使用Python和OpenCV对轮廓线进行排序

Alright, so at this point you have been exposed to contours pretty heavily on the PyImageSearch blog.

好吧，那么在这一点上，你已经在PyImageSearch博客上大量地接触到了轮廓线。

We used contours to build a kick-ass mobile document scanner.

Contours enabled us detect barcodes in images.

And we even leveraged the power of contours to find the distance from a camera to object or marker.

But there still remains a sticking question that we have not addressed: how in the world do we sort contours from left-to-right, top-to-bottom, etc.

但仍有一个我们没有解决的症结问题：我们究竟如何 从左到右、从上到下对轮廓进行排序， 等等。

Oddly enough OpenCV does not provide a built-in function or method to perform the actual sorting of contours.

奇怪的是，OpenCV并没有提供一个内置的函数或方法来进行实际的轮廓排序。

But no worries.

但不用担心。

In the rest of this blog you’ll be sorting contours using Python and OpenCV like a pro.

在本博客的其余部分，你将像专家一样使用Python和OpenCV对轮廓线进行分类。

Read on to find out more…

继续阅读以了解更多...

OpenCV and Python versions:
In order to run this example, you’ll need Python 2.7 and OpenCV 2.4.X.

OpenCV和Python版本：
为了运行这个例子，你需要Python 2.7和OpenCV 2.4.X。

By the end of this blog article you’ll be able to:

在这篇博客文章结束时，你将能够。

Sort contours according to their size/area, along with a template to follow to sort contours by any other arbitrary criteria.
根据轮廓的大小/面积进行排序，同时还有一个模板，可以按照任何其他任意的标准对轮廓进行排序。
Sort contoured regions from left-to-right, right-to-left, top-to-bottom, and bottom-to-top using only a single function.
从左到右、从右到左、从上到下、从下到上对轮廓区域进行排序，只用一个 单一函数.

So let’s go ahead and get started. Open up your favorite code editor, name it

因此，让我们继续并开始吧。打开你喜欢的代码编辑器，将其命名为

sorting_contours.py and let’s get started: → Launch Jupyter Notebook on Google Colab

sorting_contours.py ，让我们开始吧。→ 在Google Colab上启动Jupyter笔记本

Sorting Contours using Python and OpenCV

使用Python和OpenCV对轮廓线进行排序

# import the necessary packages

#导入必要的软件包

def sort_contours(cnts, method="left-to-right"):

# initialize the reverse flag and sort index

#初始化反向标志和排序索引

# handle if we need to so...