Non-RGB GAN RGB Non-RGB LEARNING METHOD AND LEARNING DEVICE FOR STRATEGIC TRANSFORMING RGB TRAINING IMAGE SETS INTO NON-RGB TRAINING IMAGE SETS TO BE USED FOR LEARNING OBJECT DETECTION ON OBJECTS OF IMAGES IN NON-RGB FORMAT BY USING CYCLE GAN RESULTING IN SIGNIFICANTLY REDUCING COMPUTATIONAL LOAD AND REUSING DATA

摘要

The present invention is a learning method and a learning apparatus for converting an RGB training image set into a Non-RGB training image set using a cycle GAN so that it can be used for object detection learning on an object of an image having a Non-RGB format, and It relates to a test method and a test apparatus used. More specifically, in a learning method for converting an RGB image tagged with at least one correct answer information into a non-RGB image tagged with at least one correct answer information using a cycle GAN (Cycle Generative Adversarial Network), (a ) When the learning device acquires at least one first image having an RGB format, the first transformer causes the first transformer to convert the first image into at least one second image having a Non-RGB format, and the first disk The limiter generates a result (1_1) by checking whether the second image is an image having a primary Non-RGB format or an image having a secondary Non-RGB format. The head Non-RGB format is a Non-RGB format that has not undergone conversion from the RGB format, and the secondary Non-RGB format is characterized in that it is a Non-RGB format that has undergone conversion from the RGB format, and allows a second transformer, Converting the second image into at least one third image having the RGB format; (b) When the learning device acquires at least one fourth image having the Non-RGB format, the second transformer causes the fourth image to be converted into at least one fifth image having the RGB format. And the second discreminator to generate a (2_1) result by checking whether the fifth image is an image having a primary RGB format or an image having a secondary RGB format, wherein the primary RGB format is It is an RGB format that has not undergone conversion from the Non-RGB format, and the secondary RGB format is an RGB format that has undergone conversion from the Non-RGB format, and the first transformer causes the fifth image to be converted to the Non-RGB format. -Converting to at least one sixth image having an RGB format; And (c) the learning device includes the first image, the second image, the third image, the fourth image, the fifth image, the sixth image, the (1_1) result, and the (2_1) ) Calculating one or more losses with reference to at least some of the results, and learning at least some of the parameters of the first transformer, the second transformer, the first disc limiter, and the second disc limiter; It relates to a learning method and a learning device comprising the, and a test method and a test device using the same.