Dish freshness identification method based on machine learning

Abstract

The invention relates to the field of algorithms, specifically, and particularly relates to a dish freshness identification method based on machine learning. The method comprises the following steps:acquiring multiple vegetable images, marking the freshness of each vegetable image to obtain marked vegetable images, and packaging each marked vegetable image to obtain a dataset file; building a network model to obtain a target network model; importing the data set file into the target network model to obtain a training model, deploying the training model in a server in the form of a set file,sending a target image to the server by the front-end equipment, identifying the target image according to the training model deployed in the server to obtain an identification result, and storing theidentification result in the server. Therefore, the freshness of the vegetables can be efficiently and conveniently recognized without manual screening, and the labor cost is remarkably reduced.

Description

technical field [0001] The invention relates to the field of machine learning algorithms, in particular to a method for identifying freshness of dishes based on machine learning. Background technique [0002] With the rapid development of science and technology and artificial intelligence, various smart home appliances have gradually entered people's daily life, gradually changing and optimizing people's daily life. In particular, they are very concerned about the freshness of fruits and vegetables in the farmer's market, and freshness is an important indicator of food quality. Traditional farmers' markets test the freshness of vegetables through manual screening, which significantly increases labor costs. Contents of the invention [0003] The invention provides a machine learning-based dish freshness recognition method. Firstly, obtain vegetable images, mark each vegetable image, and package it to obtain a data set file, build a network model, compile the network model, ...

AI Technical Summary

Problems solved by technology

In particular, they are very concerned about the freshness of fruits and vegetables in farmers' markets, and freshness is an important indicator of food quality. Traditional farmers' markets test the freshness of vegetables through manual screening, which significantly increases labor costs.

Images