Crop an image to smaller size from left to right and top to bottom using OpenCV


I have an image 315×581. I want to crop it in 28×28 from top left to bottom right, then I need to save each 28×28 image in folder.
I could crop just one image from y1=0 to y2=28 and x1=0 to x2=28.

First problem is: I used cv2.imwrite(“cropped.jpg”, cropped) to save this small image, but It doesn’t save it, provided that it works some line above.

Second problem is: How can I write a code which it keeps on cropping the image in 28×28 from left to right and top to bottom and save each subimage.
I used for loop, but I don’t know how to complete it.
Thank you so much for any help.

Here this is my code,

import cv2
import numpy as np
from PIL import Image
import PIL.Image
import os
import gzip
import matplotlib
import matplotlib.pyplot as plt
import as cm

#finalsSave='C:/Users/Tala/Documents/PythonProjects/Poster-OpenCV-MaskXray/Xray Result'

# load the image
img = cv2.imread(image1LL,0)
mask = cv2.imread(mask1LL,0)

# combine foreground+background
final1LL = cv2.bitwise_and(img,img,mask = mask)


# Save the image

# crop the image using array slices -- it's a NumPy array
# after all!

for y2 in range(0,580,28):
    for x2 in range(0,314,28):
       cropped = final1LL[0:28, 0:28]
       cv2.imshow('cropped', cropped)
       cv2.imwrite("cropped.jpg", cropped)


Your approach is good, but there is some fine tuning required. The following code will help you:

import cv2

filename = 'p1.jpg'
img = cv2.imread(filename, 1)

interval = 100
stride = 100
count = 0
print img.shape

for i in range(0, img.shape[0], interval):
    for j in range(0, img.shape[1], interval):
        print j
        cropped_img = img[j:j + stride, i:i + stride]  #--- Notice this part where you have to add the stride as well ---
        count += 1
        cv2.imwrite('cropped_image_' + str(count) + '_.jpg', cropped_img)   #--- Also take note of how you would save all the cropped images by incrementing the count variable ---


My result:

Original image:

enter image description here

Some of the cropped images:

Cropped image 1

enter image description here

Cropped image 2

enter image description here

Cropped image 3

enter image description here

Answered By – Jeru Luke

Answer Checked By – Katrina (AngularFixing Volunteer)

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