Face detection based on Yolov5

Abstract

Face recognition technology is one of the popular research directions in computer vision in recent years, which is widely used in our daily life. Therefore, this paper takes the Yolov5 algorithm as the core, introduces the COCO dataset, and at the same time introduces the Yolov5 system structure and analyzes the algorithm in terms of implementation and performance. Experiments are conducted on the detection of two targets with different genders, and by changing three different hyperparameters (number of training rounds, batch size and image size), we observe the influence of the change of different hyperparameters on the experimental effect and derive the suitable size of different hyperparameters