Combining multiple values from database into one image - numpy

Question

I'm trying to take 5 consecutive pixels from each image of a database, and position them consecutively to create a new image of 250x250px. all images in the database are 250x250px.
The Numpy array I'm getting has only 250 items in it, although the database has about 13,000 photos in it. Can someone help me spot the problem?
Current output for 'len(new_img_pxl)' = 250
Illustration
#edit:
from imutils import paths
import cv2
import numpy as np
# access database
database_path = list(paths.list_images('database'))
#grey scale database
img_gray = []
x = -5
y = 0
r = 0
new_img_pxl = []
# open as grayscale, resize
for img_path in database_path:
img = cv2.imread(img_path, cv2.IMREAD_GRAYSCALE)
img_resize = cv2.resize(img, (250, 250))
img_gray.append(img_resize)
# take five consecutive pixel from each image
for item in img_gray:
x += 5
y += 5
five_pix = item[[r][x:y]]
for pix in five_pix:
new_img_pxl.append(pix)
if y == 250:
r += 1
x = -5
y = 0
# convert to array
new_img_pxl_array = np.array(new_img_pxl)
reshape_new_img = new_img_pxl_array.reshape(25,10)
# Convert the pixels into an array using numpy
array = np.array(reshape_new_img, dtype=np.uint8)
new_img_output = cv2.imwrite('new_output_save/001.png',reshape_new_img)

Answer 1

your bug is in the second loop.
for item in img_gray:
for every image (i) in the list img_gray you do:
for a in item:
for each row (j) in the image (i), extract 5 pixels and append them to new_img_pxl.
the first bug is that you don't take just 5 pixels from each image, you take 5 pixels from each row of each image.
your 2nd bug is that after extracting 250 pixels the values of the variables x and y are higher than 250 (the length of a row). As a result, when you try to access the pixels [250:255] and so on you get 'None'.
If I understand your intentions, then the way you should have implemented this is as follows:
r = 0
# As Mark Setchell suggested, you might want to change iterating
# over a list of images to iterating over the list of paths
# for img_path in database_path:
for item in img_gray:
# As Mark Setchell suggested, you might wat to load and
# process your image here, overwriting the past image and
# having the memory released
x += 5
y += 5
# when you finish a row jump to the next?
if x==250:
x = 0
y = 5
r+=1
# not sure what you wanna do when you get to the end of the image.
# roll back to the start?
if r==249 && x==250:
r = 0
x = 0
y = 5
five_pix = a[r, x:y]
for pix in five_pix:
new_img_pxl.append(pix)