Training method of target detection model for multi-category junk scene recognition

Abstract

The invention provides a training method of a target detection model for multi-category junk scene recognition. The training method comprises the following steps: constructing a basic target detection model; in the p convolution layers, selecting m continuous convolution layers, and replacing each selected convolution layer by a cavity convolution; sequentially setting the void ratios of the m hole convolutions to meet the condition that the largest common divisor of the void ratios of any two adjacent hole convolutions is 1 so as to obtain an optimized target detection model; and training the optimized target detection model by using the sample image training set to obtain a target detection model for multi-category junk scene recognition. According to the invention, the problem of low garbage target detection precision of a scene image with a wide visual field due to a small receptive field range of a target detection model in the prior art is solved, the scene image is used as a model input for garbage recognition detection, and the obtained detection result often has the phenomenon of invalid multi-point garbage identification or false alarm of garbage detection.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a training method for a target detection model used for multi-category garbage scene recognition. Background technique [0002] Target detection is an image understanding algorithm based on the geometric and statistical characteristics of the target. Target detection combines the positioning and recognition of target objects. For example, based on computer vision algorithms, the image is detected by using the target detection model obtained through machine learning. Different categories of target objects in the target object, that is, the position of the target is marked with a rectangular frame, and the category of the target object is identified. [0003] Target detection is widely used in garbage recognition and classification. In related technologies, the target detection model can only recognize a limited number of garbage types due to a small amount of artificial c...

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Problems solved by technology

[0004] The main purpose of the present invention is to provide a training method for a target detection model for multi-category garbage scene recognition, to solve the problem that the target detection model in the prior art has a small receptive field range, so that there is garbage in the scene

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