Based on our record, NumPy should be more popular than Gitea. It has been mentiond 112 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.
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: Develop a script that iterates over the image database, preprocesses each image according to the model's requirements (e.g., resizing, normalization), and feeds them into the model for prediction. Ensure the script can handle large datasets efficiently by implementing batch processing. Use libraries like NumPy or Pandas for data management and TensorFlow or PyTorch for model inference. Include... - Source: dev.to / 24 days ago
NumPy: This library is fundamental for handling arrays and matrices, such as for operations that involve image data. NumPy is used to manipulate image data and perform calculations for image transformations and mask operations. - Source: dev.to / 24 days ago
NumPy - The fundamental package for scientific computing with Python. NumPy Documentation - Official documentation. - Source: dev.to / 30 days ago
This guide covers the basics of NumPy, and there's much more to explore. Visit numpy.org for more information and examples. - Source: dev.to / about 1 month ago
Below is an example of a code cell. We'll visualize some simple data using two popular packages in Python. We'll use NumPy to create some random data, and Matplotlib to visualize it. - Source: dev.to / 10 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.
OpenCV - OpenCV is the world's biggest computer vision library
BitBucket - Bitbucket is a free code hosting site for Mercurial and Git. Manage your development with a hosted wiki, issue tracker and source code.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.