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age-gender-recognition-retail-0013

Use Case and High-Level Description

Fully convolutional network for simultaneous Age/Gender recognition. The network is able to recognize age of people in [18, 75] years old range, it is not applicable for children since their faces were not in the training set.

Validation Dataset - Internal

~20,000 unique subjects representing diverse ages, genders, and ethnicities.

Example

Input Image

Result

Female, 18.97

Male, 26.52

Male, 33.41

Specification

Metric

Value

Rotation in-plane

±45˚

Rotation out-of-plane

Yaw: ±45˚ / Pitch: ±45˚

Min object width

62 pixels

GFlops

0.094

MParams

2.138

Source framework

Caffe*

Accuracy

Metric

Value

Avg. age error

6.99 years

Gender accuracy

95.80%

Inputs

Image, name: data, shape: 1, 3, 62, 62 in 1, C, H, W format, where:

  • C - number of channels

  • H - image height

  • W - image width

Expected color order is BGR.

Outputs

  1. Name: fc3_a, shape: 1, 1, 1, 1 - Estimated age divided by 100.

  2. Name: prob, shape: 1, 2, 1, 1 - Softmax output across 2 type classes [0 - female, 1 - male].

Demo usage

The model can be used in the following demos provided by the Open Model Zoo to show its capabilities:

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