Target detection method and device and computer readable storage medium

Abstract

The invention discloses a target detection method which comprises the following steps of: acquiring a to-be-detected image, wherein the to-be-detected image is subjected to multi-layer convolution extraction of features in a neural network to generate a feature map; loading modified structural parameters in a neural network model, and generating corresponding anchor box coordinates on the basis ofthe structural parameters, wherein the preset structural parameters comprise a reference dimension of an anchor box, an anchor box scale and a length-width ratio of the anchor box; generating candidate box coordinates on the basis of a region nomination subnet, taking a corresponding region on the feature map according to the candidate coordinates, and by pooling of a ROI (Region Of Interest), obtaining corresponding features; and on the basis of the features, determining prediction box coordinates, and on the basis of the prediction box coordinates, determining a target object position. Theinvention further discloses a target detection device and a computer readable storage medium. According to the invention, a case of generating an optimized prediction box to determine a target objectis implemented, a small target can be detected, and a detection rate for the target is improved.

Description

technical field [0001] The present invention relates to the technical field of image detection, in particular to a target detection method, device and computer-readable storage medium. Background technique [0002] The detection of targets in images is widely used in various fields. For example, in the field of automatic driving, the detection of traffic signs in images is a very important link. Identify and guide the driving of vehicles to ensure driving safety. [0003] At present, when detecting a small target in an image, because the feature information obtained by the feature extractor in the feature map is very small, it means that it is difficult to locate and classify. For example, the detector detects small objects like traffic signs. Therefore, the current target detection methods are difficult to detect small targets. [0004] The above content is only used to assist in understanding the technical solution of the present invention, and does not mean that the abo...

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Problems solved by technology

[0003] At present, when detecting a small target in an image, because the feature information obtained by the feature extractor in the feature map is very small, it means that it is difficult to locate and classify. For example, the detector detects small objects like traffic signs. It is very difficult to target, so the current target detection method is difficult to detect small targets

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