Image processing method, electronic device and storage medium

A electronic device comprising a memory and a processor, the memory stores at least one computer-readable instruction, and the processor executes the at least one computer-readable instruction to:

• acquire training data in response to receiving an image processing instruction;
• train a deep learning model with the training data by using a preset deep learning framework to obtain an initial model;
• convert a data type of the initial model;
• add a correction layer to the converted initial model;
• optimize the initial model by training weights of the correction layer to obtain an image processing model;
• acquire an image from the image processing instruction;
• and
• use the image processing model to process the image and output an image processing result.

A non-transitory storage medium having stored thereon at least one computer-readable instructions that, when the at least one computer-readable instructions are executed by a processor to implement the following steps:

• acquiring training data in response to receiving an image processing instruction;
• training a deep learning model with the training data by using a preset deep learning framework to obtain an initial model;
• converting a data type of the initial model;
• adding a correction layer to the converted initial model;
• optimizing the initial model by training weights of the correction layer to obtain an image processing model;
• acquiring an image from the image processing instruction;
• and
• using the image processing model to process the image and output an image processing result.