Method, apparatus, and storage medium for identifying identification code

A apparatus for identifying an identification code, the apparatus comprising:

• a memory storing instructions;
• and
• a processor in communication with the memory, wherein, when the processor executes the instructions, the processor is configured to cause the apparatus to perform operations comprising:
• obtaining a to-be-detected picture,
• detecting an identification code in the to-be-detected picture to obtain a detection result comprising target information of a target code corresponding to the identification code by:
• detecting the identification code in the to-be-detected picture through a first neural network model, to obtain the detection result, an intersection-over-union ratio between the target code and the identification code being greater than a preset value, and the identification code corresponding to a positive sample used in a training process of the first neural network model,
• sampling the target code according to the target information, to obtain a sampled image comprising:
• in response to the target code satisfying a resolution condition, upsampling the target code based on an image super-resolution reconstruction technology and through a second neural network model, to obtain the sampled image, wherein a weight corresponding to an edge region of the target code in a hidden layer of the second neural network model is adjusted to be greater than a preset value, and
• decoding the sampled image, to obtain an identification result corresponding to the identification code.

A non-transitory computer readable storage medium storing computer readable instructions, wherein, the computer readable instructions, when executed by a processor, are configured to cause the processor to perform operations comprising:

• obtaining a to-be-detected picture;
• detecting an identification code in the to-be-detected picture to obtain a detection result comprising target information of a target code corresponding to the identification code by:
• detecting the identification code in the to-be-detected picture through a first neural network model, to obtain the detection result, an intersection-over-union ratio between the target code and the identification code being greater than a preset value, and the identification code corresponding to a positive sample used in a training process of the first neural network model;
• sampling the target code according to the target information, to obtain a sampled image comprising:
• in response to the target code satisfying a resolution condition, upsampling the target code based on an image super-resolution reconstruction technology and through a second neural network model, to obtain the sampled image, wherein a weight corresponding to an edge region of the target code in a hidden layer of the second neural network model is adjusted to be greater than a preset value;
• and
• decoding the sampled image, to obtain an identification result corresponding to the identification code.