readme in english

Author: bytesc

README.en.md

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+# Image_Classify_WebGUI_CIFAR10
+
+✨**Intelligent Image Classification Web Applcation based on Convolutional Neural Networks and the CIFAR10 Dataset** : Image classification visualization interface, image classification front-end web page, image classification Demo display-Pywebio. AI artificial intelligence image classification-Pytorch. CIFAR10 dataset, small model. 100% pure Python code, lightweight, easy to reproduce.
+
+[简体中文文档](./README.md)
+
+[Personal website: www.bytesc.top](http://www.bytesc.top) includes online project demonstrations.
+
+## Project Introduction
+* 1. Use pytorch to implement intelligent classification of CIFAR10 dataset images
+* 2. Use a small model, lightweight, with a 76% accuracy rate
+* 3. Use pywebio as the web visualization framework, no need for front-end language, written in pure python. Lightweight, easy to reproduce, easy to deploy
+
+Network structure used
+![image](./readme_static/readme_img/net.png)
+
+## Screenshot of the effect
+![image](./readme_static/readme_img/1.png)
+![image](./readme_static/readme_img/2.png)
+![image](./readme_static/readme_img/3.png)
+
+## How to use
+Python version 3.9
+
+First install dependencies
+> pip install -r requirement.txt
+
+modelDemo.py is the project entry point, run this file to start the server
+> python modelDemo.py
+
+Copy the link to the browser and open it
+![image](./readme_static/readme_img/p1.png)
+Click "Demo" to enter the Web interface
+![image](./readme_static/readme_img/p2.png)
+
+After that, you can also click "Upload File" and select an image file from the example_img folder to upload and test
+
+## Project structure
+```
+└─Image_Classify_WebGUI_CIFAR10
+    ├─data
+    │  └─logs_import 
+    ├─example_img
+    ├─process
+    │  └─logs
+    └─readme_static
+```
+* The data folder stores some static resources, including the trained model.pth
+* The process folder stores some process files, including the model training program, etc.
+* readme_static stores static resources used in the readme document
+* The example_img folder contains some images that can be used for testing

README.md

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 # Image_Classify_WebGUI_CIFAR10
 
-基于CIFAR10的图像分类：图像分类可视化界面，图像分类前端网页，图像分类Demo展示-Pywebio。AI人工智能图像分类-Pytorch。CIFAR10数据集，小模型。100%纯Python代码，轻量化，易复现 
+✨ **基于卷积神经网络(CNN)和 CIFAR10 数据集的图像智能分类**：图像分类可视化界面，图像分类前端网页，图像分类Demo展示-Pywebio。AI人工智能图像分类-Pytorch。CIFAR10数据集，小模型。100%纯Python代码，轻量化，易复现 
+
+[English Readme](./README.en.md)🚩
 
 [个人网站：www.bytesc.top](http://www.bytesc.top) 包含项目在线演示。