trace.moe VS opencv-python

Trace.moe

https://trace.moe/ for the next time with this it is easy to find out the name of a show

trace.moe (2016-today) or formerly known as whatanime.ga (2014-2016) is surprisingly old!

Grisaia no Rakuen Specials, I'll admit I had to search this using https://trace.moe/

It's easy to forget something like that, I just put the screenshot into this site

Other helpful searchtools include saucenao.com for searching the original artist for images uploaded to deviantart, pixiv, and images of full sites from different manga. iqdb.org is helpful for finding the artist for pictures aswell. Tineye.com can be helpful sometimes of an image is cropped. Yandex.com is pretty helpful aswell since that one can sometimes even recognize a character outright and find images with same charater from different angles. trace.moe is especiall useful if you have a screenshot from an anime and want to find what anie it's from.

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!