find the top right corner with black pixel usind a grid

Question

i have this page and i am trying to make a cropped image with the top right corner i used this code for the top left corner with black pixel inside but could not edit it to work for top right.it makes a grid .if the square inside has black pixels is number 1 else is 0. it find the top left square with black pixels and crop around it.

input

output

I am trying to auto-crop this page number area

I think the script search from like the blue arrow and i want to work like the red

import cv2
import numpy as np

# Load the cropped image in grayscale
image = cv2.imread('input.jpg', cv2.IMREAD_GRAYSCALE)

# Get the height and width of the image
h, w = image.shape

# Define the number of rows and columns of the grid
rows = 30
cols = 40

# Calculate the size of each square in pixels
square_h = h // rows
square_w = w // cols

# Create an empty array to store the grid values
grid = np.zeros((rows, cols), dtype=int)

# Loop over the rows and columns of the grid
for i in range(rows):
    for j in range(cols):
        # Get the coordinates of the top left corner of the square
        x = j * square_w
        y = i * square_h

        # Get the sub-image corresponding to the square
        square = image[y:y+square_h, x:x+square_w]

        # Check if the square contains any black pixels
        if np.any(square < 255):
            # Set the grid value to 1
            grid[i, j] = 1

# Find the top left corner with a 1 square
# Use np.argwhere to get the indices of the nonzero elements
# Use np.min to get the minimum row and column index
top_left = np.min(np.argwhere(grid == 1), axis=0)

# Get the row and column index of the top left corner
row, col = top_left

# Define the number of squares to crop around the corner
crop_size = 3

# Get the coordinates of the top left corner of the cropped region
x = col * square_w
y = row * square_h

# Get the sub-image corresponding to the cropped region
cropped_image = image[y:y+crop_size*square_h, x:x+crop_size*square_w]

# Save the result
cv2.imwrite('output.jpg', cropped_image)

could not work for top right corner

Answer 1

ok i figure out what i wanted i think i find how to detect page number from a page

this is the black n white page on the top right is the pattern i want to crop ,this match with page number from multiple even pages ,the one i uploaded input.jpg is an example image

output.txt
000000000000000000000000000000000000000000000000000000000000
000000000000000000000000000000000000000000000000000000000000
000000000000000000000000000000000000000000000000000000000000
000000000000000000000000000000000000000000000000000000000000
000000000000000000000000000000000000000000000000000000000000
0000#0#######################0#####################00##00000
000##0##############################################0##00000
000#################################################00000000
000#################################################00000000
000#################################################00000000
000#################################################00000000
000#################################################00000000
000#################################################00000000
000##################################################0000000
000##################################################0000000
000##################################################0000000
000##################################################0000000
000##################################################0000000
000##################################################0000000
000##################################################0000000
000##################################################0000000
000##################################################0000000
000##################################################0000000
000##################################################0000000
000####################################################00000
000####################################################00000
000####################################################00000
000####################################################00000
000####################################################00000
000####################################################00000
000####################################################00000
000###0#######################0########################00000
000###0#######################0########################00000
000###0#######################0########################00000
000###0#######################0#####################0##00000
000###0#######################0#####################0##00000
000###0#######################0#####################0##00000
000###0#######################00########0###########0##00000
000000000000000000000000000000000000000000000000000000000000
####0000000000000000000000000000#00####00#0###000#00########
############################################################
00#0##0##0###000000000#0##000000#########00000##0000000#0000
00#0#0#0#0#000#00#000#00##00000##########000#00##0##00#00000
0###0#00###0##00#000####000#0#00###################00#000000
0#00##00####0#000000##00###0000#######0########0######000000

this is the pattern i will try to crop here is on top right

0000
0##0
0##0
0000
0000

this is the code

import cv2
import numpy as np

# Load the cropped image in grayscale
image = cv2.imread('input.jpg', cv2.IMREAD_GRAYSCALE)

# Get the height and width of the image
h, w = image.shape

# Define the number of rows and columns of the grid
rows = 45
cols = 60

# Calculate the size of each square in pixels
square_h = h // rows
square_w = w // cols

# Create an empty array to store the grid values
grid = np.empty((rows, cols), dtype=str)

# Loop over the rows and columns of the grid
for i in range(rows):
    for j in range(cols):
        # Get the coordinates of the top left corner of the square
        x = j * square_w
        y = i * square_h

        # Get the sub-image corresponding to the square
        square = image[y:y+square_h, x:x+square_w]

        # Check if the square contains any black pixel
        if np.any(square < 255):
            # Set the grid value to '#'
            grid[i, j] = '#'
        else:
            # Set the grid value to '0'
            grid[i, j] = '0'

# Write the result to output.txt
with open('output.txt', 'w') as file:
    for i in range(rows):
        for j in range(cols):
            file.write(grid[i, j])
        file.write('\n')

# Pattern matching
pattern = [
    '0000',
    '0##0',
    '0##0',
    '0000',
    '0000'
]

with open("output.txt", "r") as file:
    content = file.read()

lines = content.split('\n')

for i in range(len(lines) - len(pattern) + 1):
    for j in range(len(lines[i]) - len(pattern[0]) + 1):
        match = True
        for k in range(len(pattern)):
            if lines[i + k][j:j+len(pattern[0])] != pattern[k]:
                match = False
                break
        if match:
            print(f"Pattern found at line {i+1}, position {j+1}")

            # Crop the region where the pattern is found
            x_start = j * square_w
            y_start = i * square_h
            x_end = (j + len(pattern[0])) * square_w
            y_end = (i + len(pattern)) * square_h

            cropped_image = image[y_start:y_end, x_start:x_end]

            # Save the cropped image
            cv2.imwrite('cropped_page_number.jpg', cropped_image)

    

thanks for your comments