Crop image opencv python

Please help me crop this image.
I need to split the image below into two images to compare them, but I want to cut them in such a way that the two cropped images have the same size and remove the excess area between the two images.

I have used the following code to crop, but it seems to be not very effective.

import cv2
import numpy as np

# Đọc bức ảnh gốc
image = cv2.imread('2.jpg')

# Lấy chiều cao và chiều rộng của ảnh
height, width = image.shape[:2]

# Tính vị trí cắt giữa hai ảnh
middle = width // 2

# Cắt và lấy hai phần bức ảnh
image1 = image[:, :middle]
image2 = image[:, middle:]

# Tìm contours trong ảnh 1
gray1 = cv2.cvtColor(image1, cv2.COLOR_BGR2GRAY)
_, thresh1 = cv2.threshold(gray1, 1, 255, cv2.THRESH_BINARY)
contours1, _ = cv2.findContours(thresh1, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
x1, _, w1, _ = cv2.boundingRect(contours1[0])

# Tìm contours trong ảnh 2
gray2 = cv2.cvtColor(image2, cv2.COLOR_BGR2GRAY)
_, thresh2 = cv2.threshold(gray2, 1, 255, cv2.THRESH_BINARY)
contours2, _ = cv2.findContours(thresh2, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
x2, _, w2, _ = cv2.boundingRect(contours2[0])

# Cắt bỏ vùng đen giữa hai ảnh
image1 = image1[:, x1:(x1+w1)]
image2 = image2[:, x2:(x2+w2)]

# Hiển thị hai ảnh đã cắt
cv2.imshow('Image 1', image1)
cv2.imshow('Image 2', image2)
cv2.waitKey(0)
cv2.destroyAllWindows()

Please help me with the code to crop the image as requested.

Here is one way to separate the two parts in Python/OpenCV

• Read the input
• Threshold on black
• Apply morphology open to remove thin lines
• Get the largest external contour
• Get the bounding box
• Use the size of the input and bounding box to crop the two parts
• Save the results

Input:

import cv2
import numpy as np

# read the image
img = cv2.imread('tom_and_jerry.jpg')
hh, ww = img.shape[:2]

# threshold on black
lower = (0,0,0)
upper = (10,10,10)
thresh = cv2.inRange(img, lower, upper)

# apply morphology open to remove thin lines
kernel = np.ones((3,3), np.uint8)
morph = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel)

# get largest contour
contours = cv2.findContours(morph, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
contours = contours[0] if len(contours) == 2 else contours[1]
big_contour = max(contours, key=cv2.contourArea)

# get bounding box
x,y,w,h = cv2.boundingRect(big_contour)

# crop the image into two parts
crop1 = img[0:hh, 0:x]
crop2 = img[0:hh, x+w:ww]

# save results
cv2.imwrite('tom_and_jerry_thresh.jpg', thresh)
cv2.imwrite('tom_and_jerry_morph.jpg', morph)
cv2.imwrite('tom_and_jerry_crop1.jpg', crop1)
cv2.imwrite('tom_and_jerry_crop2.jpg', crop2)

# show results
cv2.imshow('thresh', thresh)
cv2.imshow('morph', morph)
cv2.imshow('crop1', crop1)
cv2.imshow('crop2', crop2)
cv2.waitKey(0)

Threshold Image:

Morphology Cleaned Image:

Crop 1:

Crop 2:

Here is an alternate approach using Python/OpenCV.

• Read the input
• Threshold on black
• Apply morphology open to remove thin regions
• Get the counts of non-zero pixels along each column
• Find the first (min) location where the counts are greater than some threshold (99%)
• Find the last (max) location where the counts are greater than some threshold (99%)
• Use those values to crop the image into the two parts
• Save the results

Input:

import cv2
import numpy as np

# read the image
img = cv2.imread('tom_and_jerry.jpg')
hh, ww = img.shape[:2]

# threshold on black
lower = (0,0,0)
upper = (10,10,10)
thresh = cv2.inRange(img, lower, upper)

# apply morphology open to remove thin lines
kernel = np.ones((3,3), np.uint8)
morph = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel)

# count the number of non-zero pixels in each column
counts = np.count_nonzero(morph, axis=0)

# get the first and last position where counts >= 99% of hh
T=0.99
min = np.amin(np.where(counts>=T*hh))
max = np.amax(np.where(counts>=T*hh))
print(min,max)

# crop start x and width w
x = min-1
w = max-min+2


# crop the image into two parts
crop1 = img[0:hh, 0:x]
crop2 = img[0:hh, x+w:ww]

# save results
cv2.imwrite('tom_and_jerry_thresh.jpg', thresh)
cv2.imwrite('tom_and_jerry_morph.jpg', morph)
cv2.imwrite('tom_and_jerry_crop1.jpg', crop1)
cv2.imwrite('tom_and_jerry_crop2.jpg', crop2)

# show results
cv2.imshow('thresh', thresh)
cv2.imshow('morph', morph)
cv2.imshow('crop1', crop1)
cv2.imshow('crop2', crop2)
cv2.waitKey(0)

Crop 1:

Crop 2: