Demographic Attributes

Visual Detection Overview

Visual detection models localize an object of interest in an image by returning a box that bounds that object, as well as the type of that object, also referred to as the class. A detector can detect multiple objects of different classes per image. For each detection, a detector outputs a confidence score that is independent of any other detections.

The output object in Hive detection APIs lists each detected object, including:

• The geometric description of the detected bounding box.
• The predicted class for the detection.
• For some models, the confidence score for the detection.

When submitting a video to be processed, Hive’s backend splits the video into frames, runs the model on each frame, then recombines the results into a single response for the entire video. The video output for a detector is similar to a list of detection output objects, but with multiple timestamps.

Demographics Model

Hive’s face detection model achieves state-of-the-art accuracy. Face detections are passed through an additional classification step to predict attributes like gender, age, or "liveness".

Gender Classification
The gender classification model runs on-top of the face detections provided by the face detection model, and classifies faces as:

• male
• female
• other_gender: non-human face / indistinguishable gender

Hive detects perceived gender based on the physical appearance of a face in the given context. These detections are not predictions of gender identity and this model is not designed to be used as such.

Age Classification
The age classification model runs on-top of the face detections provided by the face detection model, and classifies faces as:

• senior: 65 yrs old and above
• middle_aged: 45-64 yrs old
• adult: 18-44 yrs old
• teenager: 13-17 yrs old
• pre_teen: 5-12 yrs old, any kid older than a toddler but younger than a teen
• toddler: 2-4 yrs old, starting to be able to walk / crawl
• baby: 0-1 yrs old, recently born, unlikely to know how to walk / crawl
• other_age: non-human face / indistinguishable age

Note: All of the above ranges are inclusive. In the range 13-17, for example, all ages 13.0-17.99 are included.

Age Regression (Beta)
This class returns a number representing the predicted exact age of the subject.

Liveness Classification (Beta)
The "liveness" classification model run on top of the face detection model and classifies faces as:

• primary: this face exists in the primary image
• secondary: this face exist in a image, screen, or painting inside of the primary image (ex: A face in a picture frame hung on the wall)

Request Format

The request format for this API includes a field for the media being submitted, either as a local file path or as a url. For more information about submitting a task, see our API reference guides to synchronous and asynchronous submissions.

# submit a task with media with url
curl --request POST \
  --url https://api.thehive.ai/api/v2/task/sync \ # this is a sync example, see API reference for async
  --header 'accept: application/json' \
  --header 'authorization: token <API_KEY>' \
  --form 'url=http://hive-public.s3.amazonaws.com/demo_request/gun1.jpg'

# submit a task with media with local media file
 curl --request POST \
     --url https://api.thehive.ai/api/v2/task/sync \ # this is a sync example, see API reference for async
     --header 'Authorization: Token <token>' \
     --form 'media=@"<absolute/path/to/file>"'

Supported File Types

Image Formats:
gif
jpg
png
webp

Video Formats:
mp4
webm
avi
mkv
wmv
mov