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How do I convert a folder of images to a npy file?

I have a folder containing images of gestures. But to make it work on my code I need to change it to X.npy and Y.npy. I looked for many questions regarding this kinda problems but still in the dark. How do I evaluate this? How do I convert the folder to create npy dataset of my own? Is there any code for this or any converter?

I found a piece of code for this purpose on github.
from PIL import Image
import os, sys
import cv2
import numpy as np
'''
Converts all images in a directory to '.npy' format.
Use np.save and np.load to save and load the images.
Use it for training your neural networks in ML/DL projects.
'''
# Path to image directory
path = "/path/to/image/directory/"
dirs = os.listdir( path )
dirs.sort()
x_train=[]
def load_dataset():
# Append images to a list
for item in dirs:
if os.path.isfile(path+item):
im = Image.open(path+item).convert("RGB")
im = np.array(im)
x_train.append(im)
if __name__ == "__main__":
load_dataset()
# Convert and save the list of images in '.npy' format
imgset=np.array(x_train)
np.save("imgds.npy",imgset)

You can refer to the code snippet in the following GitHub repo, that I found in google to convert a folder of images to a npy file:
https://gist.github.com/anilsathyan7/ffb35601483ac46bd72790fde55f5c04
Here in this case entire images in the folder are converted into NumPy array and are appended in a list named x_train.To convert and save this list of images in a single '.npy' format file, we can use the same code snippet:
imgset=np.array(x_train)
np.save("imgds.npy",imgset)
To convert and save this list of images in multiple '.npy' format files, use below code snippet :
imgset=np.array(x_train,dtype=object)
for i in range(len(imgset)):
np.save("imgds"+str(i)+".npy",imgset[i])

Errno 20: Not a directory when saving into zip file

When I try to save a pyplot figure as a jpg, I keep getting a directory error saying that the given file name is not a directory. I am working in Colab. I have a numpy array called z_img and have opened a zip file.
import matplotlib.pyplot as plt
from zipfile import ZipFile
zipObj = ZipFile('slices.zip', 'w') # opening zip file
plt.imshow(z_img, cmap='binary')
The plotting works fine. I did a test of saving the image into Colab's regular memory like so:
plt.savefig(str(ii)+'um_slice.jpg')
And this works perfectly, except I am intending to use this code in a for loop. ii is an index to differentiate between each image, and several hundred images would be created so I want them going in the zipfile. Now when I try adding the path to the zipfile:
plt.savefig('/content/slices.zip/'+str(ii)+'um_slice.jpg')
I get: NotADirectoryError: [Errno 20] Not a directory: '/content/slices.zip/150500um_slice.jpg'
I assume it's because the {}.jpg string is a filename, and not a directory per se. But I am quite new to Python, and don't know how to get the plot into the zip file. That's all I want. Would love any advice!

First off, for anything that's not photographic content (ie. nice and soft), JPEG is the wrong format. You'll have a better time using a different file format. PNG is nice for pixels, SVG for vector graphics (in case you embed this in a website later!), PDF for vector, too.
The error message is quite on point: you cannot just save to a zip file as if it was a directory.
Multiple ways around:
use the tempfile module's mkdtemp to make a temporary directory, save into that, and zip the result
save not into a filename, but into a buffer (BytesIO I guess) and append that to the compressed stream (I'm not too familiar with ZipFile)
use PDF as output and simply generate a multipage PDF; it's not hard, and probably much nicer in the long term. You can still convert that vector graphic result to PNG (or any other pixel format9 as desired, but for the time being, it's space efficient, arbitrarily scaleable and keeps all your pages in one place. It's easy to import selected pages into LaTeX (matter of fact, \includegraphics does it directly) or into websites (pdf.js).

From the docs, matplotlib.pyplot.savefig accepts a binary file-like object. ZipFile.open creates binary file like objects. These two have to get todgether!
with zipobj.open(str(ii)+'um_slice.jpg', 'w') as fp:
plt.savefig(fp)

Augmenting images in a dataset - encountering ValueError: Could not find a format to read the specified file in mode 'i'

I'm in a beginner neural networks class and am really struggling.
I have a dataset of images that isn't big enough to train my network with, so I'm trying to augment them (rotate/noise addition etc.) and add the augmented images onto the original set. I'm following the code found on Medium: https://medium.com/#thimblot/data-augmentation-boost-your-image-dataset-with-few-lines-of-python-155c2dc1baec
However, I'm encountering ValueError: Could not find a format to read the specified file in mode 'i'
Not sure what this error means or how to go about solving it. Any help would be greatly appreciated.
import random
from scipy import ndarray
import skimage as sk
from skimage import transform
from skimage import util
path1 = "/Users/.../"
path2 = "/Users/.../"
listing = os.listdir(path1)
num_files_desired = 1000
image = [os.path.join(path2, f) for f in os.listdir(path2) if os.path.isfile(os.path.join(path2, f))]
num_generated_files = 0
while num_generated_files <= num_files_desired:
image_path = random.choice(image)
image_to_transform = sk.io.imread(image_path)
137 if format is None:
138 raise ValueError(
--> 139 "Could not find a format to read the specified file " "in mode %r" % mode
140 )
141
ValueError: Could not find a format to read the specified file in mode 'i'

I can see few possiblities. Before passing to them. I'd like to express what is your error. It's basically an indicator that your images cannot be read by sk.io.imread(). Let me pass to the possible things to do:
Your [os.path.join(path2, f) for f in os.listdir(path2) if os.path.isfile(os.path.join(path2, f))] part may not give the image path correctly. You have to correct it manually. If so, you can manually give the exact folder without doing such kind of a loop. Just simply use os.listdir() and read the files manually.
You can also use glob to read the files that having same extension like .jpg or stuff.
Your files may be corrupted. You can simply eliminate them by using PIL and read the images with PIL like image = Image.open() first and use image.verify() method.
Try to read about sk.io.imread(filename, plugin='' the plugin part may resolve your issue.
Hope it helps.

In python's unittest, how do I mock a fake folder with fake images inside?

I am trying to create a unit test for a function that reads every image from a folder and saves them in a list.
Here is a simplified version of the function:
def read_images(directory):
image_paths = os.listdir(directory)
images = []
for im in image_paths:
images.append(cv2.imread(os.path.join(directory, im)))
return images
This other question brought me close to the solution, but in my case I want the fake files created to be images (basically, arrays) so I can read them with cv2.imread.
My idea is not having to create any temporary folder and, of course, not having to connect with any external folder or database. Is this possible?
Edit: to be clear, I'd like to not have to create temporary folders, nor temporary image files. I'd like to know if there is a way of telling the program: "There is a folder here, and inside it there are some images/arrays with this shape", but with actually not having to create anything in memory.

If you actually need temporary files, you should check tempfile.
It allows you to create temporary files and directories which provide automatic cleanup, so there are no trash files if you use this while having the opportunity to test what you want.
EDIT
If you don't really want to use tempfiles nor tempfolders, here is another solution concerning your problem:
Generate in-memory image for your test.
from io import BytesIO
from PIL import Image
def create_in_memory_image():
in_memory_file = BytesIO()
image = Image.new('RGBA',
size=(0, 0),
color=(155, 0, 0))
image.save(in_memory_file,
'png')
in_memory_file.name = 'tmp_testing_name.png'
in_memory_file.seek(0)
return in_memory_file

how do I mock a fake folder with fake images inside?
def local_cv2_imread():
# use as a side effect
return 'fakeImg1'
def test_read_images(self):
with mock.patch('os.listdir') as mock_listdir:
with mock.patch('package.module.cv2.imread') as mock_imread:
mock_listdir.return_value = ['fake_path']
mock_imread.side_effect = local_cv2_imread
images = read_images('a_real_path')
self.assertEqual(images, ['fakeImg1']

How to load multiple images from folder. PyQt4

I want to be able to load large number of images one by one from the given folder. And also without knowing the names of the each image (only the name of the folder where all images are located). Currently I can load only one image using it's name (pic.jpg):
pixmap = QtGui.QPixmap("pic.jpg")
item = QtGui.QGraphicsPixmapItem(pixmap)
self.scene.addItem(item)
self.scene.update()
Is there any way to do this? Thanks in advance!

The os module contains filesystem access functions.
import os
dir = "dirname"
for file in os.listdir(dir):
... = QtGui.QPixmap(os.path.join(dir, file))
Note: os.path.join is there so you are platform agnostic.