Search Results for "windows control"
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Showing 29 open source projects for "windows control"
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1
DeepFaceLive
Real-time face swap for PC streaming or video calls
You can swap your face from a webcam or the face in the video using trained face models. There is also a Face Animator module in DeepFaceLive app. You can control a static face picture using video or your own face from the camera. The quality is not the best, and requires fine face matching and tuning parameters for every face pair, but enough for funny videos and memes or real-time streaming at 25 fps using 35 TFLOPS GPU. -
2
Bullet Physics SDK
Real-time collision detection and multi-physics simulation for VR
This is the official C++ source code repository of the Bullet Physics SDK: real-time collision detection and multi-physics simulation for VR, games, visual effects, robotics, machine learning etc. We are developing a new differentiable simulator for robotics learning, called Tiny Differentiable Simulator, or TDS. The simulator allows for hybrid simulation with neural networks. It allows different automatic differentiation backends, for forward and reverse mode gradients. TDS can be trained... -
3
CARLA Simulator
Open-source simulator for autonomous driving research.
CARLA has been developed from the ground up to support development, training, and validation of autonomous driving systems. In addition to open-source code and protocols, CARLA provides open digital assets (urban layouts, buildings, vehicles) that were created for this purpose and can be used freely. The simulation platform supports flexible specification of sensor suites, environmental conditions, full control of all static and dynamic actors, maps generation and much more. Multiple clients... -
4
Jina
Build cross-modal and multimodal applications on the cloud
..., GraphQL protocols with TLS. Intuitive design pattern for high-performance microservices. Seamless Docker container integration: sharing, exploring, sandboxing, versioning and dependency control via Jina Hub. Fast deployment to Kubernetes, Docker Compose and Jina Cloud. Improved engineering efficiency thanks to the Jina AI ecosystem, so you can focus on innovating with the data applications you build. -
For minor company expenses, you might utilize a spend management solution or track everything in spreadsheets. For everything more, you'll need Precoro. We help companies achieve procurement excellence and budget efficiency by building transparent, predictable, automated spending workflows.
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5
Turing.jl
Bayesian inference with probabilistic programming
Bayesian inference with probabilistic programming. -
6
PySyft
Data science on data without acquiring a copy
Most software libraries let you compute over the information you own and see inside of machines you control. However, this means that you cannot compute on information without first obtaining (at least partial) ownership of that information. It also means that you cannot compute using machines without first obtaining control over those machines. This is very limiting to human collaboration and systematically drives the centralization of data, because you cannot work with a bunch of data without... -
7
TensorFlow Datasets
TFDS is a collection of datasets ready to use with TensorFlow,
TensorFlow Datasets is a collection of datasets ready to use, with TensorFlow or other Python ML frameworks, such as Jax. All datasets are exposed as tf.data. Datasets , enabling easy-to-use and high-performance input pipelines. To get started see the guide and our list of datasets. -
8
AirSim
A simulator for drones, cars and more, built on Unreal Engine
... a platform for AI research to experiment with deep learning, computer vision and reinforcement learning algorithms for autonomous vehicles. For this purpose, AirSim also exposes APIs to retrieve data and control vehicles in a platform independent way. AirSim is fully enabled for multiple vehicles. This capability allows you to create multiple vehicles easily and use APIs to control them. -
9
Elyra
Elyra extends JupyterLab with an AI centric approach
Elyra is a set of AI-centric extensions to JupyterLab Notebooks. The Elyra Getting Started Guide includes more details on these features. A version-specific summary of new features is located on the releases page. -
This means every device on your network, and every interface on every device is automatically analyzed for performance, errors, QoS, and configuration.
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10
Zygote
21st century AD
Zygote provides source-to-source automatic differentiation (AD) in Julia, and is the next-gen AD system for the Flux differentiable programming framework. For more details and benchmarks of Zygote's technique, see our paper. You may want to check out Flux for more interesting examples of Zygote usage; the documentation here focuses on internals and advanced AD usage. -
11
Spice.ai OSS
A self-hostable CDN for databases
.... Spice makes it easy and fast to query data from one or more sources using SQL. You can co-locate a managed dataset with your application or machine learning model, and accelerate it with Arrow in-memory, SQLite/DuckDB, or with attached PostgreSQL for fast, high-concurrency, low-latency queries. Accelerated engines give you flexibility and control over query cost and performance. -
12
Axon
Nx-powered Neural Networks
... abstractions that enable easy integration while maintaining a level of separation between each component. You should be able to use any of the APIs without dependencies on others. By decoupling the APIs, Axon gives you full control over each aspect of creating and training a neural network. At the lowest-level, Axon consists of a number of modules with functional implementations of common methods in deep learning. -
13
talos
Hyperparameter Optimization for TensorFlow, Keras and PyTorch
Talos radically changes the ordinary Keras, TensorFlow (tf.keras), and PyTorch workflow by fully automating hyperparameter tuning and model evaluation. Talos exposes Keras and TensorFlow (tf.keras) and PyTorch functionality entirely and there is no new syntax or templates to learn. Talos is made for data scientists and data engineers that want to remain in complete control of their TensorFlow (tf.keras) and PyTorch models, but are tired of mindless parameter hopping and confusing optimization... -
14
DGL
Python package built to ease deep learning on graph
... want to make it easy to implement graph neural networks model family. We also want to make the combination of graph based modules and tensor based modules (PyTorch or MXNet) as smooth as possible. DGL provides a powerful graph object that can reside on either CPU or GPU. It bundles structural data as well as features for a better control. We provide a variety of functions for computing with graph objects including efficient and customizable message passing primitives for Graph Neural Networks. -
15
MagicMirror²
Modular smart mirror platform with a list of installable modules
MagicMirror² is Open Source, free and maintained by a big group of enthusiasts. Got a nice idea? Send us a pull request and become a part of the big list of contributors. The core of MagicMirror² contains a strong API which allows 3rd party developers to build additional modules. Modules you can use. Modules you can develop. Read our extensive documentation to find out everything you want to know about the MagicMirror² project. The full API description allows you to build your own modules.... -
16
ModelFox
ModelFox makes it easy to train, deploy, and monitor ML models
... learning model by running modelfox train with the path to a CSV file and the name of the column you want to predict. The CLI automatically transforms your data into features, trains a number of linear and gradient boosted decision tree models to predict the target column, and writes the best model to a .modelfox file. If you want more control, you can provide a config file. -
17
Exadel CompreFace
Leading free and open-source face recognition system
... control who has access to your Face Recognition Services. CompreFace is delivered as a docker-compose config and supports different models that work on CPU and GPU. Our solution is based on state-of-the-art methods and libraries like FaceNet and InsightFace. Official website: https://exadel.com/solutions/compreface/ Github link: https://github.com/exadel-inc/CompreFace -
18
HPCC Systems
End-to-end big data in a massively scalable supercomputing platform.
HPCC Systems® (www.hpccsystems.com) from LexisNexis® Risk Solutions is a proven, open source solution for Big Data insights that can be implemented by businesses of all sizes. With HPCC Systems, developers can design applications with Big Data at their core, enabling businesses to better analyze and understand data at scale, improving business time to results and decisions. HPCC Systems offers a consistent data-centric programming language, two processing platforms and a single, complete... -
19
ADAMS
ADAMS is a workflow engine for building complex knowledge workflows.
ADAMS is a flexible workflow engine aimed at quickly building and maintaining data-driven, reactive workflows, easily integrated into business processes. Instead of placing operators on a canvas and manually connecting them, a tree structure and flow control operators determine how data is processed (sequentially/parallel). This allows rapid development and easy maintenance of large workflows, with hundreds or thousands of operators. Operators include machine learning (WEKA, MOA, MEKA... -
20
igel
Machine learning tool that allows you to train and test models
A delightful machine learning tool that allows you to train/fit, test, and use models without writing code. The goal of the project is to provide machine learning for everyone, both technical and non-technical users. I sometimes needed a tool sometimes, which I could use to fast create a machine learning prototype. Whether to build some proof of concept, create a fast draft model to prove a point or use auto ML. I find myself often stuck writing boilerplate code and thinking too much about... -
21
Keepsake
Version control for machine learning
Keepsake is a Python library that uploads files and metadata (like hyperparameters) to Amazon S3 or Google Cloud Storage. You can get the data back out using the command-line interface or a notebook. -
22
exchange-core
Ultra-fast matching engine written in Java based on LMAX Disruptor
... optimized. Priority is a limit-order-move operation mean latency (currently ~0.5µs). Cancel operation takes ~0.7µs, placing new order ~1.0µs. Disk journaling and journal replay support, state snapshots (serialization) and restore operations, LZ4 compression. Lock-free and contention-free order matching and risk control algorithms. Matching engine and risk control operations are atomic and deterministic. -
23
rpackage conjurer
Synthetic data generation using R
Builds synthetic data applicable across multiple domains. This package also provides flexibility to control data distribution to make it relevant to many industry examples. -
24
UnrealCV
Connecting Computer Vision to Unreal Engine
UnrealCV is a project to help computer vision researchers build virtual worlds using Unreal Engine (UE). It extends UE with a plugin. UnrealCV can be used in two ways. The first one is using a compiled game binary with UnrealCV embedded. This is as simple as running a game, no knowledge of Unreal Engine is required. The second is installing the UnrealCV plugin into Unreal Engine and using the editor to build a new virtual world. -
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LAML:Linear Algebra and Machine Learning
A stand-alone Java library for linear algebra and machine learning
LAML is a stand-alone pure Java library for linear algebra and machine learning. The goal is to build efficient and easy-to-use linear algebra and machine learning libraries. The reason why linear algebra and machine learning are built together is that full control of the basic data structures for matrices and vectors is required to have fast implementation for machine learning methods. Additionally, LAML provides a lot of commonly used matrix functions in the same signature to MATLAB, thus can...