Open Source | Commodity Recognition Recommender System

A project I did a few months ago,整理一下,比较简单,It is based on the data set图片分类（使用resnet50）,Then pass the identification resultMatch recommendation database,进行推荐.

前端：html、js

后端：python-flask框架、pytorch框架

项目结构：

dataset_dir文件夹：Datasets are placed in this folder,Different types of pictures are placed in the corresponding types of folders,再通过

models文件夹：存放训练好的模型

static文件夹：Stores the required images displayed on the front-end web page

templates文件夹：Front-end web page template file

inference.py A file to test inference effects

label.py

from torchvision.datasets import ImageFolder

dataset=ImageFolder("C:/Users/forwhat/Desktop/recommend/cloth/train") #获取路径,All images are returneddata、label
print(dataset.class_to_idx) #View category names,及对应的标签.
print(dataset.imgs)  #See all the pictures in the path,及对应的标签

 label_level2.py

under_jeans =['https://detail.tmall.com/item.htm?id=636464038643','https://detail.tmall.com/item.htm?id=629142114736','https://item.taobao.com/item.htm?id=633482107680','https://item.taobao.com/item.htm?id=653135699650'
,'https://detail.tmall.com/item.htm?id=626092831491']
under_skirt = ['https://item.taobao.com/item.htm?id=667268983604','https://detail.tmall.com/item.htm?id=668100149427','https://detail.tmall.com/item.htm?id=586698989166','https://detail.tmall.com/item.htm?id=635332780625'
,'https://detail.tmall.com/item.htm?id=637917736279']
under_sporty = ['https://detail.tmall.com/item.htm?id=613077657236','https://detail.tmall.com/item.htm?id=580354266231','https://detail.tmall.com/item.htm?id=580354266231','https://detail.tmall.com/item.htm?id=653363447356','https://item.taobao.com/item.htm?id=579123847078'
,'https://detail.tmall.com/item.htm?id=42730275588']
under_suit = ['https://detail.tmall.com/item.htm?id=618731089852','https://detail.tmall.com/item.htm?id=618596933879','https://detail.tmall.com/item.htm?id=636256949983','https://detail.tmall.com/item.htm?id=636363512038'
,'https://item.taobao.com/item.htm?id=665038582357']
upper_casual = ['https://detail.tmall.com/item.htm?id=666855488772','https://detail.tmall.com/item.htm?id=667962767730','https://detail.tmall.com/item.htm?id=610974657070','https://detail.tmall.com/item.htm?id=645567560209'
,'https://detail.tmall.com/item.htm?id=644415535799']
upper_coat = ['https://item.taobao.com/item.htm?id=552053460493','https://item.taobao.com/item.htm?id=598306760200','https://detail.tmall.com/item.htm?id=665519667811','https://detail.tmall.com/item.htm?id=585993479022'
,'https://item.taobao.com/item.htm?id=649233831246']
upper_hoodie = ['https://detail.tmall.com/item.htm?id=666165898023','https://item.taobao.com/item.htm?id=652872409153','https://item.taobao.com/item.htm?id=628894958150','https://detail.tmall.com/item.htm?id=633528937891'
,'https://item.taobao.com/item.htm?id=656080489764']
upper_sporty = ['https://item.taobao.com/item.htm?id=628559051772','https://detail.tmall.com/item.htm?id=668803933152','https://detail.tmall.com/item.htm?id=655672026380','https://detail.tmall.com/item.htm?id=631357306618'
,'https://detail.tmall.com/item.htm?id=601009441405']
upper_suit = ['https://detail.tmall.com/item.htm?id=666236552324','https://detail.tmall.com/item.htm?id=668803933152','https://item.taobao.com/item.htm?id=625828294674','https://detail.tmall.com/item.htm?id=649272374842','https://detail.tmall.com/item.htm?id=666063758350'
,'https://item.taobao.com/item.htm?id=668250478482']
whole_dress = ['https://detail.tmall.com/item.htm?id=598268797504','https://item.taobao.com/item.htm?id=666364831194','https://detail.tmall.com/item.htm?id=667095587171','https://detail.tmall.com/item.htm?id=642013218199'
,'https://detail.tmall.com/item.htm?id=669133765583']

split_dataset.pyThe script does a training set on the dataset、验证集、测试集的划分.

train.pyThe script trains on the dataset

数据集

Just fit the format,参考链接一

效果展示 

Click a link to take a look  

开源地址

A simple recommendation system based on neural network: A project I did a few months ago,整理一下,比较简单,It is to classify images according to the data set（使用resnet50）,Then match the recommendation database with the recognition result,进行推荐. (gitee.com)

参考资料

(195条消息) 【深度学习】使用pythonDivide the dataset into training set, validation set and test set and put them in different folders_I am a scumbag blog-CSDN博客_python划分数据集为训练集和测试集