Image processing method, device, storage medium and camera

A non-transitory computer-readable storage medium on which a computer program is stored, wherein an image processing method is carried out when the program is executed by a processor;

• wherein the method comprises:
• capturing a target image;
• acquiring a target feature map of the target image through a preset target convolution layer, wherein the target convolution layer includes at least one of a plurality of convolution layers of a convolutional neural network (CNN);
• and
• outputting the target feature map;
• wherein the target convolution layer is determined in the following ways:
• acquiring a data volume of a feature map output by each of the plurality of convolution layers of the CNN, and determining the target convolution layer among the plurality of convolution layers based on the data volume;
• or
• obtaining a configuration information of the camera, and determining the target convolution layer among the plurality of convolution layers of the CNN according to the configuration information;
• wherein the configuration information comprises a first memory space corresponding to the camera, and the determining the target convolution layer among the plurality of convolution layers of the CNN according to the configuration information comprises:
• obtaining a second memory space required by each of the plurality of convolution layers;
• and
• obtaining a first sum value of the second memory space from a first convolution layer to a Nth convolution layer among the plurality of convolution layers, wherein if the first sum value is less than or equal to the first memory space and a second sum value of the second memory space from the first convolution layer to a N+1th convolution layer is greater than the first memory space, the Nth convolution layer and the previous convolution layer(s) of the Nth convolution layer among the plurality of convolution layers are used as the target convolution layers, where N is the integer greater than 0.

A camera, comprising:

• a memory on which a computer program is stored;
• and
• a processor configured to execute the computer program in the memory to carry out an image processing method comprising:
• capturing a target image;
• acquiring a target feature map of the target image through a preset target convolution layer, wherein the target convolution layer includes at least one of a plurality of convolution layers of a convolutional neural network (CNN);
• and
• outputting the target feature map;
• wherein the target convolution layer is determined in the following ways:
• acquiring a data volume of a feature map output by each of the plurality of convolution layers of the CNN, and determining the target convolution layer among the plurality of convolution layers based on the data volume;
• or
• obtaining a configuration information of the camera, and determining the target convolution layer among the plurality of convolution layers of the CNN according to the configuration information;
• wherein the configuration information comprises a first memory space corresponding to the camera, and the determining the target convolution layer among the plurality of convolution layers of the CNN according to the configuration information comprises:
• obtaining a second memory space required by each of the plurality of convolution layers;
• and
• obtaining a first sum value of the second memory space from a first convolution layer to a Nth convolution layer among the plurality of convolution layers, wherein if the first sum value is less than or equal to the first memory space and a second sum value of the second memory space from the first convolution layer to a N+1th convolution layer is greater than the first memory space, the Nth convolution layer and the previous convolution layer(s) of the Nth convolution layer among the plurality of convolution layers are used as the target convolution layers, where N is the integer greater than 0.