Method and apparatus for detecting image type

An apparatus for detecting an image type, the apparatus comprising:

• at least one processor;
• a zoom lens assembly, the zoom length lens assembly being used to collect images at different focal lengths, and
• a memory storing instructions, the instructions when executed by the at least one processor, cause the at least one processor to perform operations, the operations comprising:
• acquiring a first to-be-processed image and a second to-be-processed image, wherein the first to-be-processed image and the second to-be-processed image are captured by the zoom lens assembly installed in a terminal device when a positional relationship between said terminal device and a given object being captured is unchanged, and focal lengths of said zoom lens assembly when capturing the first to-be-processed image and the second to-be-processed image are different;
• determining at least one first object image and at least one second object image in the first to-be-processed image and the second to-be-processed image respectively;
• and
• for each first object image in the at least one first object image, importing the first object image and a second object image corresponding to the first object image into an image type detection model to obtain an image type corresponding to the first object image and the second object image, the image type detection model being obtained through training by using a machine learning method and being used to determine an image type by depth of field information, and the image type comprising a plane image and a stereo image.

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

• acquiring a first to-be-processed image and a second to-be-processed image, wherein the first to-be-processed image and the second to-be-processed image are captured by a zoom lens assembly installed in a terminal device when a positional relationship between said terminal device and a given object being captured is unchanged, and focal lengths of said zoom lens assembly when capturing the first to-be-processed image and the second to-be-processed image are different;
• determining at least one first object image and at least one second object image in the first to-be-processed image and the second to-be-processed image respectively;
• and
• for each first object image in the at least one first object image, importing the first object image and a second object image corresponding to the first object image into an image type detection model to obtain an image type corresponding to the first object image and the second object image, the image type detection model being obtained through training by using a machine learning method and being used to determine an image type by depth of field information, and the image type comprising a plane image and a stereo image.