An evaluation method of kitchen dirty and disorder based on density estimation

Abstract

The present invention proposes a method for evaluating messiness in the kitchen based on density estimation, which includes the following steps: step S1, collect the video of the kitchen, and extract the image X of the kitchen from its corresponding video frame; In the image X, the dirty and messy areas in the image are marked to form a label frame with a size within the preset range, and the dirty and messy situation is scored; step S3, according to the distribution of the label frame and the label to construct the kitchen image X Dirty and messy density map M of the same size; size processing and normalization of multiple dirty and messy density maps M; step S4, image data construction and training of kitchen image X and messy density map M for dirty and messy evaluation Algorithmic neural network; step S5, using the neural network to evaluate the degree of mess in the kitchen in the video image; the present invention automatically scores the dirty and messy situation of the scene through the convolutional neural network, and uses the dirty and messy density map at the same time Marking the specific location of the mess will help businesses improve the kitchen environment.

Description

technical field [0001] The invention relates to the technical field of image analysis, in particular to a density estimation-based method for evaluating kitchen mess. Background technique [0002] In the 2018 notice issued by the State Administration of Market Regulation on the issuance of guidance on the work of bright kitchens and bright stoves in catering services (Guoshi Jianshijian No. 2 [2018] No. 32), in order to supervise catering service providers, strengthen food safety management, and standardize the processing process, To promote social co-governance of food safety in catering services, according to the relevant provisions of the "Food Safety Law of the People's Republic of China", the State Administration for Market Regulation has formulated the "Guiding Opinions on the Work of Bright Kitchens and Stoves in Catering Services". As an important item in the bright kitchen, the evaluation and evaluation of the mess in the back kitchen is the current focus of the Mar...

AI Technical Summary

Problems solved by technology

[0004] 1. Floor stains

[0005] 2. Oil stains (stains) on the wall

[0006] 3. Damaged walls and floors

[0007] 4. Ground debris food residue

[0008] 5. Complex debris on the ground

[0009] 6. Desktop chaos

There is also a data-based heat map generation method, but compared to the messy kitchen, there is not so much data for image drawing

Images