Method and device for training supervised machine learning model

The invention discloses a method and a device for training a supervised machine learning model. The method includes the steps: generating a plurality of man-made images comprising movement states of same target objects at different time points in one or more time periods; recording annotation data related to movement of the target objects in one or more time periods in the generating process of the man-made images; generating multimedia streaming comprising movement based on the man-made images; using a plurality of frame data of the multimedia streaming as a plurality of input data of the model to execute operation in the model and acquire derivation data related to movement; comparing the derivation data with the annotation data to determine whether to adjust parameters of the model or not. By the method, a large quantity of manual annotation needed in the training process of the model can be omitted. 公开了种用于训练有监督机器学习的模型的方法和装置。该方法包括：生成多个人造图像，每个人造图像包含相同的目标对象在个或多个时间段内的不同时间点的运动状态；在生成多个人造图像的过程中记录与目标对象在个或多个时间段内的运