection persistence (CreateCollection, IndexFaces, SearchFaces), custom-model training (Projects, Datasets, ProjectVersions), live video (StreamProcessor), async video jobs (Start*/Get* Celebrity/Content/Face/Label/Person/Segment/Text detection), and Face Liveness sessions are not implemented.

Configuration

Variable	Default	Description
FLOCI_SERVICES_REKOGNITION_ENABLED	true	Enable or disable the service
AI_MOCK_CONFIG	unset	Path to a shared mock-response config file — see "Mock Responses" below

Mock Responses

The default stub responses above are the same for every call. To exercise application logic that branches on detection results, point AI_MOCK_CONFIG at a JSON file shared across Rekognition, Textract, and Comprehend:

{
  "rekognition": {
    "my-bucket/cat.jpg": {
      "DetectLabels": {
        "Labels": [{ "Name": "Cat", "Confidence": 97.2 }, { "Name": "Animal", "Confidence": 98.1 }],
        "LabelModelVersion": "1.0"
      }
    }
  }
}

The lookup key is "<Bucket>/<Name>" from Image.S3Object (or SourceImage.S3Object for CompareFaces — TargetImage has no independent key in this scheme). A Bytes-backed image has no such key, so mocking only applies to S3Object-based calls. The file is re-read when its modification time changes, so it can be edited without restarting the emulator. A missing file, an unset AI_MOCK_CONFIG, or no matching entry all fall back to the default stub.

Examples

export AWS_ENDPOINT_URL=http://localhost:4566

aws rekognition detect-labels \
  --image '{"S3Object":{"Bucket":"my-bucket","Name":"photo.jpg"}}' \
  --endpoint-url $AWS_ENDPOINT_URL

aws rekognition detect-text \
  --image '{"S3Object":{"Bucket":"my-bucket","Name":"photo.jpg"}}' \
  --endpoint-url $AWS_ENDPOINT_URL

aws rekognition compare-faces \
  --source-image '{"S3Object":{"Bucket":"my-bucket","Name":"source.jpg"}}' \
  --target-image '{"S3Object":{"Bucket":"my-bucket","Name":"target.jpg"}}' \
  --endpoint-url $AWS_ENDPOINT_URL

SDK Example (Java)

RekognitionClient rekognition = RekognitionClient.builder()
    .endpointOverride(URI.create("http://localhost:4566"))
    .region(Region.US_EAST_1)
    .credentialsProvider(StaticCredentialsProvider.create(
        AwsBasicCredentials.create("test", "test")))
    .build();

DetectLabelsResponse response = rekognition.detectLabels(req -> req
    .image(img -> img.s3Object(s3 -> s3.bucket("my-bucket").name("photo.jpg"))));

System.out.println("Labels: " + response.labels());