Image processing device generating dot data using machine learning model and method for training machine learning model

Abstract

In an image processing device, a controller performs: acquiring target image data representing a target image; inputting first and second datasets into a machine learning model and causing the machine learning model to output first and second partial dot data; and generating dot data specifying a dot formation state for each of a plurality of pixels in a print image corresponding to the target image using the first and second partial dot data. The first dataset includes first partial image data and a first value for an input parameter. The second dataset includes second partial image data and a second value for the input parameter. The machine learning model outputs the second partial dot data different from the first partial dot data according to the second value being different from the first value even when the second partial image data is identical to the first partial image data.