Search Results for "state-thread" - Page 2
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Showing 48 open source projects for "state-thread"
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Facexlib
FaceXlib aims at providing ready-to-use face-related functions
facexlib is a PyTorch-based library providing ready-to-use face-related functions, including detection, alignment, recognition, and more. It integrates state-of-the-art open-source methods for various face processing tasks. -
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Official YOLOv7
YOLOv7: Trainable bag-of-freebies sets new state-of-the-art
YOLOv7 is the official implementation of the paper “YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors.” It is a PyTorch-based object detection project focused on high speed and strong accuracy for real-time computer vision. The repository provides model definitions, training scripts, testing tools, inference examples, pretrained weights, and deployment-oriented materials. YOLOv7 introduced training-time improvements that raise accuracy without increasing inference cost, which is why the project became important in real-time detection research. ... -
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Fairseq
Facebook AI Research Sequence-to-Sequence Toolkit written in Python
...We provide reference implementations of various sequence modeling papers. Recent work by Microsoft and Google has shown that data parallel training can be made significantly more efficient by sharding the model parameters and optimizer state across data parallel workers. These ideas are encapsulated in the new FullyShardedDataParallel (FSDP) wrapper provided by fairscale. Fairseq can be extended through user-supplied plug-ins. Models define the neural network architecture and encapsulate all of the learnable parameters. Criterions compute the loss function given the model outputs and targets. ... -
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Interpret-Text
State-of-the-art explainers for text-based machine learning models
...Users can run their experiments across multiple state-of-the-art explainers and easily perform comparative analysis on them. Using these tools, users will be able to explain their machine-learning models globally on each label or locally for each document. -
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Spleeter
Deezer source separation library including pretrained models
Spleeter is the Deezer source separation library with pretrained models written in Python and using Tensorflow. It makes it easy to train music source separation models (assuming you have a dataset of isolated sources), and provides already trained state of the art models for performing various flavours of separation. 2 stems and 4 stems models have state of the art performances on the musdb dataset. Spleeter is also very fast as it can perform separation of audio files to 4 stems 100x faster than real-time when run on a GPU. We designed Spleeter so you can use it straight from command line as well as directly in your own development pipeline as a Python library. ... -
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PyTorchVideo
A deep learning library for video understanding research
...It is tightly integrated with PyTorch and PyTorch Lightning, offering flexible APIs for building and training spatiotemporal networks. The library includes efficient implementations of state-of-the-art architectures such as SlowFast, X3D, and MViT, optimized for both research prototyping and production inference. It supports video I/O pipelines, data augmentation, distributed training, and mixed precision computation for large-scale experiments. PyTorchVideo also connects seamlessly with other Meta AI tools such as Detectron2 and PyTorch3D for multimodal video analysis. ... -
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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. -
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Zipline
Zipline, a Pythonic algorithmic trading library
Zipline is a Pythonic algorithmic trading library. It is an event-driven system for backtesting. Zipline is currently used in production as the backtesting and live-trading engine powering Quantopian -- a free, community-centered, hosted platform for building and executing trading strategies. Quantopian also offers a fully managed service for professionals that includes Zipline, Alphalens, Pyfolio, FactSet data, and more. Installing Zipline is slightly more involved than the average Python... -
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Forecasting Best Practices
Time Series Forecasting Best Practices & Examples
...The goal of this repository is to build a comprehensive set of tools and examples that leverage recent advances in forecasting algorithms to build solutions and operationalize them. Rather than creating implementations from scratch, we draw from existing state-of-the-art libraries and build additional utilities around processing and featuring the data, optimizing and evaluating models, and scaling up to the cloud. The examples and best practices are provided as Python Jupyter notebooks and R markdown files and a library of utility functions. -
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Top Deep Learning Projects
A list of popular github projects related to deep learning
...By aggregating high-star projects across frameworks (TensorFlow, PyTorch), tools (computer vision, NLP, reinforcement learning), tutorials, and research code, it helps users quickly discover reputable and well-maintained repositories. This way one can survey state-of-the-art projects, find learning resources, or pick stable libraries for production — without manually sifting through hundreds of repos. The repository is openly licensed under MIT, making it easy to fork, extend, or contribute updates (e.g. adding newer projects or reordering by recent popularity). -
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Tensor2Tensor
Library of deep learning models and datasets
Deep Learning (DL) has enabled the rapid advancement of many useful technologies, such as machine translation, speech recognition and object detection. In the research community, one can find code open-sourced by the authors to help in replicating their results and further advancing deep learning. However, most of these DL systems use unique setups that require significant engineering effort and may only work for a specific problem or architecture, making it hard to run new experiments and... -
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ChainerRL
ChainerRL is a deep reinforcement learning library
ChainerRL (this repository) is a deep reinforcement learning library that implements various state-of-the-art deep reinforcement algorithms in Python using Chainer, a flexible deep learning framework. PFRL is the PyTorch analog of ChainerRL. ChainerRL has a set of accompanying visualization tools in order to aid developers' ability to understand and debug their RL agents. With this visualization tool, the behavior of ChainerRL agents can be easily inspected from a browser UI. -
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RecNN
Reinforced Recommendation toolkit built around pytorch 1.7
This is my school project. It focuses on Reinforcement Learning for personalized news recommendation. The main distinction is that it tries to solve online off-policy learning with dynamically generated item embeddings. I want to create a library with SOTA algorithms for reinforcement learning recommendation, providing the level of abstraction you like. -
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I3D models trained on Kinetics
Convolutional neural network model for video classification
...The I3D model extends the 2D convolutional structure of Inception-v1 into 3D, allowing it to capture spatial and temporal information from videos for action recognition. This repository includes pretrained I3D models on the Kinetics dataset, with both RGB and optical flow input streams. The models have achieved state-of-the-art results on benchmark datasets such as UCF101 and HMDB51, and also won first place in the CVPR 2017 Charades Challenge. The project provides TensorFlow and Sonnet-based implementations, pretrained checkpoints, and example scripts for evaluating or fine-tuning models. It also offers sample data, including preprocessed video frames and optical flow arrays, to demonstrate how to run inference and visualize outputs. -
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MLBox
MLBox is a powerful Automated Machine Learning python library
...Fast reading and distributed data preprocessing/cleaning/formatting. Highly robust feature selection and leak detection. Accurate hyper-parameter optimization in high-dimensional space. State-of-the-art predictive models for classification and regression (Deep Learning, Stacking, LightGBM,...) Prediction with model interpretation. MLBox has been developed and used by many active community members. Your help is very valuable to make it better for everyone. -
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WIP
Create Siri Shortcuts with Python
python-shortcuts is a library to create Siri Shortcuts on your laptop with your favorite text editor. It uses toml to represent shortcuts. The library is in a very early development state (PR welcome!), so it does not support all actions from the Shortcuts app. -
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Aglyph
Aglyph is a Dependency Injection framework for Python.
...Aglyph can assemble "prototype" components (a new instance is created every time), "singleton" components (the same instance is returned every time), "borg" components (a new instance is created every time, but all instances of the same class share the same internal state), and "weakref" components (the same instance is returned as long as there is at least one "live" reference to the instance in the running application). Aglyph can be configured using a declarative XML syntax, or programmatically in pure Python using a fluent API. -
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Face Recognition
World's simplest facial recognition api for Python & the command line
...It allows you to recognize and manipulate faces from Python or from the command line using dlib's (a C++ toolkit containing machine learning algorithms and tools) state-of-the-art face recognition built with deep learning. Face Recognition is highly accurate and is able to do a number of things. It can find faces in pictures, manipulate facial features in pictures, identify faces in pictures, and do face recognition on a folder of images from the command line. It could even do real-time face recognition and blur faces on videos when used with other Python libraries. -
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gevent
Coroutine-based concurrency library for Python
gevent is a coroutine -based Python networking library that uses greenlet to provide a high-level synchronous API on top of the libev or libuv event loop. gevent is inspired by eventlet but features a more consistent API, simpler implementation and better performance. Read why others use gevent and check out the list of the open source projects based on gevent. Since version 1.1, gevent is maintained by Jason Madden for NextThought with help from the contributors and is licensed under the... -
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HYBRYD
Library written in C with Python API for IPv6 networking
...Will put an IPv6 adress active available as soon as possible so that you can download pieces of codes. The aim of that coding was to use primary linux commands easily codable and make an object of an IPv6 connection. Moreover, the model is full-state! -
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Modules for developing, configuring and running a computation based on function blocks entirely in Python. Function block based computation is a data, event and state driven approach to data processing.
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ScardFace is a python3k library for interfacing with smart cards, which supports Plug-and-Play readers inclusion and threading. It also offers classes for manipulating APDU cmds and resps, and use them in a transport-protocol-independent fashion.
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Compound is a library that allows Python 2 code to be called seamlessly from a Python 3 program.
