Make your device aware of the people around it

People entering / leaving the scene? Age and gender of surrounding people? Emotions of surrounding people? Who are the people around? Where people are looking at? Are people talking around?

Send your first requests to angus.ai API in 5 minutes…

You send a video stream, you get back structured data, in real time!

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Our API is made of several services…

Face Detection

Tracks human faces in a video stream

Docs – Code sample

Gaze Estimation

Tracks heads orientation and eyes gazing in a video stream

Docs – Code sample

Face Recognition

Identifies specific people in a video stream

Docs – Code sample

Face Expression Estimation

Tracks human facial emotions (suprise, anger, etc…) in a video stream

Docs – Code sample

Age and Gender estimation

Tracks age and gender of the people seen in a video stream

Docs – Code sample

Voice Activity Detector

Detects if a human is heard in an audio stream

Docs – Code sample

Pricing

Starter

Access all APIs

Unlimited number of devices

Sandbox – performance drops can occur

0€

Get Started for free

Hosted

Access all APIs

Unlimited number of devices

handle as many request/day as needed

from 9€ / month

On premise

Access all APIs

Unlimited number of devices

Docker image (x86 64bits)

90€ / core / month

Get started in 3 steps…

1. Get your credentials, 2. Install our SDK, 3. Copy/paste 5 lines of codes

Python

Make a request

import angus
conn = angus.connect()
service = conn.services.get_service( 'age_and_gender_estimation' )
job = service.process({'image': open("path/to/your/image.png")})
print job.result

Get a response

{
  "input_size" : [480, 640],
  "nb_faces" : 1,
  "faces" : [
              {
                "roi" : [345, 223, 34, 54],
                "roi_confidence" : 0.89,
                "age" : 32,
                "age_confidence" :0.87,
                "gender" : "male",
                "gender_confidence" : 0.95
              }
            ]
}

Sign up to get your credentials and follow the step by step python tutorial here.

Java

Make a request

import ai.angus.sdk.*;

Configuration conf = new ConfigurationImpl();
Root root = conf.connect();
Service service = root.getServices().getService( "age_and_gender_estimation", 1 );

JSONObject params = new JSONObject();
params.put("image", new File("path/to/your/image.png"));
Job job = service.process(params);

System.out.println(job.getResult().toJSONString());

Get a response

{
  "input_size" : [480, 640],
  "nb_faces" : 1,
  "faces" : [
              {
                "roi" : [345, 223, 34, 54],
                "roi_confidence" : 0.89,
                "age" : 32,
                "age_confidence" :0.87,
                "gender" : "male",
                "gender_confidence" : 0.95
              }
            ]
}

Sign up to get your credentials and follow the step by step java tutorial here.

Curl

Make a request

curl -u your_client_id:your_access_token \
-F "attachment://bar=@path/to/your/image.jpg ; type=image/jpg" \
-F 'meta={"async" : false, "image": "attachment://bar"} ; type=application/json' \
https://gate.angus.ai/services/age_and_gender_estimation/1/jobs

Get a response

{
"url": "https://gate.angus.ai/services/age_and_gender_estimation/1/jobs/1944556c-baf8-11e5-85c3-0242ac110001",
"status": 201,
"input_size" : [480, 640],
"nb_faces" : 1,
"faces" : [{"roi" : [345, 223, 34, 54], "roi_confidence" : 0.89, "age" : 32, "age_confidence" :0.87, "gender" : "male", "gender_confidence" : 0.95}]
}

Sign up to get your credentials and see our Restful API reference here.

DEVELOPERS

Getting API credentials

Getting started in Python

Getting started in Java

COMPANY

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