Training data creation apparatus, method, and program, machine learning apparatus and method, learning model, and image processing apparatus

A training data creation method for creating training data for machine learning by a first processor performing processing comprising:

• a step of acquiring, as a single training sample, a single image and a plurality of first ground-truth region masks for the single image;
• a step of generating a single second ground-truth region mask from the plurality of first ground-truth region masks;
• a step of outputting, as training data, a pair of the single image and the single second ground-truth region mask;
• a step of calculating a sample weighting such that the higher a degree of disagreement among the plurality of first ground-truth region masks is, the smaller the sample weighting of the training sample during machine learning is, wherein
• the pair of the single image and the single second ground-truth region mask together with the calculated sample weighting are outputted as training data.

A non-transitory, computer-readable tangible recording medium which records thereon a training data creation program for causing, when read by a computer, the computer to achieve:

• a function of acquiring, as a single training sample, a single image and a plurality of first ground-truth region masks for the single image;
• a function of generating a single second ground-truth region mask from the plurality of first ground-truth region masks;
• a function of outputting, as training data, a pair of the single image and the single second ground-truth region mask;
• a function of calculating a sample weighting such that the higher a degree of disagreement among the plurality of first ground-truth region masks is, the smaller the sample weighting of the training sample during machine learning is, and
• a function of outputting, as training data, the pair of the single image and the single second ground-truth region mask together with the calculated sample weighting.