Steel defect automatic claim settlement method based on deep learning and electronic equipment

The invention relates to a steel defect automatic claim settlement method based on deep learning and electronic equipment, and the method comprises the following steps: receiving data uploaded by a user, the data uploaded by the user comprising an objection product picture and product order data; obtaining product defect data based on the objection product picture and a pre-constructed defect category identification model; performing data preprocessing on the product defect data and the product order data to obtain to-be-processed data; taking the to-be-processed data as input of a pre-constructed claim settlement model, and obtaining a corresponding claim settlement amount; wherein the defect category identification model is constructed based on a deep learning yov5 model, and the claim settlement model is constructed based on an SVR model. Compared with the prior art, the method has the advantages of high treatment efficiency, reduced labor cost and the like. 本发明涉及一种基于深度学习的钢材缺陷自动理赔方法及电子设备，所述方法包括以下步骤：接收用户上传数