Abstract: The present application provides a model training, image processing method, device, storage medium, and program product relating to deep learning technology, which are able to screen auxiliary image data with image data for learning a target task, and further fuse the target image data and the auxiliary image data, so as to train a built and to-be-trained model with the fusion-processed fused image data. This implementation can increase the amount of data for training the model, and the data for training the model is determined is based on the target image data, which is suitable for learning the target task. Therefore, the solution provided by the present application can train an accurate target model even if the amount of target image data is not sufficient.

Abstract: A milk beverage heating mixer comprises a cup, a stirrer, a base, a heating plate, a temperature measurement assembly and a first lever assembly. A cavity for accommodating the cup is formed in an upper end of the base. A first radial opening and a second radial opening are formed in a cavity wall of the cavity. The heating plate is disposed at the bottom of the cavity. The first lever assembly is rotatably disposed outside the cavity, and a protrusion at a first end of the first lever assembly stretches into the cavity via the first radial opening. When accommodated in the cavity, the cup presses the protrusion and pushes the temperature measurement assembly by means of the second end of the first lever assembly to stretch into the cavity via the second radial opening to make contact with a side wall of the cup.