moving off AWS Rekognition

Keep your code. Change two lines.

SightRadar speaks the AWS Rekognition API surface you already wrote against. Our official Python shim mirrors Rekognition's methods and response shapes, so a migration is a find-and-replace — not a rewrite.

Get an API key View the shim on GitHub

Before & after

The same workflow — create a collection, index faces, search by selfie. The only lines that change are the import and the client. Method names, arguments, and the response keys you read (FaceMatches, Similarity, ExternalImageId) stay the same.

AWS Rekognition (boto3)

rekognition.py

import boto3

rek = boto3.client("rekognition", region_name="us-east-1")

rek.create_collection(CollectionId="event-2026")

rek.index_faces(
    CollectionId="event-2026",
    Image={"S3Object": {"Bucket": "my-bucket", "Name": "guest.jpg"}},
    ExternalImageId="guest-1",
)

res = rek.search_faces_by_image(
    CollectionId="event-2026",
    Image={"Bytes": open("selfie.jpg", "rb").read()},
    FaceMatchThreshold=90,
    MaxFaces=5,
)
for m in res["FaceMatches"]:
    print(m["Face"]["ExternalImageId"], m["Similarity"])

SightRadar (drop-in shim)

sightradar.py

from sightradar_rekognition_shim import client   # 1. swap import

rek = client(api_key="frs_...")                  # 2. swap constructor

rek.create_collection(CollectionId="event-2026")

rek.index_faces(
    CollectionId="event-2026",
    Image={"URL": "https://cdn.example.com/guest.jpg"},
    ExternalImageId="guest-1",
)

res = rek.search_faces_by_image(
    CollectionId="event-2026",
    Image={"Bytes": open("selfie.jpg", "rb").read()},
    FaceMatchThreshold=90,
    MaxFaces=5,
)
for m in res["FaceMatches"]:
    print(m["Face"]["ExternalImageId"], m["Similarity"])

Install the shim

pip install sightradar-rekognition-shim

Prefer no extra dependency? Call the REST API directly:

# Or call the REST API directly — same Bearer-key pattern as any modern API:
curl https://api.sightradar.com/v1/collections/event-2026/search \
  -H "Authorization: Bearer frs_..." \
  -F file=@selfie.jpg -F threshold=0.9 -F limit=5

Method mapping

The Rekognition operations SightRadar supports, and the endpoint each maps to. Two conventions are translated for you: scores convert between Rekognition's 0–100 scale and SightRadar's 0–1, and image inputs accept Bytes, S3Object, or a URL.

AWS Rekognition	SightRadar
CreateCollection	POST /v1/collections
DeleteCollection	DELETE /v1/collections/{id}
ListCollections	GET /v1/collections
DescribeCollection	GET /v1/collections/{id}
IndexFaces	POST /v1/collections/{id}/index
SearchFacesByImage	POST /v1/collections/{id}/search
SearchFaces (by id)	POST /v1/collections/{id}/search-by-id
DetectFaces	POST /v1/detect
CompareFaces	POST /v1/compare

Operations SightRadar doesn't offer (label/text detection, celebrity recognition, async video) raise a clear error in the shim rather than silently doing nothing — so you know exactly what to adjust.

Why teams switch

Drop-in compatible
Keep your Rekognition-shaped code. The shim or a two-line REST swap is the whole migration.
Accuracy you can verify
Run your own selfie against your own collection in the playground before you commit a line of code.
No subscription, no minimums
Prepaid credits, billed per photo processed. Spend nothing until you call the API.
Lower cost than Rekognition
Real-time recognition runs about 26% below AWS Rekognition Group-1, with batch lower still.

Start migrating See pricing Migration FAQ