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Open Pull Request #53
polars, fae, unredacter, OpenRGB, forma and Scaling GIPHY - the Legos of Visual Communication
Talk of the week
Scaling GIPHY - the Legos of Visual Communication
Open Source Projects
polars by pola-rs
Fast multi-threaded, hybrid-streaming DataFrame library in Rust | Python | Node.js. Polars is a blazingly fast DataFrames library implemented in Rust using Apache Arrow Columnar Format as the memory model.
⭐ 10.4k 👀 104 🍴 554 🚧 323
fae by wearefine
CMS for Rails. For Reals. Like many Rails CMS engines, Fae delivers all the basics to get you up and running quickly: authentication, authorization, a sleek UI, form helpers, image processing, and workflows. But unlike other engines, Fae's generated models, controllers, and views are built to customize and scale.
⭐ 808 👀 30 🍴 133 🚧 27
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unredacter by @bishopfox
Shows you why you should never ever ever use pixelation as a redaction technique. Decipher redacted images by pixelation
⭐ 6.5k 👀 60 🍴 583 🚧 18
Read More about this Never, Ever, Ever Use Pixelation for Redacting Text
OpenRGB by @CalcProgrammer1
One of the biggest complaints about RGB is the software ecosystem surrounding it. Every manufacturer has their own app, their own brand, their own style. If you want to mix and match devices, you end up with a ton of conflicting, functionally identical apps competing for your background resources. On top of that, these apps are proprietary and Windows-only. Some even require online accounts. What if there was a way to control all of your RGB devices from a single app, on both Windows and Linux, without any nonsense? That is what OpenRGB sets out to achieve.
One app to rule them all.
⭐ 1.5k 👀 34 🍴 101 🚧 3
forma by @GoogleOSS
A (thoroughly) parallelized experimental Rust vector-graphics renderer with both a software (CPU) and hardware (GPU) back-end having the following goals, in this order:
Portability; supporting Fuchsia, Linux, macOS, Windows, Android & iOS.
Performance; making use of compute-focused pipeline that is highly parallelized both at the instruction-level and the thread-level.
Simplicity; implementing an easy-to-understand 4-stage pipeline.
Size; minimizing the number of dependencies and focusing on vector-graphics only.
⭐ 1.5k 👀 10 🍴 23 🚧 15