Method and apparatus for training face recognition model

An apparatus for training a face recognition model, comprising:

• a memory, and
• a processor coupled to the memory and the processor is to:
• remove black eyepits and sunglasses in first actual scenario data composed of an image containing a face which is acquired from an actual scenario, to obtain second actual scenario data;
• count a proportion wearing glasses in the second actual scenario data;
• divide original training data composed of an image containing a face into wearing-glasses first training data and not-wearing-glasses second training data, where the proportion of wearing glasses in the original training data is lower than the proportion of wearing glasses in the second actual scenario data;
• generate wearing-glasses third training data based on glasses data and the second training data;
• generate fourth training data in which the proportion of wearing glasses is equal to the proportion of wearing glasses in the second actual scenario data, based on the third training data and the original training data;
• and
• train the face recognition model based on the fourth training data.

A non-transitory computer-readable storage medium storing thereon a program that, when executed by an information processing apparatus, causes the information processing apparatus to execute the operations of:

• removing black eyepits and sunglasses in first actual scenario data composed of an image containing a face which is acquired from an actual scenario, to obtain second actual scenario data;
• counting a proportion of wearing glasses in the second actual scenario data;
• dividing original training data composed of an image containing a face into wearing-glasses first training data and not-wearing-glasses second training data, where the proportion of wearing glasses in the original training data is lower than the proportion of wearing glasses in the second actual scenario data;
• generating wearing-glasses third training data based on glasses data and the second training data;
• generating fourth training data in which a proportion of wearing glasses is equal to the proportion of wearing glasses in the second actual scenario data, based on the third training data and the original training data;
• and
• training the face recognition model based on the fourth training data.