Based on our record, Kivy should be more popular than Scikit Image. It has been mentiond 46 times since March 2021. 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.
We will create this complete Python registration form using Kivy. We get started by installing Kivy, a powerful Python framework for building interactive applications. - Source: dev.to / 3 months ago
For reference, YouTube runs on Python[1,2,3]: > 1. Python and Django: YouTube’s backend is predominantly written in Python, offering a balance of performance and readability. > 2. Google Cloud Platform... > 3. Java and C++: YouTube also utilizes Java and C++ for specific backend services, as they provide better performance for certain tasks. --- A long time ago, I looked into these Python frameworks: -... - Source: Hacker News / 4 months ago
I suggest you use kivy which is suitable for the desktop but also has the advantage of being one of few options for creating Python based native(ish) mobile apps (for IoS and Android app stores). Source: 7 months ago
I think the best one right now for python is "beeware": https://beeware.org/ You also have Kivy which is prety good: https://kivy.org/. - Source: Hacker News / 7 months ago
I'm a big fan of https://kivy.org/ it looks modern and has a wide range of components. - Source: Hacker News / 10 months 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
Blender - Blender is the open source, cross platform suite of tools for 3D creation.
OpenCV - OpenCV is the world's biggest computer vision library
Unity - The multiplatform game creation tools for everyone.
Microsoft Computer Vision API - Extract rich information from images and analyze content with Computer Vision, an Azure Cognitive Service.
Unreal Engine - Unreal Engine 4 is a suite of integrated tools for game developers to design and build games, simulations, and visualizations.
Amazon Rekognition - Add Amazon's advanced image analysis to your applications.