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images to np array and keep the order

I am trying to take 1967 jpg images to a np array with following codes. How do I keep the original order of the images in the array?
import cv2
import glob
import numpy as np
X_data = []
files = glob.glob ("/content/drive/My Drive/CourseWork/images/emotionet_validation/*.jpg")
for myFile in files:
print(myFile)
image = cv2.imread (myFile)
X_data.append (image)
print('X_data shape:', np.array(X_data).shape)

https://docs.python.org/3/howto/sorting.html
import cv2
import glob
import numpy as np
X_data = []
files = glob.glob ("/content/drive/My Drive/CourseWork/images/emotionet_validation/*.jpg")
sorted(files)
## Do you need sort to ignore case?
## sorted(files, key=str.casefold)
for myFile in files:
print(myFile)
image = cv2.imread (myFile)
X_data.append (image)
print('X_data shape:', np.array(X_data).shape)

Merging images from different folders and storing to a different folder

I have three different folders m1, m2, and m3. The 'm1' folder contains images of the format image(i)_m1.png (where i =1 to N), 'm2' folder contains images of the format image(i)_m2.png, and 'm3' folder contains images of the format image(i)_m3.png. I want to merge these images using cv2.merge like this:(cv2.merge((image1_m1, image1_m2, image1_m3)) and it continues for N times and get stored in a different folder than contains 'N' merged images of the format image(i)_merged.png.
import pandas as pd
import cv2
import numpy as np
import glob
import os
filenames1 = glob.glob("data_folder/m1/*.png")
filenames1.sort()
filenames2 = glob.glob("data_folder/m2/*.png")
filenames2.sort()
filenames3 = glob.glob("data_folder/m3/*.png")
filenames3.sort()
for f1 in filenames1:
for f2 in filenames2:
for f3 in filenames3:
img1 = cv2.imread(f1)
img2 = cv2.imread(f2)
img3 = cv2.imread(f3)
img_m1 = cv2.cvtColor(img1, cv2.COLOR_BGR2GRAY)
img_m2 = cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY)
img_m3 = cv2.cvtColor(img3, cv2.COLOR_BGR2GRAY)
img_rgb = cv2.merge((img_m1, img_m2, img_m3))
cv2.imwrite("data_folder/merge/img_name.png", img_rgb)

Your question is not complete. I assume you have a problem with for loop.
You might replace the nested for loops with this:
for f1,f2,f3 in zip(filenames1,filenames2,filenames3):

Write an array of Dicom images

I have a folder of dicom images and I stored these images in an array and I would like to print them out in a different folder.
I cannot find a method that will write out each of the images like the cv2.imwrite
import pydicom
import skimage, os
import numpy as np
FolderPathName = r'FolderPathName'
slices = [pydicom.read_file(FolderPathName + imagename) for imagename in os.listdir(FolderPathName)]
# Sort the dicom slices in their respective order
slices.sort(key=lambda x: int(x.InstanceNumber))
for x in range(len(slices)):
#write the images in a new folder

Method 1:
In your case,
The answer is ...
import pydicom
import skimage, os
import numpy as np
FolderPathName = r'FolderPathName'
slices = [pydicom.read_file(FolderPathName + imagename) for imagename in os.listdir(FolderPathName)]
# Sort the dicom slices in their respective order
slices.sort(key=lambda x: int(x.InstanceNumber))
jpg_folder = '' # Set your jpg folder
for idx in range(len(slices)):
#write the images in a new folder
jpg_filepath = os.path.join( jpg_folder, "pic-{}.jpg".format(idx) )
np_pixel_array = slices[idx].pixel_array
cv2.imwrite(jpg_filepath, np_pixel_array)
Method 2:
But, there is better way to process dicom files ...
import pydicom
import os
import numpy as np
import cv2
dicom_folder = '' # Set the folder of your dicom files that inclued images
jpg_folder = '' # Set the folder of your output folder for jpg files
# Step 1. prepare your input(.dcm) and output(.jpg) filepath
dcm_jpg_map = {}
for dicom_f in os.listdir(dicom_folder):
dicom_filepath = os.path.join(dicom_folder, dicom_f)
jpg_f = dicom_f.replace('.dcm', '.jpg')
jpg_filepath = os.path.join(jpg_folder,jpg_f)
dcm_jpg_map[dicom_filepath] = jpg_filepath
# Now, dcm_jpg_map is key,value pair of input dcm filepath and output jpg filepath
# Step 2. process your image by input/output information
for dicom_filepath, jpg_filepath in dcm_jpg_map.items():
# convert dicom file into jpg file
dicom = pydicom.read_file(dicom_filepath)
np_pixel_array = dicom.pixel_array
cv2.imwrite(jpg_filepath, np_pixel_array)
In above code,
the Step 1 is focus on file path processing. It's good for your to porting your code into different environment easily.
The Step 2 is major code which focus on any kind of image processing.

Reading Multiple tiff files in python from a folder

I have a folder containing 10K tiff files, how can i import all the files using python so that i can do some predictive modelling.
thanks
NK

Use the following approach:
import os
from PIL import Image
import numpy as np
dirname = 'tiff_folder_path'
final = []
for fname in os.listdir(dirname):
im = Image.open(os.path.join(dirname, fname))
imarray = np.array(im)
final.append(imarray)
final = np.asarray(final) # shape = (60000,28,28)

How to convert multiple RGB images in one folder to grayscale in python

Someone could help me please, I want to convert my RGB images in one folder to grayscale at one time. I've been looking for some Python codes but haven't found any. I tried to do as following but it didn't work.
Here is my code:
from skimage.color import rgb2gray
from skimage.io import imread, imsave
from skimage.filters import threshold_otsu
from skimage import img_as_uint
inp_image = imread("C:/RGB/*.JPG")
img_gray = rgb2gray(inp_image)
thresh = threshold_otsu(img_gray)
binary_thresh_img = img_gray & gt; thresh
imsave("C:/Grayscale", img_as_uint(binary_thresh_img))
And it gave me following error:
OSError: [Errno 22] Invalid argument: 'C:/RGB/*.JPG'

You can get the list with the filenames with glob().
import glob
for filename in glob.glob("C:/RGB/*.JPG"):
inp_image = imread(filename)
[...]

To add to the list of solutions:
import os
from PIL import Image
ORIGIN_PATH = "./folder1/"
DESTIN_PATH = "./folder2/"
for filename in os.listdir(ORIGIN_PATH):
img = Image.open(ORIGIN_PATH + filename).convert("LA")
img.save(DESTIN_PATH + filename)