sk-cv 0.2.0

Image processing kit.

📦 setup.py (for humans)

This repo exists to provide an example setup.py file, that can be used to bootstrap your next Python project. It includes some advanced patterns and best practices for setup.py, as well as some commented–out nice–to–haves.

For example, this setup.py provides a $ python setup.py upload command, which creates a universal wheel (and sdist) and uploads your package to PyPi using Twine, without the need for an annoying setup.cfg file. It also creates/uploads a new git tag, automatically.

In short, setup.py files can be daunting to approach, when first starting out — even Guido has been heard saying, "everyone cargo cults thems". It's true — so, I want this repo to be the best place to copy–paste from :)

Check out the example!

Installation

cd your_project

# Download the setup.py file:
#  download with wget
wget https://raw.githubusercontent.com/navdeep-G/setup.py/master/setup.py -O setup.py

#  download with curl
curl -O https://raw.githubusercontent.com/navdeep-G/setup.py/master/setup.py

To Do

• Tests via $ setup.py test (if it's concise).

Pull requests are encouraged!

Requirements

• opencv_python_headless==4.4.0.46
• numpy==1.19.3
• scipy==1.5.2
• matplotlib==3.3.2
• Pillow==8.2.0

Modules included

• image_io
  • read_image_opencv 使用opencv读取图片(支持中英文路径)
  • read_image_image 使用PIL中的Image读取图片
  • image_save 保存图片(支持中英文路径)
  • display_image 显示图片
• image_processing
  • image_type_trans_opencv_image opencv和Image打开的图片格式转换
  • image_type_transform 常用图片格式转换
  • rotate_angle 旋转图片
  • image_lightup 增加亮度
  • image_erosion 腐蚀
  • image_dilate 膨胀
  • edge_detection 边缘检测
  • hsv_extract 颜色提取
  • remove_outliers 过滤连通区域
  • hough_lines 霍夫变换
  • filtering_function 均值滤波、高斯滤波、中值滤波
  • contour_detection 检测轮廓
  • draw_contour 在图像上画出全部轮廓
  • max_area_contours 寻找最大轮廓，并画出该轮廓最小外接矩形
  • filter_contours_area 过滤面积较小的轮廓
  • filter_contours_ratio 根据轮廓的最小外接矩形长宽比过滤轮廓
  • compute_ssim ssim算法计算两张图的相似度

More Resources

• What is setup.py? on Stack Overflow
• Official Python Packaging User Guide
• The Hitchhiker's Guide to Packaging
• Cookiecutter template for a Python package

License

This is free and unencumbered software released into the public domain.

Anyone is free to copy, modify, publish, use, compile, sell, or distribute this software, either in source code form or as a compiled binary, for any purpose, commercial or non-commercial, and by any means.