
Logseq
Obsidian.md
Notion
Joplin
Roam Research
Anytype.io
Evernote
Trilium Notes
Scikit Image
OpenCV
Microsoft Computer Vision API
Amazon Rekognition
Microsoft Video API
Clarifai
SimpleCV
Cloudinary
Logseq
Scikit ImageBased on our record, Logseq seems to be a lot more popular than Scikit Image. While we know about 300 links to Logseq, 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.
Using Logseq[1][2] for years and quite happy with it, especially since it has apps for tablets/iPad and phones as well, while being completely FOSS. [1] https://logseq.com/ [2] https://github.com/logseq/logseq. - Source: Hacker News / 12 days ago
Choose a local Markdown tool like Obsidian, Logseq, Foam, or Tolaria to store all your knowledge as plain .md files you own and control. - Source: dev.to / 3 months ago
I should call out another thing that convinced me was a user of forgetful (twsta) posted in the discord a skill for managing wok and todos from how they used to use Logseq. - Source: dev.to / 5 months ago
The Zettelkasten method is a knowledge management system that helps organise ideas effectively. I believe this system would work well for myself, so I have been looking at applications such a Logseq and Zettlr as a result. I am currently using a Wiki-style solution in Zim, however. - Source: dev.to / 7 months ago
I am a fan of Logseq [0] as well, although itโs slightly different in that it is mostly for bulleted notes and not long-form prose. [0]: https://logseq.com/. - 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 / over 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: over 4 years ago
Obsidian.md - A second brain, for you, forever. Obsidian is a powerful knowledge base that works on top of a local folder of plain text Markdown files.
OpenCV - OpenCV is the world's biggest computer vision library
Notion - All-in-one workspace. One tool for your whole team. Write, plan, and get organized.
Microsoft Computer Vision API - Extract rich information from images and analyze content with Computer Vision, an Azure Cognitive Service.
Joplin - Joplin is a free, open source note taking and to-do application, which can handle a large number of notes organised into notebooks. The notes are searchable, tagged and modified either from the applications directly or from your own text editor.
Amazon Rekognition - Add Amazon's advanced image analysis to your applications.