
GitHub Pages
Vercel
Netlify
Jekyll
Cloudflare Pages
surge.sh
Neocities
tiiny.host
Scikit Image
OpenCV
Microsoft Computer Vision API
Amazon Rekognition
Microsoft Video API
Clarifai
SimpleCV
Cloudinary
GitHub Pages
Scikit ImageBased on our record, GitHub Pages seems to be a lot more popular than Scikit Image. While we know about 504 links to GitHub Pages, we've tracked only 7 mentions of Scikit Image. 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.
The site itself is a statically generated Next.js app, built in CI and deployed to GitHub Pages via actions/deploy-pages. No server to manage, no hosting bill. - Source: dev.to / 4 months ago
Static sites are fast and cheap to host, but your data goes stale the moment you deploy. This post shows how a SvelteKit portfolio site serves live data from five external sources while still deploying as static HTML to GitHub Pages. - Source: dev.to / 4 months ago
All three themes are designed for accessible deployment. You can host them for free on Netlify, GitHub Pages, Vercel, or Cloudflare Pages. The only cost is a domain name (which can be as cheap as $5/year on Porkbun). - Source: dev.to / 5 months ago
This action can store collected benchmark results in GitHub pages branch and provide a chart view. Benchmark results are visualized on the GitHub pages of your project. - Source: dev.to / 10 months ago
But that's not the case. The blog is a simple static generated website using Jekyll, it is built and served through GitHub Pages. With that in mind it makes more sense to use tools and leverage tool calling. - Source: dev.to / 11 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 / about 2 years 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 / over 2 years 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 3 years 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 4 years ago
There's probably something in scikit-image to do what you want, or close enough to build on. Source: about 4 years ago
Vercel - Vercel is the platform for frontend developers, providing the speed and reliability innovators need to create at the moment of inspiration.
OpenCV - OpenCV is the world's biggest computer vision library
Netlify - Build, deploy and host your static site or app with a drag and drop interface and automatic delpoys from GitHub or Bitbucket
Microsoft Computer Vision API - Extract rich information from images and analyze content with Computer Vision, an Azure Cognitive Service.
Jekyll - Jekyll is a simple, blog aware, static site generator.
Amazon Rekognition - Add Amazon's advanced image analysis to your applications.