API Usage

spoofsense-triton endpoints are optimised for speed and performance.

Walk through

Authentication

You will require x-api-key in order to use the API.

Contact [e-mail] in case you do not already have it.

1. POST /antispoofing

Performs a Passive Liveness Check

https://z3jwq0rjyj.execute-api.ap-south-1.amazonaws.com/prod/antispoofing

Request body

{
    "data": "image_base64_string",          # base64 string of the image
}

Response

Understanding the Response

Following table shows the API responses and behaviours in different cases

HTTP Code	Type of Image	Raw Output
200	Live Face	{ "success": true, "message": "Process finished successfully", "model_output": { "pred_idx": "real", "prob_real": 0.9997915625572205 }
200	Spoof Face	{ "success": true, "message": "Process finished successfully", "model_output": { "pred_idx": "spoof", "prob_real": 0.00045343424235454 }
200	No Face	{ "success": false, "message": "face not detected" }
200	Bad Input	{ "success": false, "message": "Invalid base64 string" }
413	Image Size > 10MB	HTTP content length exceeded 10485760 bytes.

model_output

model_output contains everything needed to check for facial liveness

"pred_idx" refers to the predicted class of the face and has two possible values:

• "real": A Live Face

• "spoof": A Spoof Face / Presentation Attack

"prob_real" refers to the probability of the face being "real" (live). A score above 0.50 means the face is "real". A score less than 0.50 means the face is "spoof". "prob_real" metric can should be used for writing the liveness check logic in your app.

Perform Liveness Check

if model_output[“prob_real”] > 0.55:

return “Liveness Confirmed”

else:

return “Liveness Failed”