Python 提取边界框并将其保存为图像
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Extract bounding box and save it as an image
提问by Edgar Andrés Margffoy Tuay
Suppose you have the following image:
假设您有以下图像：
Now I want to extract each of the independent letters into individual images. Currently, I've recovered the contours and then drew a bounding box, in this case for the character a:
现在我想将每个独立的字母提取到单独的图像中。目前，我已经恢复了轮廓，然后绘制了一个边界框，在这种情况下为字符a：
After this, I want to extract each of the boxes (in this case for the letter a) and save it to an image file.
在此之后，我想提取每个框（在本例中为字母a）并将其保存到图像文件中。
Expected result:
预期结果：
Here's my code so far:
到目前为止，这是我的代码：
import numpy as np
import cv2
im = cv2.imread('abcd.png')
im[im == 255] = 1
im[im == 0] = 255
im[im == 1] = 0
im2 = cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)
ret,thresh = cv2.threshold(im2,127,255,0)
contours, hierarchy = cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
for i in range(0, len(contours)):
if (i % 2 == 0):
cnt = contours[i]
#mask = np.zeros(im2.shape,np.uint8)
#cv2.drawContours(mask,[cnt],0,255,-1)
x,y,w,h = cv2.boundingRect(cnt)
cv2.rectangle(im,(x,y),(x+w,y+h),(0,255,0),2)
cv2.imshow('Features', im)
cv2.imwrite(str(i)+'.png', im)
cv2.destroyAllWindows()
Thanks in advance.
提前致谢。
采纳答案by Andrey Kamaev
The following will give you a single letter
下面给你一个字母
letter = im[y:y+h,x:x+w]
回答by nathancy
Here's an approach:
这是一种方法：
- Convert image to grayscale
- Otsu's threshold to obtain a binary image
- Find contours
- Iterate through contours and extract ROI using Numpy slicing
- 将图像转换为灰度
- 获得二值图像的大津阈值
- 查找轮廓
- 迭代轮廓并使用 Numpy 切片提取 ROI
After finding contours, we use cv2.boundingRect()to obtain the bounding rectangle coordinates for each letter.
找到轮廓后，我们使用cv2.boundingRect()获取每个字母的边界矩形坐标。
x,y,w,h = cv2.boundingRect(c)
To extract the ROI, we use Numpy slicing
为了提取 ROI，我们使用 Numpy 切片
ROI = image[y:y+h, x:x+w]
Since we have the bounding rectangle coordinates, we can draw the green bounding boxes
由于我们有边界矩形坐标，我们可以绘制绿色边界框
cv2.rectangle(copy,(x,y),(x+w,y+h),(36,255,12),2)
Here's the detected letters
这是检测到的字母
Here's each saved letter ROI
这是每个保存的字母 ROI
import cv2
image = cv2.imread('1.png')
copy = image.copy()
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
thresh = cv2.threshold(gray,0,255,cv2.THRESH_OTSU + cv2.THRESH_BINARY)[1]
cnts = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
ROI_number = 0
for c in cnts:
x,y,w,h = cv2.boundingRect(c)
ROI = image[y:y+h, x:x+w]
cv2.imwrite('ROI_{}.png'.format(ROI_number), ROI)
cv2.rectangle(copy,(x,y),(x+w,y+h),(36,255,12),2)
ROI_number += 1
cv2.imshow('thresh', thresh)
cv2.imshow('copy', copy)
cv2.waitKey()
