Method and device for detecting stacking degree of express cargos

Abstract

The invention provides a method and device for detecting the stacking degree of express cargos. The method comprises the steps: obtaining a cargo stacking image of a target station, taking the cargo stacking image as a prediction sample, inputting the prediction sample into a preset deep learning detection model, and using output of the deep learning detection model as a stacking degree detectionresult corresponding to the cargo stacking image of the target station, wherein the deep learning detection model is used for representing the corresponding relationship between the stacking type of the cargo stacking image and the stacking degree detection result. The detection algorithm is based on the principle of deep learning, can achieve automatic detection of the stacking degree of expresscargos, is efficient in detection process, and is accurate in detection result; and further a manager is helped to know the stacking condition of each cargo stacking region of a current express dispatching center in real time, and corresponding measures can be taken in time in a targeted manner.

Description

technical field [0001] The invention relates to the field of express sorting, and more specifically, to a method and device for detecting the accumulation degree of express goods. Background technique [0002] After the express goods are sorted by the rough sorting line and the terminal sorting line in the express distribution center, they need to be loaded and sent to the corresponding direction. However, in many cases, the goods have been sorted, but the vehicle has not yet arrived, so the goods need to be temporarily placed in the stacking area. Since the stacking area has an upper limit for stacking, when the stacking area is full of express goods but the vehicle has not arrived, it will have a great impact on the loading site, so on-site management personnel are required to intervene. [0003] There are additional timeliness requirements for the storage area of ​​the site, that is, all the goods in this area need to be loaded and delivered before a certain time point t...

AI Technical Summary

Problems solved by technology

[0004] However, since each express delivery distribution center has a large number of cargo accumulation areas, it is difficult for on-site management personnel to sense the extent of cargo accumulation in each area in real time and make effective processing in advance. Aging has a greater impact

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