Search Results for "u-breadlybread"
Sort By:
Showing 425 open source projects for "u-breadlybread"
View related business solutions-
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
Gemini 3 and 200+ AI Models on One PlatformBuild generative AI apps with Vertex AI. Switch between models without switching platforms.
-
1
u-root
A fully Go userland with Linux bootloaders
A fully Go userland with Linux bootloaders! u-root can create a one-binary root file system (initramfs) containing a busybox-like set of tools written in Go. -
2
U++
C++ framework with an ide.
U++ is BSD licensed C++ cross-platform rapid application development framework focused on programmers productivity without sacrificing runtime performance. Based on strictly deterministic design it provides an alternative to GC collected platforms. -
3
Cemu Wii U emulator
Cemu is a Wii U emulator
Software to emulate Wii U games and applications on PC. Currently, the DRC (GamePad), Pro Controller, and Classic Controller is emulated. Wiimotes are emulated as well (including native support). Keyboard input + USB controllers as input devices are supported. GamePad touch input can be controlled via a left mouse click. Gyro functionality is emulated with limitations and can be controlled via the right mouse button. -
4
rembg
Rembg is a tool to remove images background
Rembg is a powerful tool that utilizes AI (specifically U^2-Net) to automatically remove backgrounds from images, offering a streamlined command-line interface and Docker support. It's ideal for batch processing and integrates smoothly into workflows -
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
5
x-unet
Implementation of a U-net complete with efficient attention
Implementation of a U-net complete with efficient attention as well as the latest research findings. For 3d (video or CT / MRI scans). -
6
ani-cli
A cli tool to browse and play anime
...This tool scrapes the site gogoplay. If you encounter "Video URL not found" or any breaking issue, then make sure you are on the latest version by typing sudo ani-cli -U to update on Linux, Mac, and Android. On Windows, run gitbash as administrator then their type ani-cli -U. If after this the issue persists then open an issue. If you see sed warnings or your history entries have disappeared after updating, then update your history file with the history transition script. -
7
uSDR
Simple lightweight (micro) SDR receiver software
uSDR is a general purpose multimode software defined radio receiver Windows application. "u" (μ) means micro becuase of lightweight binaries distributive, simple and compact user interface, highly optimized DSP routines to minimize CPU usage. Compatible with RTL-SDR, AirSpy, BladeRF, HackRF, LimeSDR, Fobos SDR frontends. Able to perform input IQ streaming, base band and pass band recording, play back, demodulation, spectrum and waterfall visualization, animated spectrum navigation, fast zoom and pan. ... -
8
uAVD
Analog Video Decoder application software
The basic capabilities: - obtain IQ passband stream from the uSDR host application via uSDR-TCP link - demodulate and decode the video data within a software - visualize a picture Supported modulations: - AM (broadcast analog television) - FM (FPV drone video links) - RAW (composite output from VHS, camcorders, game consoles ...) Supported formats: - NTSC - PAL - SECAM Supported modes: - GrayScale - Full color picture ! Educational and entertainment purposes only ! -
9
UEFI_MULTI
UEFI_MULTI - Make Multi-Boot USB-Drive
...Make Bootable USB Drive with MBR and 2 Partitions. UEFI Secure boot support requires Format Drive using Grub2 as EFI Manager. Copy and Rename your Linux ISO files to folder images on FAT32 USB Boot drive U-BOOT. -
Catch Bugs Before Your Customers DoMove from alert to fix before users notice. AppSignal monitors errors, performance bottlenecks, host health, and uptime—all from one dashboard. Instant notifications on deployments, anomaly triggers for memory spikes or error surges, and seamless log management. Works out of the box with Rails, Django, Express, Phoenix, Next.js, and dozens more. Starts at $23/month with no hidden fees.
-
10
S.U.P.E.R.M.A.N.
S.U.P.E.R.M.A.N. optimizes the macOS software update experience
super is a compact, high-performance tiling window manager for macOS that offers keyboard-driven workflow efficiency similar to tiling window managers found in Linux environments like i3 or dwm. Written in Swift, super leverages macOS APIs to allow users to manage windows in grid-like patterns, enabling rapid arrangement, resizing, and navigation without reaching for the mouse. It’s ideal for developers, power users, and keyboard-centric users who want to boost productivity within macOS’s... -
11
Video Diffusion - Pytorch
Implementation of Video Diffusion Models
Implementation of Video Diffusion Models, Jonathan Ho's new paper extending DDPMs to Video Generation - in Pytorch. Implementation of Video Diffusion Models, Jonathan Ho's new paper extending DDPMs to Video Generation - in Pytorch. It uses a special space-time factored U-net, extending generation from 2D images to 3D videos. 14k for difficult moving mnist (converging much faster and better than NUWA) - wip. Any new developments for text-to-video synthesis will be centralized at Imagen-pytorch. For conditioning on text, they derived text embeddings by first passing the tokenized text through BERT-large. ... -
12
Cemu Graphic Packs
Community Graphic Packs for Cemu
Use Cemu's built-in graphic packs downloader (a feature added in Cemu 1.15.1) to automatically retrieve the newest graphic packs from our repository. Remove all of your graphic packs first, then move all of the folders from a downloaded .zip below to the graphicPacks folder from your Cemu folder. Choose one of the 3 downloads from above. Each download has a range of versions it supports, pick the one that’s supported by your downloaded Cemu version. Some graphic packs might not be available... -
13
-
14
NeuralOperators.jl
DeepONets, Neural Operators, Physics-Informed Neural Ops in Julia
...Instead of solving by finite element method, a PDE problem can be resolved by training a neural network to learn an operator mapping from infinite-dimensional space (u, t) to infinite-dimensional space f(u, t). Neural operator learns a continuous function between two continuous function spaces. The kernel can be trained on different geometry, which is learned from a graph. Fourier neural operator learns a neural operator with Dirichlet kernel to form a Fourier transformation. It performs Fourier transformation across infinite-dimensional function spaces and learns better than neural operators. ... -
15
yt-dlp
A youtube-dl fork with additional features and fixes
yt-dlp is a youtube-dl fork based on the now inactive youtube-dlc. The main focus of this project is adding new features and patches while also keeping up to date with the original project -
16
DynamicQuantities.jl
Lightweight + fast physical quantities in Julia
DynamicQuantities defines a simple statically-typed Quantity type for Julia. Physical dimensions are stored as a value, as opposed to a parametric type, as in Unitful.jl. This can greatly improve both runtime performance, by avoiding type instabilities, and startup time, as it avoids overspecializing methods. -
17
Meridian
Meridian is an MMM framework
...The framework provides a robust foundation for constructing in-house MMM pipelines capable of handling both national and geo-level data, with built-in support for calibration using experimental data or prior knowledge. Meridian uses the No-U-Turn Sampler (NUTS) for Markov Chain Monte Carlo (MCMC) sampling to produce statistically rigorous results, and it includes GPU acceleration to significantly reduce computation time. -
18
diff-so-fancy
Make your diffs human readable instead of machine readable
diff-so-fancy strives to make your diffs human readable instead of machine readable. This helps improve code quality and helps you spot defects faster. diff-so-fancy is also available from NPM, Nix, brew, and as a package on Arch and Debian Linux. Windows users may need to install MinGW or the Windows subsystem for Linux. By default, the separator for the file header uses Unicode line-drawing characters. If this is causing output errors on your terminal, set this to false to use ASCII... -
19
DynamicHMC
Implementation of robust dynamic Hamiltonian Monte Carlo methods
Implementation of robust dynamic Hamiltonian Monte Carlo methods in Julia. In contrast to frameworks that utilize a directed acyclic graph to build a posterior for a Bayesian model from small components, this package requires that you code a log-density function of the posterior in Julia. Derivatives can be provided manually, or using automatic differentiation. Consequently, this package requires that the user is comfortable with the basics of the theory of Bayesian inference, to the extent... -
20
The Aura Package Manager
A secure, multilingual package manager for Arch Linux
...-S yields pacman packages and only pacman packages. This agrees with the above. In Aura, the -A operation is introduced for obtaining AUR packages. -A comes with sub-options you're used to (-u, -s, -i, etc.). PKGBUILDs from the AUR can contain anything. It's a user's responsibility to verify the contents of a PKGBUILD before building, but people can make mistakes and overlook details. -
21
Pytorch-toolbelt
PyTorch extensions for fast R&D prototyping and Kaggle farming
A pytorch-toolbelt is a Python library with a set of bells and whistles for PyTorch for fast R&D prototyping and Kaggle farming. Easy model building using flexible encoder-decoder architecture. Modules: CoordConv, SCSE, Hypercolumn, Depthwise separable convolution and more. GPU-friendly test-time augmentation TTA for segmentation and classification. GPU-friendly inference on huge (5000x5000) images. Every-day common routines (fix/restore random seed, filesystem utils, metrics). Losses:... -
22
LatentSync
Taming Stable Diffusion for Lip Sync
...In effect, given a source video (with masked or reference frames) and an audio track, LatentSync directly generates frames whose lip motions and expressions align with the audio, producing convincing talking-head or animated lip-sync output. The system leverages a U-Net diffusion backbone, with cross-attention of audio embeddings (via an audio encoder) and reference video frames to guide generation, and applies a set of loss functions (temporal, perceptual, sync-net based) to enforce lip-sync accuracy, visual fidelity, and temporal consistency. Over versions, LatentSync has improved temporal stability and lowered resource requirements — making inference more practical (e.g. 8 GB VRAM for earlier versions, somewhat higher for latest models). -
23
Casual Suite
An umbrella package to support a single install point
...As an older version of Transient is built-in to the Emacs release, the package manager package.el will not update this package unless the customizable variable package-install-upgrade-built-in is set to t. Set this variable and proceed with installing Casual Suite. Alternately invoking package-install with a prefix (C-u) will temporarily coerce the update of the built-in package. -
24
Serf
Service orchestration and management tool
...The Serf library is independent of the command line agent, serf. The serf binary is located under cmd/serf and can be installed stand alone by issuing the command go get -u github.com/hashicorp/serf/cmd/serf. -
25
Imagen - Pytorch
Implementation of Imagen, Google's Text-to-Image Neural Network
Implementation of Imagen, Google's Text-to-Image Neural Network that beats DALL-E2, in Pytorch. It is the new SOTA for text-to-image synthesis. Architecturally, it is actually much simpler than DALL-E2. It consists of a cascading DDPM conditioned on text embeddings from a large pre-trained T5 model (attention network). It also contains dynamic clipping for improved classifier-free guidance, noise level conditioning, and a memory-efficient unit design. It appears neither CLIP nor prior...
