Dish-ID:一种基于神经的成分提取和进一步配方建议方法

Ilya Shchuka, Saydash Miftakhov, Vladislav Patrushev, M. Tikhonova, Alena Fenogenova
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引用次数: 2

摘要

本文提出了一种俄文餐食识别、配料提取和配方建议的方法。该算法由几个连续的阶段组成。在第一阶段,模型从菜肴的照片中提取配料列表,并以此为基础选择第二阶段的食谱。第一阶段测试了两种成分提取体系,提出了三种配方建议的配方匹配方法。此外,该算法还被应用到电报机器人中,提供了友好的用户体验。源代码在https://github.com/Alenushldish_id_sirius。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dish-ID: A neural-based method for ingredient extraction and further recipe suggestion
The paper presents a method for meal recognition, ingredient extraction and recipe suggestion in the Russian language. The proposed algorithm consists of several consecutive stages. On the first stage the model extracts a list of ingredients from a photo of the dish, based on which recipes on the second stage are selected. Two ingredient extraction architectures were tested for the first stage and three recipe matching methods for recipe suggestion are proposed. In addition, the algorithm was incorporated into the telegram-bot which provides friendly user experience. Source code is at https://github.com/Alenushldish_id_sirius.
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