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How do I make multiple videos of individual images at once using images in a folder? Moviepy -Python

Soooo, I have no clue how to do this and am completely new to python however,
I would like to select all images in a folder and turn them into 10 second individual videos for each image using MoviePy.
but instead of combining all the images together into one video, I want to make multiple videos for each individual image in the folder. From what I know you can use import glob to get all images in the folder but that's about it.
I have tried:
clips = [ImageClip(clip).set_duration(10) for clip in glob("imagesfolder/*.jpg")]
video_clip = concatenate_videoclips(clips, method="compose")
audioclip = AudioFileClip("backgroundmusicforduck.mp3")
new_audio = afx.audio_loop(audioclip, duration=video_clip.duration)
video_clip.audio = new_audio
video_clip.write_videofile("memes.mp4", fps=24, remove_temp=True, codec="libx264", audio_codec="aac")
but all this does is combine all the images together into one video..
Thanks!!!

convert all img in one pdf .?

I would like to finish my script, I tried a lot to solve but being a beginner failed.
I have a function imageio which takes image from website and after that, i would like resize all images in 63x88 and put all my images in one pdf.
full_path = os.path.join(filePath1, name + ".png")
if os.path.exists(full_path):
number = 1
while True:
full_path = os.path.join(filePath1, name + str(number) + ".png")
if not os.path.exists(full_path):
break
number += 1
imageio.imwrite(full_path, im_padded.astype(np.uint8))
os.chmod(full_path, mode=0o777)
thanks for answer

We (ImageIO) currently don't have a PDF reader/writer. There is a long-standing features request for it, which hasn't been implemented yet because there is currently nobody willing to contribute it.
Regarding the loading of images, we have an example for this in the docs:
import imageio as iio
from pathlib import Path
images = list()
for file in Path("path/to/folder").iterdir():
im = iio.imread(file)
images.append(im)
The caveat is that this particular example assumes that you want to read all images in a folder, and that there is only images in said folder. If either of these cases doesn't apply to you, you can easily customize the snippet.
Regarding the resizing of images, you have several options, and I recommend scikit-image's resize function.
To then get all the images into a PDF, you could have a look at matplotlib, which can generate a figure which you can save as a PDF file. The exact steps to do so will depend on the desired layout of your resulting pdf.

How to load many images eficiently from folder using openCV

I try to create my own image datasets for machine learning.
The workflow I thought is the following :
①Load all image files as an array in the folder.
②Label the loaded images
③Split loaded image files to image_data and label_data.
④Finally, split image_data to image_train_data and image_test_data and split label_data to label_train_data and label_test_data.
However, it doesn't go well in the first step(①).
How can I load all image data efficiently?
And if you implement an image data set for machine learning according to this workflow, how you handle it?
I wrote following code.
cat_im = cv2.imread("C:\\Users\\path\\cat1.jpg")
But, Am I forced writing \cat1.jpg , \cat2.jpg ,\cat3.jpg.....?

## you can find all images like extenstion
import os,cv2
import glob
all_images_path= glob.glob('some_folder\images\*png') ## it gives path of images as list
## then you can loop over all files
loaded_images = []
for image_path in all_images_path:
image = cv2.imread(image_path)
loaded_images.append(image)
## lets assume your labels are just name of files and its like cat1.png,cat2.png etc
labels = []
for image_path in all_images_path:
labels.append(os.basename(image_path))

save multi directory images in a single file after preprocessing

I am working on DICOM images, I have 5 scans(folders) each scan contain multiple images, after working some preprocessing on the images, I want to save the processed images in a single file using "np.save", I have the code below that save each folder in a separate file:
data_path = 'E:/jupyter/test/LIDC-IDRI/'
patients_data = os.listdir(data_path)
for pd in range(len(patients_data)):
full_path = load_scan(data_path + patients_data[pd])
after_pixel_hu = get_pixels_hu(full_path)
after_resample, spacing = resample(after_pixel_hu, full_path, [1,1,1])
np.save(output_path + "images_of_%s_patient.npy" % (patients_data[pd]), after_resample)
load_scan is a function for loading(reading) DICOM files, what I want to do with this code is to save all processed images in a single file, not in five files, can anyone tell me how to do that, please?

The first thing to notice is that you are using %s with patients_data[pd]. I assume patients_data is a list of the names of the patients, which means you are constructing a different output path for each patient - you are asking numpy to save each of your processed images to a new location.
Secondly, .npy is probably not the file type you want to use for your purposes, as it does not handle appending data. You probably want to pick a different file type, and then np.save() to the same file path each time.
Edit: Regarding file type, a pdf may be your best option, where you can make each of your images a separate page.

Chunking a directory and applying image blending using PIL. Can't save images correctly with Python

Sorry for the title... So the goal of this script is to take a folder full on images that are listed in a particular order. Then it chunks the images into groups of 3. From there it takes the 3 images and blends them together using PIL. Now the issue that I have is that the code below does a great job of doing what I want. I can show imgbld2 it'll create 4 images in a temporary folder.
Now my problem is that when I go to save the images using imgbld2.save()it will only save the first created image into 4 image files, instead of 4 created images into 4 separate files.
I can fix this issue by pointing another script to retrieve the images from the temp folder by using glob.glob(). But that would require me to make sure to run the script on a freshly restarted computer but that seems to be too messy for my taste.
Is there a better way to achieve what I'm trying to do? Or there a saving method that I'm missing?
Any help would be appreciated, here is the code:
from PIL import Image
import os.path
import glob
#Lists Directory
Dir = os.listdir('/path/to/Directory/of/Images')
#Glob all jpgs
im = glob.glob( '/path/to/Directory/of/Images/*.jpg')
#sort jpg according to name
imsort = sorted(im)
def chunker(imsort,size = 3):
for i in range(0, len(imsort), size):
yield imsort[i:i + size]
print('what does it look like?')
for j in chunker(imsort):
print(j)
img1 = Image.open(j[0])
img2 = Image.open(j[1])
img3 = Image.open(j[2])
imgbld1 = Image.blend(img1, img2, 0.3)
imgbld2 = Image.blend(imgbld1, img3, 0.3)
imgbld2.show()
imgbld2.save('path/to/new/folder/' + 'blended' , 'JPEG')