If you are loading images, you are likely going to be working with one or both of matplotlib and opencv to manipulate and view the images.
For this reason, I tend to use their image readers and append those to lists, from which I make a NumPy array.
import os
import matplotlib.pyplot as plt
import cv2
import numpy as np
# Get the file paths
im_files = os.listdir('path/to/files/')
# imagine we only want to load PNG files (or JPEG or whatever...)
EXTENSION = '.png'
# Load using matplotlib
images_plt = [plt.imread(f) for f in im_files if f.endswith(EXTENSION)]
# convert your lists into a numpy array of size (N, H, W, C)
images = np.array(images_plt)
# Load using opencv
images_cv = [cv2.imread(f) for f in im_files if f.endswith(EXTENSION)]
# convert your lists into a numpy array of size (N, C, H, W)
images = np.array(images_cv)
The only difference to be aware of is the following:
So a single image that is 256*256 in size would produce matrices of size (3, 256, 256) with opencv and (256, 256, 3) using matplotlib.