Warning: file_get_contents(/data/phpspider/zhask/data//catemap/2/python/323.json): failed to open stream: No such file or directory in /data/phpspider/zhask/libs/function.php on line 167

Warning: Invalid argument supplied for foreach() in /data/phpspider/zhask/libs/tag.function.php on line 1116

Notice: Undefined index: in /data/phpspider/zhask/libs/function.php on line 180

Warning: array_chunk() expects parameter 1 to be array, null given in /data/phpspider/zhask/libs/function.php on line 181
Python opencv在图像上查找五边形轮廓_Python_Image_Opencv_Image Processing_Opencv Contour - Fatal编程技术网

Python opencv在图像上查找五边形轮廓

Python opencv在图像上查找五边形轮廓,python,image,opencv,image-processing,opencv-contour,Python,Image,Opencv,Image Processing,Opencv Contour,我试图从简单的附加图像中读取数字 为此,我试图找到五角大楼持有的数字。然而,当我试图使用opencv findcontour函数查找五角大楼时,它没有给出正确的值。我试过用这个函数进行各种排列。这些都不管用 到目前为止,我已经尝试了以下几点: import cv2 as cv import numpy as np im = cv.imread(r'out.jpg') imgray = cv.cvtColor(im, cv.COLOR_BGR2GRAY) ret, thresh = cv.th

我试图从简单的附加图像中读取数字

为此,我试图找到五角大楼持有的数字。然而,当我试图使用opencv findcontour函数查找五角大楼时,它没有给出正确的值。我试过用这个函数进行各种排列。这些都不管用

到目前为止,我已经尝试了以下几点:

import cv2 as cv
import numpy as np

im = cv.imread(r'out.jpg')
imgray = cv.cvtColor(im, cv.COLOR_BGR2GRAY)
ret, thresh = cv.threshold(imgray, 200, 255, 0)

contours, hierarchy = cv.findContours(thresh, cv.RETR_LIST  , cv.CHAIN_APPROX_SIMPLE)

for c in contours:
    print(len(c))
输出: 1. 1. 1. 1. 1. 1. 1. 1. 38 36 1. 1. 85 87 128 133 55 47 4. 4. 7. 4. 4. 四,

这些都不是5,所以上面的几点不可能是五角大楼


如果我犯了什么错误,你能帮我一下吗?

你说得对。找到轮廓后,需要使用+,执行轮廓近似。您可以从
cv2.approxPolyDP
检查返回值,这将为您提供多边形曲线形状近似值。如果该值为5,则可以假定它是五角大楼。这里有一个简单的方法:

  • 获取二值图像。加载图像,灰度

  • 查找轮廓并执行轮廓近似。查找轮廓,然后执行轮廓近似。如果轮廓通过此过滤器,我们将使用提取边界矩形坐标,并使用Numpy切片提取/保存ROI


  • 检测到的ROI以teal表示

    提取/保存的ROI

    注意:有两个ROI保存为单个图像,但它们是相同的

    代码

    import cv2
    import numpy as np
    
    # Load image, grayscale, bilaterial filter, Otsu's threshold
    image = cv2.imread('1.jpg')
    original = image.copy()
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    blur = cv2.bilateralFilter(gray,9,75,75)
    thresh = cv2.threshold(blur, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]
    
    # Find contours, perform contour approximation, and extract ROI
    ROI_num = 0
    cnts = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    cnts = cnts[0] if len(cnts) == 2 else cnts[1]
    for c in cnts:
        peri = cv2.arcLength(c, True)
        approx = cv2.approxPolyDP(c, 0.04 * peri, True)
        # If has 5 then its a pentagon
        if len(approx) == 5:
            x,y,w,h = cv2.boundingRect(approx)
            cv2.rectangle(image, (x, y), (x + w, y + h), (200,255,12), 2)
            ROI = original[y:y+h, x:x+w]
            cv2.imwrite('ROI_{}.png'.format(ROI_num), ROI)
            ROI_num += 1
    
    cv2.imshow('thresh', thresh)
    cv2.imshow('ROI', ROI)
    cv2.imshow('image', image)
    cv2.waitKey()