opencv-python VS chafa

Extra stuff like type checking and annotations are definitely not the reason why python became that popular and widely adapted and used, but it certainly doesn't hurt to add and use them.

To be clear, I'm not expecting people to start adding generics to their quick hacked together Python scripts (in fact please don't do that). Instead, if you're building a library or maintaining a larger Python codebase, a lot of these start becoming very useful. A lot of the typing features I mentioned are already used by Python under the hood, and that a lot of Python developers just take for granted.

Case in point, the python-opencv (https://github.com/opencv/opencv-python) library has basically no types and it's an absolute pain to work with.

BTW thats a really good SO thread, thanks for linking it!

Have you ever felt like your photos needed a little extra touch to stand out? Well, get ready because we're about to learn a cool Python trick! We're going to take ordinary photos and turn them into awesome pencil sketches using Python and OpenCV. This will make your pictures look like they were drawn by hand!

There are several modules that would allow you to process images in Python. Two of the perhaps most famous ones are PIL (https://pypi.org/project/Pillow/, also known as pillow), and opencv (https://pypi.org/project/opencv-python/).

Classifying images with trained model by using OpenCV and Teachable Machine packages

opencv-python: OpenCV for Python

Tool: Data collected using Python opencv, and a rudimentary OCR built from scratch. Graphic created with Microsoft Excel.

cv2: https://pypi.org/project/opencv-python/

I would try installing opencv-python on its own to see if you can learn more: https://pypi.org/project/opencv-python/

I've been googling and reading for a while but I'm very unsure about which tools I need, which tools will help me achieve what I want the easiest way. What about (pylivestream)[https://pypi.org/project/pylivestream/] for example? Will this do the job for me? What about a lower level approach including (pyopencv)[https://pypi.org/project/opencv-python/]? What about a higher level approach using (vidgear)[https://github.com/abhiTronix/vidgear], which seems promising but I don't feel confident in assessing if it's the tool I really need?

This is likely to be buggy and frustrating, and it's very likely that you'll need to use OpenCV to preprocess the screenshot. Not my idea of a good time!

A few months ago, I came across Chafa — a command-line tool that turns images into ANSI/ASCII art. If you’ve never tried it, it’s kind of brilliant. You point it at a PNG or JPEG, and it spits out a wall of colored text that looks eerily close to the original image — all using braille, Unicode blocks, or ASCII characters.

Like some people here and under this post said, I like Kitty and would recommend it to anyone who uses/used Alacritty, as they are very similar in surface. I actually switch between Alacritty and Kitty pretty often, depending on my "mood". I recently went back to Kitty for image support (through chafa though, for better compatibility across terminal emulators). However, Wayland support is poor and I have some issues with fonts being too bold, although it could just be my config...

If you use a more modern terminal you can also use stuff like:

https://hpjansson.org/chafa/

There's also https://github.com/princejoogie/chafa.nvim, which wraps https://github.com/hpjansson/chafa Did you know about that? I wonder what the differences between your plugin and that one are?

Hello r/Python! I'm here to introduce you to a project I've been working on called chafa.py source. These are Python bindings for the amazing terminal image visualizer Chafa.

this is a plugin that wraps the functionality of chafa into neovim. chafa is a way to display images in the terminal by converting it into ANSI escape sequences.

I guess it is using https://github.com/hpjansson/chafa for that, and it needs to be using https://github.com/seebye/ueberzug/tree/2c55173878906c3b221cdef16cf083f0c412bb58

Chafa: Terminal Graphics for the 21st Century\ (13 comments)