Search Results for "framework python" - Page 40
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Showing 1691 open source projects for "framework python"
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VoteNet
Deep Hough Voting for 3D Object Detection in Point Clouds
VoteNet is a 3D object detection framework for point clouds that combines deep point set networks with a Hough voting mechanism to localize and classify objects in 3D space. It tackles the challenge that object centroids in 3D scenes often don’t lie on any input surface point by having each point “vote” for potential object centers; these votes are then clustered to propose object hypotheses. Once cluster centers are formed, the network regresses bounding boxes around them and classifies... -
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CrypTen
A framework for Privacy Preserving Machine Learning
CrypTen is a research framework developed by Facebook Research for privacy-preserving machine learning built directly on top of PyTorch. It provides a secure and intuitive environment for performing computations on encrypted data using Secure Multiparty Computation (SMPC). Designed to make secure computation accessible to machine learning practitioners, CrypTen introduces a CrypTensor object that behaves like a regular PyTorch tensor, allowing users to seamlessly apply automatic... -
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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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Graph Nets library
Build Graph Nets in Tensorflow
Graph Nets, developed by Google DeepMind, is a Python library designed for constructing and training graph neural networks (GNNs) using TensorFlow and Sonnet. It provides a high-level, flexible framework for building neural architectures that operate directly on graph-structured data. A graph network takes graphs as inputs, consisting of edges, nodes, and global attributes, and produces updated graphs with modified feature representations at each level. -
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TensorWatch
Debugging, monitoring and visualization for Python Machine Learning
TensorWatch is an open source debugging and visualization platform created by Microsoft Research to support machine learning, deep learning, and reinforcement learning workflows. It enables developers to observe training behavior in real time through interactive visualizations, primarily within Jupyter Notebook environments. The tool treats most data interactions as streams, allowing flexible routing, storage, and visualization of metrics generated during model training. A distinctive... -
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MMSkeleton
A OpenMMLAB toolbox for human pose estimation, skeleton-based action
MMSkeleton is an open-source toolbox for skeleton-based human understanding. It is a part of the open-mmlab project in the charge of Multimedia Laboratory, CUHK. MMSkeleton is developed on our research project ST-GCN. MMSkeleton provides a flexible framework for organizing codes and projects systematically, with the ability to extend to various tasks and scale up to complex deep models. MMSkeleton addresses to multiple tasks in human understanding. Build a custom skeleton-based dataset.... -
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PixelCNN
Code for the paper "PixelCNN++: A PixelCNN Implementation..."
PixelCNN is the official implementation from OpenAI of the autoregressive generative model described in the paper Conditional Image Generation with PixelCNN Decoders. It provides code for training and evaluating PixelCNN models on image datasets, focusing on conditional image modeling where pixels are generated sequentially based on the values of previously generated pixels. The repository demonstrates how to apply masked convolutions to enforce autoregressive dependencies and achieve... -
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jieba
Stuttering Chinese word segmentation
...The paddle mode uses the PaddlePaddle deep learning framework to train the sequence labeling (bidirectional GRU) network model to achieve word segmentation. Also supports part-of-speech tagging. To use paddle mode, you need to install paddlepaddle-tiny, pip install paddlepaddle-tiny==1.6.1. Currently paddle mode supports jieba v0.40 and above. For versions below jieba v0.40, please upgrade jieba, pip install jieba --upgrade. -
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PyTracking
Visual tracking library based on PyTorch
A general python framework for visual object tracking and video object segmentation, based on PyTorch. Official implementation of the RTS (ECCV 2022), ToMP (CVPR 2022), KeepTrack (ICCV 2021), LWL (ECCV 2020), KYS (ECCV 2020), PrDiMP (CVPR 2020), DiMP (ICCV 2019), and ATOM (CVPR 2019) trackers, including complete training code and trained models. -
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C++QED
A framework for simulating open quantum dynamics
C++QED is an application-programming framework for simulating open quantum dynamics in general. It has demonstrated the ability to simulate full Master equation of up to several thousand, and quantum trajectories of up to several hundred thousand dimensions. The basic idea is to allow users to build arbitrarily complex interacting quantum systems out of free subsystems and interactions (elements), and simulate their time evolution with a number of available time-evolution... -
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Orator
The Orator ORM provides a simple yet beautiful ActiveRecord implement.
The Orator ORM provides a simple yet beautiful ActiveRecord implementation. The Orator ORM is based on conventions to avoid the hassle of defining every single aspect of your models. It is inspired by the database part of the Laravel framework, but largely modified to be more pythonic. All you need to get you started is the configuration describing your database connections and passing it to a DatabaseManager instance. If you have multiple databases configured you can specify which one is... -
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TensorFlow Machine Learning Cookbook
Code for Tensorflow Machine Learning Cookbook
TensorFlow Machine Learning Cookbook repository provides practical code examples and educational materials that accompany the book TensorFlow Machine Learning Cookbook. The repository contains numerous Python scripts and Jupyter notebooks that demonstrate how to implement machine learning algorithms and neural networks using the TensorFlow framework. Each section focuses on a different aspect of machine learning development, including tensor manipulation, model training, optimization strategies, and data processing techniques. The examples illustrate how TensorFlow operations and tensors can be used to build machine learning pipelines and perform tasks such as regression, classification, and clustering. ... -
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Miasm
Reverse engineering framework in Python
The Miasm intermediate representation is used for multiple task: emulation through its jitter engine, symbolic execution, DSE, program analysis, but the intermediate representation can be a bit hard to read. We will present in this article new tricks Miasm has learned in 2018. Among them, the SSA/Out-of-SSA transformation, expression propagation and high-level operators can be joined to “lift” Miasm IR to a more human-readable language. We use graphviz to illustrate some graphs. Its layout... -
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Machine Learning with TensorFlow
Accompanying source code for Machine Learning with TensorFlow
Machine Learning with TensorFlow is an open repository containing the source code and practical examples that accompany the book Machine Learning with TensorFlow. The project provides numerous code samples demonstrating how to build machine learning models using the TensorFlow framework. These examples illustrate core machine learning concepts such as regression, classification, clustering, and neural networks through practical implementations. The repository includes implementations of... -
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DeepSDF
Learning Continuous Signed Distance Functions for Shape Representation
DeepSDF is a deep learning framework for continuous 3D shape representation using Signed Distance Functions (SDFs), as presented in the CVPR 2019 paper DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation by Park et al. The framework learns a continuous implicit function that maps 3D coordinates to their corresponding signed distances from object surfaces, allowing compact, high-fidelity shape modeling. Unlike traditional discrete voxel grids or meshes, DeepSDF... -
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King Phisher
Phishing Campaign Toolkit
King Phisher is an open source tool that can simulate real world phishing attacks. It has an easy-to-use, flexible architecture that allows for full control over both emails and server content. It is useful for running awareness campaigns and training, and can only be used for legal applications when the explicit permission of the targeted organization has been obtained. -
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hug
Embrace the APIs of the future. For developing APIs
...Writing tests for APIs written on-top of hug should be easy and intuitive. Magic done once, in an API framework, is better than pushing the problem set to the user of the API framework. Be the basis for next-generation Python APIs, embracing the latest technology. -
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Neural MMO
Code for the paper "Neural MMO: A Massively Multiagent Game..."
Neural MMO is a massively multi-agent simulation environment developed by OpenAI for reinforcement learning research. It provides a persistent, procedurally generated world where thousands of agents can interact, compete, and cooperate in real time. The environment is inspired by Massively Multiplayer Online Role-Playing Games (MMORPGs), featuring resource gathering, combat mechanics, exploration, and survival challenges. Agents learn behaviors in a shared ecosystem that supports long-term... -
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An open source framework for LC-MS based proteomics and metabolomics. OpenMS offers data structures and algorithms for the processing of mass spectrometry data. The library is written in C++. Our source code and wiki lives on GitHub (https://github.com/OpenMS/OpenMS).
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WALKOFF
A flexible, easy to use, automation framework
Faster, smarter, cheaper operations through automation. WALKOFF puts the tools in your hands to easily automate the tedious repetitive tasks dragging your operations down. Act smarter with WALKOFF by automatically gathering data, analyzing data, or visualizing data customized to your requirements. Act faster with WALKOFF by integrating the capabilities you already own to dynamically respond on your terms to your fast-moving environment. Drag and drop workflow editor. Sharable apps and... -
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MMF
A modular framework for vision & language multimodal research
MMF is a modular framework for vision and language multimodal research from Facebook AI Research. MMF contains reference implementations of state-of-the-art vision and language models and has powered multiple research projects at Facebook AI Research. MMF is designed from ground up to let you focus on what matters, your model, by providing boilerplate code for distributed training, common datasets and state-of-the-art pre-trained baselines out-of-the-box. MMF is built on top of PyTorch that... -
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CCZero (中国象棋Zero)
Implement AlphaZero/AlphaGo Zero methods on Chinese chess
ChineseChess-AlphaZero is a project that implements the AlphaZero algorithm for the game of Chinese Chess (Xiangqi). It adapts DeepMind’s AlphaZero method—combining neural networks and Monte Carlo Tree Search (MCTS)—to learn and play Chinese Chess without prior human data. The system includes self-play, training, and evaluation pipelines tailored to Xiangqi's unique game mechanics. -
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A symbolic framework for C++, Python and Octave implementing automatic differentiation by source code transformation in forward and reverse modes on sparse matrix-valued computational graphs.
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Coach
Enables easy experimentation with state of the art algorithms
Coach is a python framework that models the interaction between an agent and an environment in a modular way. With Coach, it is possible to model an agent by combining various building blocks, and training the agent on multiple environments. The available environments allow testing the agent in different fields such as robotics, autonomous driving, games and more. -
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AIAlpha
Use unsupervised and supervised learning to predict stocks
AIAlpha is a machine learning project focused on building predictive models for financial markets and algorithmic trading strategies. The repository explores how artificial intelligence techniques can analyze historical financial data and generate predictions about asset price movements. It provides a research-oriented environment where users can experiment with data processing pipelines, model training workflows, and quantitative trading strategies. The project typically involves collecting...
