Search Results for "easy run opensource" - Page 3
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Showing 73 open source projects for "easy run opensource"
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Stop Storing Third-Party Tokens in Your DatabaseRolling your own OAuth token storage can be a security liability. Token Vault securely stores access and refresh tokens from federated providers and handles exchange and renewal automatically. Connected accounts, refresh exchange, and privileged worker flows included.
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CoTracker
CoTracker is a model for tracking any point (pixel) on a video
CoTracker is a learning-based point tracking system that jointly follows many user-specified points across a video, rather than tracking each point independently. By reasoning about all tracks together, it can maintain temporal consistency, handle mutual occlusions, and reduce identity swaps when trajectories cross. The model takes sparse point queries on one frame and predicts their sub-pixel locations and a visibility score for every subsequent frame, producing long, coherent trajectories.... -
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Asteroid
The PyTorch-based audio source separation toolkit for researchers
...Filterbanks, encoders, maskers, decoders and losses are all common building blocks that can be combined in a flexible way to create new systems. Extending the toolkit with new features is simple. Add a new filterbank, separator architecture, dataset or even recipe very easily. Recipes provide an easy way to reproduce results with data preparation, system design, training and evaluation in a single script. This is an essential tool for the community! The default logger is TensorBoard in all the recipes. From the recipe folder, you can run the following to visualize the logs of all your runs. -
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hloc
Visual localization made easy with hloc
This is hloc, a modular toolbox for state-of-the-art 6-DoF visual localization. It implements Hierarchical Localization, leveraging image retrieval and feature matching, and is fast, accurate, and scalable. This codebase won the indoor/outdoor localization challenges at CVPR 2020 and ECCV 2020, in combination with SuperGlue, our graph neural network for feature matching. We provide step-by-step guides to localize with Aachen, InLoc, and to generate reference poses for your own data using... -
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Horovod
Distributed training framework for TensorFlow, Keras, PyTorch, etc.
Horovod was originally developed by Uber to make distributed deep learning fast and easy to use, bringing model training time down from days and weeks to hours and minutes. With Horovod, an existing training script can be scaled up to run on hundreds of GPUs in just a few lines of Python code. Horovod can be installed on-premise or run out-of-the-box in cloud platforms, including AWS, Azure, and Databricks. Horovod can additionally run on top of Apache Spark, making it possible to unify data processing and model training into a single pipeline. ... -
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Repo of Tree of Thoughts (ToT)
Implementation of "Tree of Thoughts
Language models are increasingly being deployed for general problem-solving across a wide range of tasks, but are still confined to token-level, left-to-right decision-making processes during inference. This means they can fall short in tasks that require exploration, strategic lookahead, or where initial decisions play a pivotal role. To surmount these challenges, we introduce a new framework for language model inference, Tree of Thoughts (ToT), which generalizes over the popular Chain of... -
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TensorFlow Documentation
TensorFlow documentation
An end-to-end platform for machine learning. TensorFlow makes it easy to create ML models that can run in any environment. Learn how to use the intuitive APIs through interactive code samples. -
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minimalRL-pytorch
Implementations of basic RL algorithms with minimal lines of codes
...The project is designed primarily as an educational resource that demonstrates how reinforcement learning algorithms work internally without the complexity of large frameworks. Each algorithm implementation is contained within a single file and typically ranges from about 100 to 150 lines of code, making it easy for learners to inspect the entire implementation at once. The repository includes examples of widely used reinforcement learning methods such as REINFORCE, Deep Q-Networks, Proximal Policy Optimization, and Actor-Critic architectures. Most experiments are designed to run quickly using the CartPole environment so that users can focus on understanding algorithm logic rather than computational infrastructure. -
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FrankMocap
A Strong and Easy-to-use Single View 3D Hand+Body Pose Estimator
FrankMocap is a monocular 3D human capture system that estimates body, hand, and optionally face pose from a single RGB image or video. It regresses parametric human models (e.g., SMPL/SMPL-X) directly, producing temporally stable meshes and joint angles suitable for animation or analytics. The pipeline couples a robust 2D keypoint detector with 3D mesh regression networks and priors that keep results anatomically plausible. It can run frame-by-frame or with temporal smoothing, and includes... -
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CleanRL
High-quality single file implementation of Deep Reinforcement Learning
CleanRL is a Deep Reinforcement Learning library that provides high-quality single-file implementation with research-friendly features. The implementation is clean and simple, yet we can scale it to run thousands of experiments using AWS Batch. CleanRL is not a modular library and therefore it is not meant to be imported. At the cost of duplicate code, we make all implementation details of a DRL algorithm variant easy to understand, so CleanRL comes with its own pros and cons. You should consider using CleanRL if you want to 1) understand all implementation details of an algorithm's variant or 2) prototype advanced features that other modular DRL libraries do not support (CleanRL has minimal lines of code so it gives you great debugging experience and you don't have to do a lot of subclassing like sometimes in modular DRL libraries). -
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.
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AllenNLP
An open-source NLP research library, built on PyTorch
AllenNLP makes it easy to design and evaluate new deep learning models for nearly any NLP problem, along with the infrastructure to easily run them in the cloud or on your laptop. AllenNLP includes reference implementations of high quality models for both core NLP problems (e.g. semantic role labeling) and NLP applications (e.g. textual entailment). AllenNLP supports loading "plugins" dynamically. -
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KoboldAI
Your gateway to GPT writing
...You can also turn on Adventure mode and play the game like AI Dungeon Unleashed. Stories can be played like a Novel, a text adventure game or used as a chatbot with an easy toggles to change between the multiple gameplay styles. This makes KoboldAI both a writing assistant, a game and a platform for so much more. The way you play and how good the AI will be depends on the model or service you decide to use. No matter if you want to use the free, fast power of Google Colab, your own high end graphics card, an online service you have an API key for (Like OpenAI or Inferkit) or if you rather just run it slower on your CPU you will be able to find a way to use KoboldAI that works for you. -
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AI Chatbots based on GPT Architecture
Training & Implementation of chatbots leveraging GPT-like architecture
Training & Implementation of chatbots leveraging GPT-like architecture with the aitextgen package to enable dynamic conversations. It sure seems like there are a lot of text-generation chatbots out there, but it's hard to find a python package or model that is easy to tune around a simple text file of message data. This repo is a simple attempt to help solve that problem. ai-msgbot covers the practical use case of building a chatbot that sounds like you (or some dataset/persona you choose)... -
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VoiceSmith
[WIP] VoiceSmith makes training text to speech models easy
VoiceSmith makes it possible to train and infer on both single and multispeaker models without any coding experience. It fine-tunes a pretty solid text to speech pipeline based on a modified version of DelightfulTTS and UnivNet on your dataset. Both models were pretrained on a proprietary 5000 speaker dataset. It also provides some tools for dataset preprocessing like automatic text normalization. Windows (only CPU supported currently) or any Linux based operating system. If you want to run... -
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YOLOv3
Object detection architectures and models pretrained on the COCO data
Fast, precise and easy to train, YOLOv5 has a long and successful history of real time object detection. Treat YOLOv5 as a university where you'll feed your model information for it to learn from and grow into one integrated tool. You can get started with less than 6 lines of code. with YOLOv5 and its Pytorch implementation. Have a go using our API by uploading your own image and watch as YOLOv5 identifies objects using our pretrained models. Start training your model without being an... -
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Interactive Deep Colorization
Deep learning software for colorizing black and white images
Interactive Deep Colorization is a software project for colorizing black-and-white (grayscale) images using deep learning, allowing users to add a few hints (e.g. scribbles) and get a plausible, fully colorized output. The idea is to merge automatic colorization (via neural networks) with optional user guidance — so if the automatic model’s guess isn’t quite right, the user can nudge colors via hints to steer the result, achieving more controlled, satisfying outputs. The project includes... -
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TensorFlowTTS
Real-Time State-of-the-art Speech Synthesis for Tensorflow 2
...It offers a variety of architectures for text-to-speech, including classic and modern models such as Tacotron‑2, FastSpeech / FastSpeech2, and neural vocoders like MelGAN and Multiband‑MelGAN. Because it’s based on TensorFlow 2, it can leverage optimizations such as fake-quantization aware training and pruning — which allow models to run faster than real time and to be deployable on mobile or embedded platforms. The library supports multiple languages (English, French, Korean, Chinese, German, etc.) and is relatively easy to adapt to new languages. With integrated vocoder + mel-spectrogram generation pipelines, pre-trained models, and fairly flexible architecture, TensorFlowTTS is a great off-the-shelf and extensible TTS engine for applications ranging from voice assistants to content generation or accessibility tools. -
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ReinventCommunity
Jupyter Notebook tutorials for REINVENT 3.2
This repository is a collection of useful jupyter notebooks, code snippets and example JSON files illustrating the use of Reinvent 3.2. -
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DeepMosaics
Automatically remove the mosaics in images and videos, or add mosaics
Automatically remove the mosaics in images and videos, or add mosaics to them. This project is based on "semantic segmentation" and "Image-to-Image Translation". You can either run DeepMosaics via a pre-built binary package, or from source. Run time depends on the computer's performance (GPU version has better performance but requires CUDA to be installed). Different pre-trained models are suitable for different effects.[Introduction to pre-trained models]. -
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NLP Architect
A model library for exploring state-of-the-art deep learning
NLP Architect is an open-source Python library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing and Natural Language Understanding neural networks. The library includes our past and ongoing NLP research and development efforts as part of Intel AI Lab. NLP Architect is designed to be flexible for adding new models, neural network components, data handling methods, and for easy training and running models. NLP Architect is a... -
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Neural Networks Collection
Neural Networks Collection
...So far the project implements: LVQ in several variants, SOM in several variants, Hopfield network and Perceptron. Other neural network types are planned, but not implemented yet. The project can run in two modes: command line tool and Python 7.2 extension. Currently, Python version appears more functional, as it allows easy interaction with algorithms developed by other people. -
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Easy-TensorFlow
Simple and comprehensive tutorials in TensorFlow
The goal of this repository is to provide comprehensive tutorials for TensorFlow while maintaining the simplicity of the code. Each tutorial includes a detailed explanation (written in .ipynb) format, as well as the source code (in .py format). There is a necessity to address the motivations for this project. TensorFlow is one of the deep learning frameworks available with the largest community. This repository is dedicated to suggesting a simple path to learn TensorFlow. In addition to the... -
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DSTK - DataScience ToolKit
DSTK - DataScience ToolKit for All of Us
DSTK - DataScience ToolKit is an opensource free software for statistical analysis, data visualization, text analysis, and predictive analytics. Newer version and smaller file size can be found at: https://sourceforge.net/projects/dstk3/ It is designed to be straight forward and easy to use, and familar to SPSS user. While JASP offers more statistical features, DSTK tends to be a broad solution workbench, including text analysis and predictive analytics features. -
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ProtPOS
Prediction of PROTtein Preferred Orientation on a Surface
ProtPOS is a self-contained, lightweight, and easy-to-use software package for predicting the preferred orientation of protein on a given surface upon initial adsorption. It searches quickly for the low energy protein poses in all translational and rotational degrees of freedom of the protein with respect to the surface using particle swarm optimization. Each successful run returns the lowest energy orientation of the protein on the surface in PDB format, which is readily used for MD simulations. ...
