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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])

Unable To Convert PDF to Text format

I am getting this error while parsing the PDF file using pypdf2
i am attaching PDF along with the error.
I have attached the PDF to be parsed please click to view
Can anyone help?
import PyPDF2
def convert(data):
pdfName = data
read_pdf = PyPDF2.PdfFileReader(pdfName)
page = read_pdf.getPage(0)
page_content = page.extractText()
print(page_content)
return (page_content)
error:
PyPDF2.utils.PdfReadError: Expected object ID (8 0) does not match actual (7 0); xref table not zero-indexed.

There are some open source OCR tools like tesseract or openCV.
If you want to use e.g. tesseract there is a python wrapper library called pytesseract.
Most of OCR tools work on images, so you have to first convert your PDF into an image file format like PNG or JPG. After this you can load your image and process it with pytesseract.
Here is some sample code how you can use pytesseract, let's suppose you have already converted your PDF to an image with filename pdfName.png:
from PIL import Image
import pytesseract
def ocr_core(filename):
"""
This function will handle the core OCR processing of images.
"""
text = pytesseract.image_to_string(Image.open(filename)) # We'll use Pillow's Image class to open the image and pytesseract to detect the string in the image
return text
print(ocr_core('pdfName.png'))

How to find a file/ data from a given data set in python- opencv image processing project?

I have a data set of images in an image processing project. I want to input an image and scan through the data set to recognize the given image. What module/ library/ approach( eg: ML) should I use to identify my image in my python- opencv code?

To find exactly the same image, you don't need any kind of ML. The image is just an array of pixels, so you can check if the array of the input image equals that of an image in your dataset.
import glob
import cv2
import numpy as np
# Read in source image (the one you want to match to others in the dataset)
source = cv2.imread('test.jpg')
# Make a list of all the images in the dataset (I assume they are images in a directory)
filelist = glob.glob(r'C:\Users\...\Images\*.JPG')
# Loop through the images, read them in and check if an image is equal to your source
for file in filelist:
img = cv2.imread(file)
if np.array_equal(source, img):
print("%s is the same image as source" %(file))
break

Convert .h5 file to .jpg with Python

I currently have a .h5 file containing grayscale imagery. I need to convert it to a .jpg.
Does anybody have any experience with this?
Note: I could possible convert the h5 file to a numpy array and then use an external library like pypng to convert that to a png. But I am wondering if there is a more efficient way to convert to an image, and preferrably a .jpg.

Key ingredients:
h5py to read the h5 file.
Determine the format of your image and use PIL.
Let us suppose it's RGB format (https://support.hdfgroup.org/products/java/hdfview/UsersGuide/ug06imageview.html)
Suppose your image is located at Photos/Image 1 then you can do.
import h5py
import numpy as np
from PIL import Image
hdf = h5py.File("Sample.h5",'r')
array = hdf["Photos/Image 1"][:]
img = Image.fromarray(array.astype('uint8'), 'RGB')
img.save("yourimage.thumbnail", "JPEG")
img.show()

Extracting images from matlab file

I'm trying to extract the images (and its label and such) from an RGB-D dataset called NYUV2 dataset. (I downloaded the labelled dataset)
It's a matlab file so I tried using hdf5 to read it but I don't know how to proceed from here. How do I save the images and its corresponding labels and depths into a different folder??
Here's the script that I used and its corresponding output.
import numpy as np
import h5py
f = h5py.File('nyu_depth_v2_labeled.mat','r')
k = list(f.keys())
print(k)
Output is
['#refs#', '#subsystem#', 'accelData', 'depths', 'images', 'instances', 'labels', 'names', 'namesToIds', 'rawDepthFilenames', 'rawDepths', 'rawRgbFilenames', 'sceneTypes', 'scenes']

I hope this helps.
I suppose you are using the PIL package The function fromarray expects the "mode of the image" see https://pillow.readthedocs.io/en/3.1.x/handbook/concepts.html#concept-modes
I suppose your image is in RGB. I believe the image souhld be under group 'images' and dataset image_name
Therefore
import h5py
import numpy as np
from PIL import Image
hdf = h5py.File('nyu_depth_v2_labeled.mat','r')
array = np.array(list(hdf.get("images/image_name")))
img = Image.fromarray(array.astype('uint8'), 'RGB')
img.show()
You can also look at another answer I gave to know how to save images
Images saved as HDF5 arent colored
To view the content of the h5 file, download HDFview, it will help navigate through it.