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使用 OpenCV Python 提取所有边界框

[英]Extract all bounding boxes using OpenCV Python

I have an image that contains more than one bounding box.我有一张包含多个边界框的图像。
装订盒的书籍

I need to extract everything that has bounding boxes in them.我需要提取其中包含边界框的所有内容。 So far, from this site I've gotten this answer:到目前为止,从这个网站我得到了这个答案:

y = img[by:by+bh, bx:bx+bw]
cv2.imwrite(string + '.png', y)

It works, however, it only gets one.它有效,但是,它只有一个。 How should I modify the code?我应该如何修改代码? I tried putting it in the loop for contours but it still spews out one image instead of multiple ones.我尝试将其放入轮廓循环中,但它仍然喷出一张图像而不是多张图像。

Thank you so much in advance.非常感谢你。

there you go:你去吧:

import cv2

im = cv2.imread('c:/data/ph.jpg')
gray=cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)
contours, hierarchy = cv2.findContours(gray,cv2.RETR_LIST,cv2.CHAIN_APPROX_SIMPLE)[-2:]
idx =0 
for cnt in contours:
    idx += 1
    x,y,w,h = cv2.boundingRect(cnt)
    roi=im[y:y+h,x:x+w]
    cv2.imwrite(str(idx) + '.jpg', roi)
    #cv2.rectangle(im,(x,y),(x+w,y+h),(200,0,0),2)
cv2.imshow('img',im)
cv2.waitKey(0)    

A simple approach is to find all contours, obtain the bounding rectangle coordinates using cv2.boundingRect then extract the ROI using Numpy slicing.一个简单的方法是找到所有轮廓,使用cv2.boundingRect获得边界矩形坐标,然后使用 Numpy 切片提取 ROI。 We can keep a counter to save each ROI then save it with cv2.imwrite .我们可以保留一个计数器来保存每个 ROI,然后用cv2.imwrite保存它。 Here's a working example:这是一个工作示例:

Input image:输入图像:

在此处输入图片说明

Detected ROIs to extract highlighted in green检测到的 ROIs 以绿色突出显示

在此处输入图片说明

Saved ROIs节省的投资回报率

在此处输入图片说明

Code代码

import cv2
import numpy as np

# Load image, grayscale, Otsu's threshold 
image = cv2.imread('1.png')
original = image.copy()
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]

# Find contours, obtain bounding box, extract and save ROI
ROI_number = 0
cnts = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
for c in cnts:
    x,y,w,h = cv2.boundingRect(c)
    cv2.rectangle(image, (x, y), (x + w, y + h), (36,255,12), 2)
    ROI = original[y:y+h, x:x+w]
    cv2.imwrite('ROI_{}.png'.format(ROI_number), ROI)
    ROI_number += 1

cv2.imshow('image', image)
cv2.waitKey()

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