Extract bounding box and save it as an image

Question

Suppose you have the following image:

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 :

After this, I want to extract each of the boxes (in this case for the letter a ) and save it to an image file.

Expected result:

Here's my code so far:

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.

Answer 1

下面会给你一封信

letter = im[y:y+h,x:x+w]

Answer 2

Here's an approach:

• Convert image to grayscale
• Otsu's threshold to obtain a binary image
• Find contours
• Iterate through contours and extract ROI using Numpy slicing

---

After finding contours, we use cv2.boundingRect() to obtain the bounding rectangle coordinates for each letter.

x,y,w,h = cv2.boundingRect(c)

To extract the ROI, we use Numpy slicing

ROI = image[y:y+h, x:x+w]

Since we have the bounding rectangle coordinates, we can draw the green bounding boxes

cv2.rectangle(copy,(x,y),(x+w,y+h),(36,255,12),2)

Here's the detected letters

Here's each saved letter 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()

Answer 3

        def bounding_box_img(img,bbox):
            x_min, y_min, x_max, y_max = bbox
            bbox_obj = img[y_min:y_max, x_min:x_max]
            return bbox_obj

        img = cv2.imread("image.jpg")
        cropped_img = bounding_box_img(img,bbox)
        cv2.imshow(cropped_img)

this returns cropped image (bounding box)

in this aproach, bounding box coordinates bases on pascal-voc annotation formats like here