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image - Crop Rectangle returned by minAreaRect OpenCV [Python]

minAreaRect in OpenCV returns a rotated rectangle. How do I crop this part of the image which is inside the rectangle?

boxPoints returns the co-ordinates of the corner points of the rotated rectangle so one can access the pixels by looping through the points inside the box, but is there a faster way to crop in Python?

EDIT

See code in my answer below.

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here a function that does this task:

import cv2
import numpy as np

def crop_minAreaRect(img, rect):

    # rotate img
    angle = rect[2]
    rows,cols = img.shape[0], img.shape[1]
    M = cv2.getRotationMatrix2D((cols/2,rows/2),angle,1)
    img_rot = cv2.warpAffine(img,M,(cols,rows))

    # rotate bounding box
    rect0 = (rect[0], rect[1], 0.0) 
    box = cv2.boxPoints(rect0)
    pts = np.int0(cv2.transform(np.array([box]), M))[0]    
    pts[pts < 0] = 0

    # crop
    img_crop = img_rot[pts[1][1]:pts[0][1], 
                       pts[1][0]:pts[2][0]]

    return img_crop

here an example usage

# generate image
img = np.zeros((1000, 1000), dtype=np.uint8)
img = cv2.line(img,(400,400),(511,511),1,120)
img = cv2.line(img,(300,300),(700,500),1,120)

# find contours / rectangle
_,contours,_ = cv2.findContours(img, 1, 1)
rect = cv2.minAreaRect(contours[0])

# crop
img_croped = crop_minAreaRect(img, rect)

# show
import matplotlib.pylab as plt
plt.figure()
plt.subplot(1,2,1)
plt.imshow(img)
plt.subplot(1,2,2)
plt.imshow(img_croped)
plt.show()

this is the output

original and croped image


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