{"id":2483,"date":"2021-09-03T09:00:31","date_gmt":"2021-09-03T01:00:31","guid":{"rendered":"https:\/\/blog.ailia.ai\/uncategorized\/agegenderrecognitionretail-machine-learning-model-for-age-and-gender-identification\/"},"modified":"2025-05-20T16:18:45","modified_gmt":"2025-05-20T08:18:45","slug":"agegenderrecognitionretail-machine-learning-model-for-age-and-gender-identification","status":"publish","type":"post","link":"https:\/\/blog.ailia.ai\/en\/tips-en\/agegenderrecognitionretail-machine-learning-model-for-age-and-gender-identification\/","title":{"rendered":"AgeGenderRecognitionRetail : A Machine Learning Model to Identify Age and Gender"},"content":{"rendered":"\n

Overview<\/strong><\/h3>\n\n\n\n

AgeGenderRecognitionRetail\u00a0<\/em>is a machine learning model developed by\u00a0Intel\u00a0<\/em>to identify the age and gender of a person from a single picture.<\/p>\n\n\n\n

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Source: https:\/\/pixabay.com\/ja\/videos\/%E3%82%AB%E3%83%83%E3%83%97%E3%83%AB-%E8%8B%A5%E3%81%84%E3%81%A7%E3%81%99-%E9%9B%BB%E8%A9%B1-50020\/<\/a><\/figcaption><\/figure>\n\n\n\n

<\/a><\/p>\n\n\n\n

open_model_zoo\/models\/intel\/age-gender-recognition-retail-0013<\/a><\/p>\n\n\n\n

Architecture<\/strong><\/h3>\n\n\n\n

AgeGenderRecognitionRetail\u00a0<\/em>takes a 62×62 face image as input, and outputs the gender and age. The gender is output as a two-dimensional probability vector, and the age as a number.<\/p>\n\n\n\n

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Source: https:\/\/github.com\/openvinotoolkit\/open_model_zoo\/tree\/master\/models\/intel\/age-gender-recognition-retail-0013<\/a><\/figcaption><\/figure>\n\n\n\n

The age is output as a value between 0 and 1.0 which has to be multiplied by 100 to compute the age.<\/p>\n\n\n\n

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Source: https:\/\/github.com\/openvinotoolkit\/open_model_zoo\/blob\/master\/demos\/interactive_face_detection_demo\/cpp\/detectors.cpp<\/a><\/figcaption><\/figure>\n\n\n\n

The model architecture is a simple CNN. Caffe was used for training.<\/p>\n\n\n\n

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AgeGenderRecognitionRetail<\/em> was trained using Intel\u2019s internal dataset made of 20,000 images. This model is capable of recognizing ages from 18 to 75 years old. A person under the age of 18 cannot be accurately estimated since the dataset did not contain images of children.<\/p>\n\n\n\n

Faces facing the camera with an angle up to 45 degrees are supported. Since the accuracy is higher with faces facing the camera, it is desirable to use a face orientation detection model such as HopeNet<\/em><\/a>.<\/p>\n\n\n\n

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Source: https:\/\/github.com\/openvinotoolkit\/open_model_zoo\/tree\/master\/models\/intel\/age-gender-recognition-retail-0013<\/a><\/figcaption><\/figure>\n\n\n\n

The average error for the age estimation is 6.99 years, and the accuracy of the gender estimation is 95.80%.<\/p>\n\n\n\n

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Source: https:\/\/github.com\/openvinotoolkit\/open_model_zoo\/tree\/master\/models\/intel\/age-gender-recognition-retail-0013<\/a><\/figcaption><\/figure>\n\n\n\n

In the official demo application, when the model is applied to videos, the tracking of faces is smoothed over multiple frames. Age is updated by 5%, and gender is calculated by summing the probability values.<\/p>\n\n\n\n

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Source: https:\/\/github.com\/openvinotoolkit\/open_model_zoo\/blob\/master\/demos\/interactive_face_detection_demo\/cpp\/face.cpp<\/a><\/figcaption><\/figure>\n\n\n\n

Even when the person is wearing a mask, a face properly facing the camera can be detected with a reasonable degree of accuracy.<\/p>\n\n\n\n

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Source: https:\/\/pixabay.com\/ja\/photos\/%e7%9c%8b%e8%ad%b7%e5%a9%a6-%e3%83%9e%e3%82%b9%e3%82%af%e3%82%b5%e3%83%bc%e3%82%b8%e3%82%ab%e3%83%ab%e3%83%9e%e3%82%b9%e3%82%af-4962034\/<\/a><\/figcaption><\/figure>\n\n\n\n

Usage<\/strong><\/h3>\n\n\n\n

AgeGenderRecognitionRetail can be used with ailia SDK on the webcam video stream with the following command.<\/p>\n\n\n\n

$ python3 age-gender-recognition-retail.py -v 0<\/code><\/p>\n\n\n\n

<\/a>ailia-models\/face_recognition\/age-gender-recognition-retail<\/a><\/p>\n\n\n\n

Use the following command to estimate the age after face recognition if performed for images in a specific folder.<\/p>\n\n\n\n

$ python3 age-gender-recognition-retail.py -i faces -d<\/code><\/p>\n\n\n\n

Here is an output example.<\/p>\n\n\n\n

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