Method and apparatus for compression of a task output by machine learning
Disclosed herein are a method and apparatus for distributed image data processing. The method for distributed image data processing includes performing machine learning on an original image to produce a plurality of different task outputs, combining the plurality of task outputs to extract at least one final output, and compressing the final output and transmitting the final output to a server.
1 . A method for generating compressed image data, comprising:
extracting from an original image a plurality of partial regions;
generating an extracted image by combining the plurality of partial regions;
generating inference data for the plurality of partial regions; and
generating compressed image data by encoding the extracted image and the inference data for the plurality of partial regions,
wherein the inference data comprises:
position data representing a coordinate of a partial region extracted from the original image, and
size data representing a size of the partial region extracted from the original image,
wherein the position data and the size data are encoded for each of the plurality of partial regions, and
wherein a size of the extracted image is different from a size of the original image.
2 . The method of claim 1 , wherein the inference data further comprises information on whether there is a pixel in an extracted partial region.
3 . The method of claim 1 , wherein the method further comprises adjusting a spatial resolution of the extract image, the extract image with an adjusted spatial resolution being encoded to generate the compressed image data.
4 . The method of claim 1 , wherein the plurality of partial regions are extracted by performing a plurality of tasks.
5 . The method of claim 1 , wherein the plurality of partial regions are extracted by a machine learning based on a neural network.
6 . An apparatus for generating compressed image data processing, comprising:
a memory configured to store a control program for generating the compressed image data; and
a processor configured to execute the control program stored in the memory,
wherein the processor is configured to:
extract from an original image a plurality of partial regions;
generate an extracted image by combining the plurality of partial regions;
generate inference data for the plurality of partial regions; and
generate the compressed image data by encoding the extracted image and the inference data for the plurality of partial regions,
wherein the inference data comprises:
position data representing a coordinate of a partial region extracted from the original image, and
size data representing a size of the partial region extracted from the original image,
wherein the position data and the size data are encoded for each of the plurality of partial regions, and
wherein a size of the extracted image is different from a size of the original image.
7 . A method for decompressing compressed image data, comprising:
decoding an extracted image from the compressed image data, the extracted image comprising a plurality of partial regions;
obtaining inference data for the plurality of partial regions in the extracted image; and
generating an output image from the extracted image,
wherein the inference data comprises:
position data representing a coordinate of a partial region included in the extracted image, and
size data representing a size of the partial region included in the extracted image,
wherein the position data and the size data are obtained for each of the plurality of partial regions, and
wherein a size of the extracted image is different from a size of the output image.