Intelligent man-machine interaction innumerable network control module

Abstract

The invention discloses an intelligent man-machine interaction infinite network control module which comprises a mobile computing equipment hardware layer, a Flask rear end, an internal API, a processcontrol module, a video and audio output module, a GPIO control module, an HTML template rendering module and peripheral equipment. During use, peripheral equipment is connected to the GPIO control module and the video and audio output module; the equipment is connected to a network, an administrator user is connected with the same local area network through an external computer to enter a configuration interface of the device, the operation process of Internet of Things control is visually completed by dragging a corresponding module, the configuration process is simple and rapid, intelligent automation is achieved, and the processing complexity of Internet of Things device access is reduced; the full life cycle of the Internet of Things data from generation to recovery is realized, quick access of household Internet of Things equipment is facilitated, the summary efficiency of different Internet of Things data can be improved, and the environmental protection benefit is obvious.

Description

technical field [0001] The invention belongs to the field of computer technology, and relates to an image-based object detection technology, in particular to an intelligent human-computer interaction infinite network control module. Background technique [0002] Computer vision-based target recognition technology refers to the technology of using computers to process, analyze and understand images to identify targets and objects in various patterns. It is a practical application of deep learning algorithms. At this stage, image recognition technology is generally divided into face recognition and commodity recognition. Face recognition is mainly used in security inspection, identity verification and mobile payment; commodity recognition is mainly used in the process of commodity circulation, especially unmanned shelves, smart retail cabinets, etc. Unmanned retail area. [0003] The traditional image recognition process is divided into four steps: image acquisition→image pre...

AI Technical Summary

Problems solved by technology

One of the shortcomings of modern image recognition technology is poor adaptive performance. Once the target image is polluted by strong noise or the target image has a large defect, ideal results are often not obtained.

Images