pillow VS scikit-image

"down" could be a good name for a python image library plugin/extension.

https://github.com/python-pillow/Pillow

The final image is a created using the Pillow Python imaging library, and is comprised of

I've been searching for Native Python Support of JXL and the latest posts (Pillow 1, Pillow 2) and packages are from about 2 years ago.

I may have sent you on a bit of a wild goose chase here, sorry mate.. It appears like PIL may not use libpng at all, or that it is only used on Windows for some reason. There is PngImagePlugin written in pure python and uses zlib: https://github.com/python-pillow/Pillow/blob/main/src/PIL/PngImagePlugin.py

Pillow - https://github.com/python-pillow/Pillow

but the Python Pillow library cannot

I was able to build a simple base image using Canva. Then, I overlayed the text using Pillow. Working with text on images is somwhat complicated to get perfect so I opted to create 4 categories and a ratio for each one.

Lets break down the problem space (this should be your first step with any program anyway). You'd need something that can sample pixel data from your display. For that I'd use something like Pillow. Then, for generating your simulated input events (mouse clicks/movement, keypresses, etc...) something like Pynput should suffice.

No because I dont need. I use this packages for my frontend. Pillow==6.2.1  # https://github.com/python-pillow/Pillow django-versatileimagefield==1.11 # https://pypi.org/project/django-versatileimagefield/ django-imagekit==4.0.2 # https://pypi.org/project/django-imagekit/

Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks.

scikit hog library: https://github.com/scikit-image/scikit-image/blob/main/skimage/feature/_hog.py#L302 , https://github.com/scikit-image/scikit-image/blob/main/skimage/feature/_hoghistogram.pyx

This is a good cv deep learning book with python examples https://www.manning.com/books/deep-learning-for-vision-systems. If you're pretty comfortable with the concepts of traditional image processing this is a good companion to cv2 (so you don't have to reinvent the wheel) https://scikit-image.org/

Also, don't know if you're familiar with Python, but if you need ideas for to implement for future directions : https://scikit-image.org/

There's probably something in scikit-image to do what you want, or close enough to build on.

Scikit-image The Scikit-image library is a collection of image processing algorithms that are designed to be easy to use and understand. It includes algorithms for common tasks like edge detection, feature extraction, and image restoration. If you are just starting out in image processing, then this is a good library to check out!

Python is a general-purpose programming language that provides many image processing libraries for adding image processing capabilities to digital images. Some of the most common image processing libraries in Python are OpenCV, Python Imaging Library (PIL), Scikit-image etc.

Then you would need to find what this plugin does for imshow. First thing you can see is that "interpolation" is not "bicubic" as you used, but "nearest"… but there are other settings here that are responsible for the difference of displays. (it's better that you look at the source code in your environment, as it might be slightly different)