Facial Age Estimator

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This model detects faces in an image, extracts facial features for each face detected and finally predicts the age of each face. The model uses a coarse-to-fine strategy to perform multi-class classification and regression for age estimation. The input to the model is an image and the output is a list of estimated ages and bounding box coordinates of each face detected in the image. The format of the bounding box coordinates is [xmin, ymin, width, height]. The model is based on the SSR-Net model.

Model Metadata

Domain Application Industry Framework Training Data Input Data Format
Vision Facial Recognition General Keras & TensorFlow IMDB-WIKI Dataset Image (PNG/JPG)



Component License Link
This repository Apache 2.0 LICENSE
Model Weights MIT LICENSE
Model Code (3rd party) MIT LICENSE
Test assets Various Asset README

Options available for deploying this model

This model can be deployed using the following mechanisms:

  • Deploy from Dockerhub:
    docker run -it -p 5000:5000 codait/max-facial-age-estimator
  • Deploy on Kubernetes:
    kubectl apply -f https://raw.githubusercontent.com/IBM/MAX-Facial-Age-Estimator/master/max-facial-age-estimator.yaml
  • Locally: follow the instructions in the model README on GitHub

Example Usage

Once deployed, you can test the model from the command line. For example:

curl -F "image=@assets/tom_cruise.jpg" -XPOST http://localhost:5000/model/predict
    "status": "ok",
    "predictions": [
            "age_estimation": 48,
            "face_box": [