Search Results for "win-builds" - Page 5
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Showing 207 open source projects for "win-builds"
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ArkID
Enterprise IDaaS/IAM platform system
Rich plug-in, quickly builds an exclusive IDaaS/IAM platform. Easy integration into all your applications. Unified identity, certification, and authority management system. Extendable bottom application architecture based on Plug-in interpolation. You can flexibly and quickly add new functions to the main program without changing the main program. Achieve centralized and safe storage of corporate organizational structure and identity information of massive personnel. -
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PixelBuilds
Latest Android builds from PixelBoot.
Builds and images, yet to be tested, both stable and unstable from several different custom ROMs, with different changes in source code for further experimentations to fix build bugs and issues. If installing on your own personal device, proceed with caution, and kindly follow instructions given by builder. -
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Ungoogled Chromium Android
Android build for ungoogled-chromium
Ungoogled Chromium Android is the Android platform build configuration and support tooling for Ungoogled Chromium on mobile devices, enabling privacy-minded users and developers to compile a version of the Chromium browser for Android that excludes Google-dependent services, telemetry, and tracking. This repository contains platform-specific patches, build targets, and integration scripts to adapt the upstream Chromium source for Android while eliminating components like Google Play Services... -
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RetroPie-Setup
Shell script to set up a Raspberry Pi/Odroid/PC
RetroPie‑Setup is a collection of shell scripts designed to install and configure RetroPie—an emulation frontend—on Raspberry Pi OS, Ubuntu, Odroid, or PC platforms. It automates installing RetroArch, emulator cores, configuring controllers, themes, and optional ports. Used for retro gaming on varied hardware. -
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Transarctica Remake
Open source revival of the game Transarctica / Arctic Baron
The main goal of the project to offer the original game's full functionality. Roam a hostile frozen world in a futuristic steampunk train, fight exciting train battles and try to stay alive against all odds while searching for clues about the "Sun". -
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Interpret-Text
State-of-the-art explainers for text-based machine learning models
A library that incorporates state-of-the-art explainers for text-based machine learning models and visualizes the result with a built-in dashboard. Interpret-Text builds on Interpret, an open source python package for training interpretable models and helping to explain blackbox machine learning systems. We have added extensions to support text models. Interpret-Text incorporates community-developed interpretability techniques for NLP models and a visualization dashboard to view the results. Users can run their experiments across multiple state-of-the-art explainers and easily perform comparative analysis on them. ... -
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Mocking Bird
Clone a voice in 5 seconds to generate arbitrary speech in real-time
MockingBird is an open-source voice cloning and real-time speech generation toolkit that lets you clone a speaker’s voice from a short audio sample (reportedly as little as 5 seconds) and then synthesize arbitrary speech in that voice. It builds on deep-learning based TTS / voice-cloning technology (in the lineage of projects such as Real-Time-Voice-Cloning), but extends it with support for Mandarin Chinese and multiple Chinese speech datasets — broadening its applicability beyond English. The codebase is implemented in Python (with PyTorch) and includes modules for encoder, synthesizer, vocoder, preprocessing, and inference, as well as demo scripts and a web-server interface for easier experimentation or deployment. ... -
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SageMaker TensorFlow Serving Container
A TensorFlow Serving solution for use in SageMaker
SageMaker TensorFlow Serving Container is an a open source project that builds docker images for running TensorFlow Serving on Amazon SageMaker. Some of the build and tests scripts interact with resources in your AWS account. Be sure to set your default AWS credentials and region using aws configure before using these scripts. Amazon SageMaker uses Docker containers to run all training jobs and inference endpoints. -
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Opyrator
Turns your machine learning code into microservices with web API
...Deploy and access your services via HTTP API or interactive UI. Seamlessly export your services into portable, shareable, and executable files or Docker images. Opyrator builds on open standards - OpenAPI, JSON Schema, and Python type hints - and is powered by FastAPI, Streamlit, and Pydantic. It cuts out all the pain for productizing and sharing your Python code - or anything you can wrap into a single Python function. An Opyrator-compatible function is required to have an input parameter and return value based on Pydantic models. ... -
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DensePose
A real-time approach for mapping all human pixels of 2D RGB images
...DensePose is widely used in augmented reality, motion capture, virtual try-on, and visual effects applications because it enables real-time 3D human mapping from 2D inputs. The model architecture builds on Mask R-CNN, using additional regression heads to predict UV coordinates that map image pixels to 3D surfaces. -
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Atgen A2 Automation
Atgen A2 is a radically simple Workload Automation & Scheduling tool.
Atgen A2 is a radically simple IT automation solution that automates application builds, continuous testing, data parsing & processing, report generation, batch processing, job scheduling, and many other IT needs. Avoid running repetitive batch jobs and managing access to deploy and update your applications — automate in a language that approaches plain English, using SSH or WinRM, with no agents to install on remote systems. https://www.atgensoft.com/ You can install a released version of Atgen A2 via package manager(yum) by downloading latest release. ... -
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FontForge Windows builds
Unofficial Windows builds of FontForge
The aim of this project is to compile up-to-date Windows builds of FontForge. For 'stable' builds, see https://github.com/fontforge/fontforge/releases The build system used was based off that offered by Matthew Petroff (http://www.mpetroff.net/software/fontforge-windows/), but has since been practically rewritten. New in 11/07/2020: * Synced with the 20201107 release. New in 06/04/2020: * Updated to latest master, picks up a clipboard copying fix New in 14/03/2020: * Synced with the 20200314 release. ... -
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Multi-Agent Emergence Environments
Environment generation code for the paper "Emergent Tool Use"
...It was designed for the experiments described in the paper and blog post “Emergent Tool Use from Multi-Agent Autocurricula”, which investigated how complex cooperative and competitive behaviors can evolve through self-play. The repository provides environment generation code that builds on the mujoco-worldgen package, enabling dynamic creation of simulated physical environments. Developers can construct custom environments by combining modular components such as Boxes, Ramps, and RandomWalls using a flexible layering approach that reduces code duplication. The framework includes several predefined environments—such as Hide and Seek, Box Locking, Blueprint Construction, and Shelter Construction—that model distinct problem-solving and collaboration scenarios. -
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Consistent Depth
We estimate dense, flicker-free, geometrically consistent depth
Consistent Depth is a research project developed by Facebook Research that presents an algorithm for reconstructing dense and geometrically consistent depth information for all pixels in a monocular video. The system builds upon traditional structure-from-motion (SfM) techniques to provide geometric constraints while integrating a convolutional neural network trained for single-image depth estimation. During inference, the model fine-tunes itself to align with the geometric constraints of a specific input video, ensuring stable and realistic depth maps even in less-constrained regions. ... -
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HyperGAN
Composable GAN framework with api and user interface
A composable GAN built for developers, researchers, and artists. HyperGAN builds generative adversarial networks in PyTorch and makes them easy to train and share. HyperGAN is currently in pre-release and open beta. Everyone will have different goals when using hypergan. HyperGAN is currently beta. We are still searching for a default cross-data-set configuration. Each of the examples supports search. Automated search can help find good configurations. -
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VideoPose3D
Efficient 3D human pose estimation in video using 2D keypoint
VideoPose3D is a deep learning framework that reconstructs 3D human poses from 2D keypoint sequences extracted from videos. It builds on top of convolutional and temporal networks that map 2D joint coordinates over time to consistent 3D skeletons, enabling robust motion capture without specialized sensors. The model is trained on large motion capture datasets and can generalize well to unseen environments by leveraging temporal context for smoothing and error correction. -
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repo2docker GitHub Action
A GitHub action to build data science environment images
Trigger repo2docker to build a Jupyter enabled Docker image from your GitHub repository and push this image to a Docker registry of your choice. This will automatically attempt to build an environment from configuration files found in your repository. Images generated by this action are automatically tagged with both latest and <SHA> corresponding to the relevant commit SHA on GitHub. Both tags are pushed to the Docker registry specified by the user. If an existing image with the latest tag... -
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AdaNet
Fast and flexible AutoML with learning guarantees
AdaNet is a TensorFlow framework for fast and flexible AutoML with learning guarantees. AdaNet is a lightweight TensorFlow-based framework for automatically learning high-quality models with minimal expert intervention. AdaNet builds on recent AutoML efforts to be fast and flexible while providing learning guarantees. Importantly, AdaNet provides a general framework for not only learning a neural network architecture but also for learning to the ensemble to obtain even better models. At each iteration, it measures the ensemble loss for each candidate, and selects the best one to move onto the next iteration. ... -
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StellarGraph
Machine Learning on Graphs
...StellarGraph is built on TensorFlow 2 and its Keras high-level API, as well as Pandas and NumPy. It is thus user-friendly, modular and extensible. It interoperates smoothly with code that builds on these, such as the standard Keras layers and scikit-learn. -
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DepHell
Python project management. Manage packages
DepHell is a Python packaging and dependency management tool that aims to unify and simplify the Python packaging ecosystem. It can convert between various formats (Pipfile, poetry, setup.py, etc.), manage virtual environments, and ensure reproducible builds. It's a powerful tool for Python developers juggling complex dependencies. -
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SMAC
SMAC: The StarCraft Multi-Agent Challenge
SMAC (StarCraft II Multi-Agent Challenge) is a benchmark environment for cooperative multi-agent reinforcement learning (MARL), based on real-time strategy (RTS) game scenarios in StarCraft II. It allows researchers to test algorithms where multiple units (agents) must collaborate to win battles against built-in game AI opponents. SMAC provides a controlled testbed for studying decentralized execution and centralized training paradigms in MARL. -
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Vega Strike is a 3d OpenGL Action Space Sim for Win/Lin/Mac allowing players to trade, bounty hunt, or explore in a vast universe. Active development is now on https://github.com/vegastrike and on http://www.vega-strike.org Vega Strike is mod ready and network playable.
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setupjavax
Provides Java and integrated Jython/Pyhon + Java builds
...The current release supports the following commands, additional are coming soon: - build_java - Java build and packaging for Python. Supports Java packaging for Python projects, adds native Java modules for Jython. - build_jy - Integrated Python and Java builds for Jython. Supports combined Java and Python / Jython packaging. Calls build_py and build_java. -
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TF Quant Finance
High-performance TensorFlow library for quantitative finance
...Users can value options and fixed-income instruments, simulate paths, fit curves, and calibrate models while leveraging TensorFlow’s jit compilation and automatic differentiation. The codebase is organized as modular math and finance primitives so you can combine building blocks or target end-to-end examples. It includes Bazel builds, tests, and example notebooks to accelerate learning and adoption in real workflows. With hardware acceleration and differentiable models, it enables modern techniques like gradient-based calibration and end-to-end learning of market dynamics. -
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setupdocx
Multidocument automation by templates - for sphinx, mkdocs, epydoc ...
...The provided commands are distributed as entry points and optional base classes for further customization into 'setup.py' - setuptools / distutils. Manages arbitrary document templates for the supported builder, supports multiple builds with arbitrary document layouts, designs, and patched contents. The current release supports the following commands: - build_docx - Enhanced documentation. - install_docx - Installs local documentation. - dist_docx - Documentation packaging. - build_apidoc - Standalone Generator for API Documentation - build_apiref - Standalone Generator for API Reference
