Scikit Image might be a bit more popular than GTK. We know about 7 links to it since March 2021 and only 6 links to GTK. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Wha? An example of a barebones GTK JavaScript app is right there on the front page. One click on the bindings link, will send you to the official GNOME-hosted GitLab repo for gjs, which in-turn, has links to official API documentation. Source: over 1 year ago
I think what is lacking is a kind of introduction similar to what you have written in your post now. Myself, I am totally new to GTK. I come as a user of Gnome. All I knew until today was that to develop applications for Gnome, preferably I should use something called GTK. And I heard so much about the recent version that came out - GTK 4. So I started to look for a Getting Started tutorial for GTK 4, to build... Source: about 2 years ago
BTW, I think the GTK team should really step up their game in terms of how to encourage new people into their ecosystem. Seeing that windows screenshot in the official tutorial makes me think I'm dealing with some old technology. Also, the official gtk.org has two separate tutorials that show very similar applications being built. Source: about 2 years ago
Faces of GNOME Faces of GNOME is an initiative to create something similar to People of Mozilla / Mozillians which is a directory of active, current or past GNOME Contributors. Faces of GNOME (Current Demo HERE) aims to give a space for every GNOME Contributor, GNOME Foundation Member and more. It is being designed to showcase the list of current Maintainers, People that spoke at GNOME Conferences/Events, GNOME... Source: over 2 years ago
My advice is to basically learn how to write GTK apps using Python. Source: over 2 years ago
We will use the Hugging Face transformers and diffusers libraries for inference, FiftyOne for data management and visualization, and scikit-image for evaluation metrics. - Source: dev.to / 2 months ago
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. - Source: dev.to / 7 months ago
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/. Source: over 1 year ago
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/. Source: almost 2 years ago
There's probably something in scikit-image to do what you want, or close enough to build on. Source: about 2 years ago
wxWidgets - wxWidgets: Cross-Platform GUI Library
OpenCV - OpenCV is the world's biggest computer vision library
Qt - Powerful, flexible and easy to use, Qt will help you not only meet your tight deadline, but also reduce the maintainable code by an astonishing percentage.
Microsoft Computer Vision API - Extract rich information from images and analyze content with Computer Vision, an Azure Cognitive Service.
PyQt - Riverbank | Software | PyQt | What is PyQt?
Amazon Rekognition - Add Amazon's advanced image analysis to your applications.