Gitea might be a bit more popular than OpenCV. We know about 60 links to it since March 2021 and only 52 links to OpenCV. 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.
This reminds me of Gogs [0], where the original author refused a lot of good ideas and improvements, eventually leading to a fork [1] that's now a lot more popular and active than the original. [0] https://gogs.io/ [1] https://gitea.io/en-us/. - Source: Hacker News / about 1 year ago
Yes, we do this using https://gitea.io/en-us/ on a private server. Firewall, backups and a replica running for most projects. Github is only used when it's required by a stakeholder. - Source: Hacker News / about 1 year ago
There's a number of places out there, some of which also support alternatives to Git itself. By no means a complete list and in no particular order: GitLab - https://about.gitlab.com/ Sourcehut - https://sourcehut.org/ Codeberg - https://codeberg.org/ Launchpad - https://launchpad.net/ Debian Salsa - https://salsa.debian.org/public Pagure - https://pagure.io/pagure For self hsoted options, there's these below... - Source: Hacker News / about 1 year ago
And if you need GitLab (for runner, etc...) then it's not too bad to run in Docker. But if anyone is looking for a somewhat simpler git solution, gitea is pretty great. Source: about 1 year ago
Check: Configuration and syntax changes and Special packages. The latter includes changes on PostgreSQL, Python and Gitea. - Source: dev.to / about 1 year ago
How to Accomplish: Use statistical analysis tools and libraries (e.g., Pandas for tabular data) to calculate and visualize these characteristics. For image datasets, custom scripts to analyze object sizes or mask distributions can be useful. Tools like OpenCV can assist in analyzing image properties, while libraries like Pandas and NumPy are excellent for tabular and numerical analysis. To address class... - Source: dev.to / 21 days ago
Open the camera feed — and use the OpenCV library for real-time computer vision processing. - Source: dev.to / about 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
You might be able to achieve this with scripting tools like AutoHotkey or Python with libraries for GUI automation and image recognition (e.g., PyAutoGUI https://pyautogui.readthedocs.io/en/latest/, OpenCV https://opencv.org/). Source: 7 months ago
- [ OpenCV](https://opencv.org/) instead of YoloV8 for computer vision and object detection. Source: 11 months ago
GitLab - Create, review and deploy code together with GitLab open source git repo management software | GitLab
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
GitHub - Originally founded as a project to simplify sharing code, GitHub has grown into an application used by over a million people to store over two million code repositories, making GitHub the largest code host in the world.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
BitBucket - Bitbucket is a free code hosting site for Mercurial and Git. Manage your development with a hosted wiki, issue tracker and source code.
NumPy - NumPy is the fundamental package for scientific computing with Python