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Image processing kit.

Project description

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📦 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

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.

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