Second-hand commercial vehicle condition detection method based on improved Faster RCNN prediction model

Abstract

The invention discloses a second-hand commercial vehicle condition detection method based on an improved Faster RCNN prediction model, and the method comprises the steps: collecting an image of a to-be-detected part of a second-hand commercial vehicle, and dividing the image of the to-be-detected part into a training set and a test set according to a proportion; using an image marking tool to mark the category and the position coordinate of an accident point in the training set; and naming the training set as an image file in a preset format, scaling the image file in the preset format into a preset size suitable for network training through a bilinear interpolation method, and then performing data enhancement operation on the image file to obtain a preprocessed image. The method has the advantages that the deep learning technology and the image processing technology are combined, the accident point on the second-hand commercial vehicle in the complex scene is detected and recognized through the deep learning method, and the detection speed and precision are improved. The network structure and the training mode of the Faster RCNN prediction model are improved, the optimization algorithm and the data augmentation method are improved, and the detection effect is improved.

Description

technical field [0001] The invention relates to the technical field of used vehicle detection, in particular to a method for detecting the condition of a used commercial vehicle based on an improved Faster RCNN prediction model. Background technique [0002] The replacement of second-hand cars is the premise and key to promoting new car sales. Its transaction volume is increasing year by year, especially the proportion of second-hand commercial vehicles in the entire second-hand car transaction volume is constantly expanding. However, it is undeniable that there are still many pain points in the second-hand commercial vehicle transaction market. The most obvious of these is the evaluation and detection system. The evaluation and inspection system of commercial vehicles requires complex procedures and comprehensive inspections of the cab, chassis, engine, gearbox, etc., and ordinary buyers do not have the ability to discriminate. At the same time, due to the actual use envir...

AI Technical Summary

Problems solved by technology

The evaluation and inspection system of commercial vehicles requires complex procedures and comprehensive inspections of cabs, chassis, engines, gearboxes, etc., and ordinary buyers do not have the ability to discriminate

At the same time, due to the actual use environment of the vehicle, the professional knowledge of the practitioners and the lack of professional third-party service agencies, the second-hand commercial vehicle market has never had a reasonable evaluation system or unified standards, which makes it often difficult for users to purchase second-hand commercial vehicles. Accurately judge the condition of the car, and the trust in second-hand cars continues to decrease

[0003] When buying a second-hand commercial vehicle, the buyer is most concerned about whether the second-hand commercial vehicle has experienced an accident, what accident points and accident phenomena have occurred in the accident; and the target detection method using traditional manual features to detect the second-hand commercial vehicle. Although the detection task can be completed, the manually designed features are not robust to diversity changes, and the detection and recognition effect is not ideal.

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