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How to Increase image quality in streamlit

I am viewing images by using streamlit without converting to RGB below is the line of code which I am using
st.image("image.jpg")
But the problem is I need to read some numbers inside the image but the image is blurred which means that I am not able to read the numbers present in the image.
Increasing the size of the image does not work.

Convert pyglet ColorBufferImage into PIL format

I have a small animation (pyglet) that I am taking a screenshot of that I want to use in a CNN afterwards. At the moment, I have to save a screenshot (ColorBufferImage) and then upload it again directly so that the image is in the correct format for the CNN (PIL format).
For better performance I would skip the whole thing without having to save the image extra. Here is my code:
pyglet.image.get_buffer_manager().get_color_buffer().save('screenshot.png')
image = tensorflow.keras.utils.load_img('screenshot.png',color_mode='rgb',target_size=(256, 256),interpolation='nearest',keep_aspect_ratio=False)

When loading and writing a PNG image to PDF using Pillow (PIL), how do I fix the size of the image in the PDF?

I am reading in a list of PNG images from a directory and I want to maintain the image sizes.
However, when I go to save them, each image is automatically resized to fit the entire page AND it automatically rotates the images to landscape rather than keeping them portrait.
Example of what I am doing below:
from PIL import Image
x = []
# get list of images
for i in [list of image files in my directory]:
im = Image.open(i)
im = im.convert('RGB') # will not save as RGBA
x.append(im)
im.save('my_doc.pdf', save_all=True, append_images=x)
Yet, the images which are all the same dimensions and sized to fit neatly onto a single page in portrait orientation, are being rotated to landscape orientation and stretched to the limits of the page making them blurry as a result.
I want one image per page, using the native dimensions of the images, and in portrait.
Is there a way to prevent PIL from doing this?
Thanks in advance!

How to compress quality of conversion JPG to WebP in Python

I'm trying to convert the jpg images into new generation WebP format. I used PIL for that and everything working perfectly!
But my problem is when the program compresses a JPG file which is 134KB and when it converted into WebP it became 108KB.
How I can shorten the size of the WebP image ?, I want to compress the quality.
My code looks like this:
from PIL import Image
import glob
import os
image = Image.open('my-image.jpg')
image = image.convert('RGB')
image.save('my-image.jpg.webp', 'webp')
Does anybody know how we can again decrease the size of the converted WebP images?

Set the quality parameter while saving the image.
image.save('my-image.jpg.webp', 'webp', optimize = True, quality = 10)
Save the picture with desired quality. To change the quality of image, set the quality variable at your desired level, The more the value of quality variable
and lesser the compression

Using Python. How to save a 4 dimension array (21,32,1024,1024) as a tif image. biomedicine

I want to save an stack of arrays in a tiff file, so a microscopy software can read it in channels and z planes, as images. So this is a 4 dimensions array: (21,32,1024,1024). But I do not find a way.
For example using: io.imsave(os.path.join(outpath), stack2), this is saved as a stack of individual images but not in grups of 32 channels representing the 21 z planes.
do you know any way to achieve that?

Since the TIFF specification does not handle multi-channel Z stacks, additional metadata needs to be saved with the image data. There are two common metadata formats for saving ZCYX images in TIFF for bio-imaging: OME-TIFF and ImageJ hyperstacks. OME-TIFF is supported by more software. Tifffile can read and write both formats:
import numpy
from tifffile import imwrite
image = numpy.zeros((21, 32, 1024, 1024), dtype='uint16')
# write OME-TIFF
imwrite('zcyx.ome.tif', image)
# write ImageJ hyperstack
imwrite('zcyx.tif', image, imagej=True)