VEHICLE LOSS DETECTION MODEL TRAINING METHOD AND APPARATUS, VEHICLE LOSS DETECTION METHOD AND APPARATUS, AND DEVICE AND MEDIUM

摘要

A vehicle loss detection model training method and apparatus, a vehicle loss detection method and apparatus, and a device and a medium, related to the field of classification models of artificial intelligence. The method comprises: inputting a vehicle loss sample set containing vehicle loss sample images into a vehicle loss detection model for training, extracting loss texture features by the vehicle loss detection model based on an InceptionV4 model architecture, and obtaining at least one prediction resu obtaining the identification result by using a GIOU method and a soft-NMS algorithm; determining a first loss value according to a GIOU loss algorithm, and determining a second loss value by using a multi-classification cross entropy method; determining a total loss value according to the first loss value and the second loss value; and when the total loss value does not reach a preset convergence condition, iteratively updating initial parameters of the vehicle loss detection model until the total loss value reaches the preset convergence condition, and recording the converged vehicle loss detection model as a trained vehicle loss detection model. According to the method, the vehicle loss type and the vehicle loss area can be quickly identified.