k-means cluster images

说明

慕课网上例子，使用k-means算法分类图片， 此处调试运行通过， 并添加包管理内容， 使得其他同学容易运行。

例子地址： https://github.com/fanqingsong/cluster-images

运行环境：

python3.7

包管理工具：

pipenv

参考： https://www.cnblogs.com/wuzdandz/p/9545584.html

运行：

pipenv install

pipenv run ImageKmean.py

安装运行遇到问题

1、 安装依赖（numpy Pillow）很慢，

使用国内镜像替换：

http://greyli.com/set-custom-pypi-mirror-url-for-pip-pipenv-poetry-and-flit/

如果想对项目全局（per-project）设置，可以修改 Pipfile 中 [[source]] 小节：

[[source]] url = "https://pypi.doubanio.com/simple" verify_ssl = true name = "douban"

1 2 3 4 5

[[source]]   url = "https://pypi.doubanio.com/simple" verify_ssl = true name = "douban"

 如果不用pipenv， 使用pip安装

https://blog.csdn.net/lambert310/article/details/52412059

windows下，直接在user目录中创建一个pip目录，如：C:\Users\xx\pip，新建文件pip.ini，内容如下

 

 [global]
 index-url = https://pypi.tuna.tsinghua.edu.cn/simple

运行报错： ModuleNotFoundError: No module named 'PIL'

https://blog.csdn.net/qq_37721412/article/details/79159544

pip install Pillow 

Pillow库

https://pillow.readthedocs.io/en/stable/handbook/overview.html

he Python Imaging Library adds image processing capabilities to your Python interpreter.

This library provides extensive file format support, an efficient internal representation, and fairly powerful image processing capabilities.

The core image library is designed for fast access to data stored in a few basic pixel formats. It should provide a solid foundation for a general image processing tool.

Let’s look at a few possible uses of this library.

参考

https://github.com/jump1003/ImageKmeans

https://scikit-learn.org/stable/auto_examples/index.html#general-examples