Food-Recipe-CNN:使用深度卷积神经网络将食物图像转化为食谱-源码

上传者: 42129005 | 上传时间: 2021-09-20 12:35:20 | 文件大小: 199.37MB | 文件类型: ZIP
用于烹饪食谱检索的深度学习食物图像识别系统 演示:DeepChef 总览 更新:博客文章现已发布。 有关更多信息,请访问! 例如用法,请访问此Jupyter Notebook: Maturaarbeit 2018:这项工作利用Keras的深度卷积神经网络将图像分类为230种食物并输出匹配的食谱。 数据集包含来自chefkoch.de的> 400'000食物图像和> 300'000食谱。 几乎没有任何其他领域能像营养一样对人类福祉产生类似的影响。 每天,用户都会在社交网络上发布无数的食物图片; 从第一个自制蛋糕到顶级米其林菜肴,万一菜肴成功,您将与世界分享快乐。 事实是,无论彼此之间有多大差异,美食都会受到大家的赞赏。 个别烹饪原料的分类或对象识别方面的进展很少。 问题在于几乎没有公开编辑的记录。 处理 该代码(Jupyter笔记本)提供了许多德语注释。 该过程如下所示: 1│──数据准备│└──清除数据│└──数据扩充 2│──数据分析和可视化,拆分数据(训练,有效,测试) 3│──使用简单ML模型的首次尝试│└──最近邻分类器(kNN) │└──k-均值聚类│└──支持向量机

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