FIELD: computing equipment for image processing.
SUBSTANCE: computerized method of training, involving the following operations: obtaining access to image data; machine learning algorithm is used, to obtain machine annotations of objects in one or more scales of said image; generating a viewing window configurable based on the magnification ratio; simulating manual annotation of an object at different scales and/or in different parts of each image scale; using simulated manual annotations as different training inputs into machine learning algorithm; quantifying changes in various resultant machine annotations of objects; increasing coefficient and spatial offset parameter based on identified simulated manual annotation and after receiving the input data, manual annotation of the object by the user is used as a training input to the machine learning algorithm.
EFFECT: technical result consists in improvement of annotation of objects in image due to machine learning algorithm.
20 cl, 7 dwg
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