Animal face key point marking method

Abstract

The invention discloses an animal face key point marking method. The method includes the steps of detecting an animal face of an input sample image to obtain an animal face contour and the positions of animal face key points, processing the input sample image according to the animal face contour and the positions of the animal face key points, sending the processed sample image into a pre-trainedkey point prediction network to obtain a first key point prediction result, adjusting the first key point prediction result to obtain marked points of the animal face key points, and conducting quality detecting on the marked points according to a pre-defined standard image to obtain the quality score of the marked points. By means of the technical scheme, the animal face key points can be precisely marked, the marked points can be automatically checked, and therefore the marking precision is improved and the work efficiency is greatly improved.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a method for labeling key points of animal faces. Background technique [0002] In recent years, selfie beauty makeup has received more and more attention, and the demand for cute pet beauty makeup has also emerged. Just as human face beauty makeup relies on the precise positioning of facial key points, cute pet beauty makeup also has a strong dependence on animal facial key points. At present, there are relatively few algorithms for locating animal facial key points in both academic circles and industrial circles. The reason may be that compared with human face key points, there are fewer labeled samples of animal facial key points and the lack of public evaluation databases. The research on animal facial key point positioning algorithm largely depends on the labeling of animal facial key points. By marking the key points of animal face, a training sample of animal fac...

AI Technical Summary

Problems solved by technology

[0003] At present, the key point labeling system for animal faces follows the human face key point labeling system, which includes the following modules: face detection module, key point prediction module and key point labeling module, among them, key point prediction module and key point labeling module They are two completely independent modules. The system simply imports sample pictures, and the key point labeling relies entirely on the manual operation of engineers based on experience. Therefore, the facial key point labeling of sample pictures will not be very accurate, resulting in Many invalid labeled samples, and these invalid labeled samples are not helpful to improve the performance of the key point positioning algorithm

In addition, after the manual labeling is completed, it is necessary to manually review all the labeled samples, which is also a very time-consuming and labor-intensive process, which is not conducive to the improvement of work efficiency

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