Method and apparatus for detecting object in image, and storage medium thereof

An apparatus for detecting an object in an image, comprising:

• a memory operable to store program code;
• and
• a processor operable to read the program code and configured to:
• obtain a detection image, an n-level deep feature map framework, and an m-level non-deep feature map framework, n being an integer greater than or equal to 2, m being an integer greater than or equal to 1, and the n-level deep feature map framework and the m-level non-deep feature map framework comprising a feature size and a feature dimension;
• extract, based on a deep feature extraction model, deep feature from an (i−1)-level feature of the detection image using an i-level deep feature map framework, to obtain an i-level feature of the detection image, i being a positive integer less than or equal to n;
• extract, based on a non-deep feature extraction model, non-deep feature from a (j−1+n)-level feature of the detection image using a j-level non-deep feature map framework, to obtain a (j+n)-level feature of the detection image, j being a positive integer less than or equal to m;
• and
• perform, based on a feature prediction model, an information regression operation on an a-level feature to an (m+n)-level feature of the detection image, to obtain an object type information and an object position information of an object in the detection image, a being an integer less than n and greater than or equal to 2.

A non-transitory machine-readable media, having processor executable instructions stored thereon for causing a processor to:

• obtain a detection image, an n-level deep feature map framework, and an m-level non-deep feature map framework, n being an integer greater than or equal to 2, m being an integer greater than or equal to 1, and the n-level deep feature map framework and the m-level non-deep feature map framework comprising a feature size and a feature dimension;
• extract, based on a deep feature extraction model, deep feature from an (i−1)-level feature of the detection image using an i-level deep feature map framework, to obtain an i-level feature of the detection image, i being a positive integer less than or equal to n;
• extract, based on a non-deep feature extraction model, non-deep feature from a (j−1+n)-level feature of the detection image using a j-level non-deep feature map framework, to obtain a (j+n)-level feature of the detection image, j being a positive integer less than or equal to m;
• and
• perform, based on a feature prediction model, an information regression operation on an a-level feature to an (m+n)-level feature of the detection image, to obtain an object type information and an object position information of an object in the detection image, a being an integer less than n and greater than or equal to 2.