Amazon Rekognition
Amazon Rekognition
Amazon Rekognition is image and video analysis — object detection, face recognition, text extraction, and content moderation.
Pretrained models work out of the box — no training data needed
Face recognition accuracy depends on lighting, angle, and age
Call Rekognition.detectLabels / detectFaces / detectText for sync analysis. Video uses startLabelDetection as an async job that writes results to S3.
Uptime · 30-day window
GitHub activity
About this API
Rekognition is the entry point to AWS computer vision — pretrained models for general object detection, face detection and comparison, text extraction, content moderation, celebrity recognition, landmark recognition, and activity detection. Image analysis is synchronous (millisecond latency); video analysis runs as async jobs that write results to S3 with SNS notifications.
Face recognition has several usage patterns: detectFaces returns attributes (age, emotion, eyewear) without identifying who; compareFaces verifies whether two faces match; indexFaces + searchFaces build a face collection for 1:N search. Custom Labels (2019) lets you upload tens to hundreds of labeled images, AWS auto-trains a domain-specific model (e.g. detect manufacturing defects), and you call an inference API. Several jurisdictions regulate face recognition (Illinois BIPA, Washington State, post-IBM-exit legislation in many places); evaluate compliance before deploying.
What you can build
- 1Moderate user-uploaded content on UGC platforms
- 2Cluster and search faces in photo libraries
- 3Extract text from images (OCR)
- 4Detect celebrities, landmarks, and activities in video
Strengths & limitations
Strengths
- Pretrained models work out of the box — no training data needed
- Video API samples frames to control cost
- Custom Labels lets you train domain-specific models with small datasets
Limitations
- Face recognition accuracy depends on lighting, angle, and age
- Some jurisdictions (e.g. parts of the US) regulate face recognition use
Example request
curl https://github.com/mermade/aws2openapi/<endpoint> \
-H "Authorization: Bearer $API_KEY"
# Some providers use X-Api-Key instead — verify in the docs.Getting started
Call Rekognition.detectLabels / detectFaces / detectText for sync analysis. Video uses startLabelDetection as an async job that writes results to S3.
FAQ
What is the Rekognition free tier?+
First 12 months: 5,000 images and 1,000 minutes of video per month.
How accurate is it?+
General object detection and text recognition approach commercial state-of-the-art. Face recognition is strong under standard conditions but degrades with lighting and angle. Use human review for high-stakes cases.
Does it support Chinese?+
detectText supports Chinese OCR. Other models output labels primarily in English.
Technical details
- Auth type
- api_key
- Pricing
- paid
- Protocols
- REST
- SDKs
- python, javascript, java, go, ruby, csharp
- Response time
- 26 ms
- Last health check
- 5/12/2026, 7:36:34 AM
Endpoints
Parsed from the OpenAPI spec. Showing 12 of 65 non-deprecated endpoints.
/#X-Amz-Target=RekognitionService.CompareFaces/#X-Amz-Target=RekognitionService.CopyProjectVersion/#X-Amz-Target=RekognitionService.CreateCollection/#X-Amz-Target=RekognitionService.CreateDataset/#X-Amz-Target=RekognitionService.CreateFaceLivenessSession/#X-Amz-Target=RekognitionService.CreateProject/#X-Amz-Target=RekognitionService.CreateProjectVersion/#X-Amz-Target=RekognitionService.CreateStreamProcessor/#X-Amz-Target=RekognitionService.DeleteCollection/#X-Amz-Target=RekognitionService.DeleteDataset/#X-Amz-Target=RekognitionService.DeleteFaces/#X-Amz-Target=RekognitionService.DeleteProject53 more endpoints not shown. See the OpenAPI spec for the full list.
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