Search Results for "modules" - Page 11
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Showing 531 open source projects for "modules"
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UniVL
Official implementation for UniVL video and language training models
UniVL is a video-language pretrain model. It is designed with four modules and five objectives for both video language understanding and generation tasks. It is also a flexible model for most of the multimodal downstream tasks considering both efficiency and effectiveness. -
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pyrpl
PyRPL turns your Red Pitaya into a powerful analog feedback device.
...Based on the open source software provided by the board manufacturer, PyRPL (Python RedPitaya Lockbox) implements many devices that are needed for optics experiments with the Red Pitaya. PyRPL implements various digital signal processing (DSP) modules (see features below). It allows to arbitrarily interconnect the available DSP modules and retrieve signal values on timescales below 1 ms. The graphical user interface (GUI) provides a realtime display of the various measurement instruments and allows the easy configuration of DSP signal chains and feedback controllers. At the highest abstraction level, arbitrary feedback sequences can be defined to fulfill tasks as complex as approaching and locking a resonance of a high-finesse Fabry-Perot cavity (tested up to finesse=100,000). -
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... • You will be able to convert your Python programs to .exe format with the pyinstaller method in the criteria you want. • You can quickly set up a virtual environment in your project, test it in a virtual environment, load modules and assist in the development phase of your project. It will be added with updates.
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BasicSR
Winning Solution in NTIRE19 Challenges on Video Restoration
...Unlike single-image restoration models, EDVR addresses the temporal dimension by aligning multiple video frames using deformable convolutional layers in a coarse-to-fine manner, allowing it to effectively handle large motion and complex scene dynamics. The architecture includes bespoke modules (e.g., Pyramid, Cascading and Deformable alignment and Temporal Spatial Attention fusion) that align information across frames and emphasize important features for restoration, enabling state-of-the-art performance on benchmarks such as the REDS challenge. By fusing spatial and temporal context, EDVR produces significantly improved visual quality in restored videos compared with approaches that treat each frame independently. -
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The Development System for Auditory Modelling (DSAM) is a computational library designed specifically for producing simulations of the auditory system. It brings together many established auditory models within a flexible programming platform.
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fastNLP
fastNLP: A Modularized and Extensible NLP Framework
fastNLP is a lightweight framework for natural language processing (NLP), the goal is to quickly implement NLP tasks and build complex models. A unified Tabular data container simplifies the data preprocessing process. Built-in Loader and Pipe for multiple datasets, eliminating the need for preprocessing code. Various convenient NLP tools, such as Embedding loading (including ELMo and BERT), intermediate data cache, etc.. Provide a variety of neural network components and recurrence models... -
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TIDoS
Python web penetration testing framework with modular security tools
...It provides a comprehensive environment for performing multiple phases of security assessment, including reconnaissance, scanning, enumeration, vulnerability analysis, and exploitation. Its modular architecture contains more than one hundred modules organized into several testing phases, allowing users to automate or manually run different security checks against a target application. The framework includes both graphical and command-line interfaces, enabling flexible interaction depending on the user’s workflow and preferred interface. A console interface inspired by tools like Metasploit allows testers to execute modules, manage targets, and perform operations efficiently. ... -
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surpriver
Find big moving stocks before they move using machine learning
...By applying machine learning techniques to market indicators, the tool attempts to identify patterns in trading behavior that deviate significantly from normal market activity. These anomalies are interpreted as signals that a stock may soon experience a major upward or downward move. The framework includes modules for retrieving market data, computing technical indicators, and applying anomaly detection algorithms to identify unusual patterns. The project is intended as a research tool for quantitative finance experiments and algorithmic trading strategy development. -
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AlphaPy
Python AutoML for Trading Systems and Sports Betting
AlphaPy is a Python-based AutoML framework tailored for trading systems and sports betting applications. Built on popular libraries like scikit-learn and pandas, it enables data scientists and speculators to craft predictive models, ensemble strategies, and automated forecasting systems with minimal setup. Run machine learning models using scikit-learn, Keras, xgboost, LightGBM, and CatBoost. Generate blended or stacked ensembles. Create models for analyzing the markets with MarketFlow.... -
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Delta ML
Deep learning based natural language and speech processing platform
DELTA is a deep learning-based end-to-end natural language and speech processing platform. DELTA aims to provide easy and fast experiences for using, deploying, and developing natural language processing and speech models for both academia and industry use cases. DELTA is mainly implemented using TensorFlow and Python 3. DELTA has been used for developing several state-of-the-art algorithms for publications and delivering real production to serve millions of users. It helps you to train,... -
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pytorch-tutorial
PyTorch Tutorial for Deep Learning Researchers
...It is designed primarily for beginners and intermediate practitioners who want to understand PyTorch fundamentals and quickly move toward building real neural network models. The repository walks users through core concepts such as tensors, autograd, neural network modules, convolutional networks, recurrent networks, and transfer learning. Each section includes runnable code examples that progressively increase in complexity, helping learners build intuition while practicing hands-on implementation. Because the tutorials are concise and practical, the project is widely used in classrooms and self-study environments. ... -
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Think Bayes
Code repository for Think Bayes
ThinkBayes is the code repository accompanying Think Bayes: a book on Bayesian statistics written in a computational style. Instead of heavy focus on continuous mathematics or calculus, the book emphasizes learning Bayesian inference by writing Python programs. The project includes code examples, scripts, and environments that correspond to the chapters of the book. Learners can run the code, experiment with probability distributions, compute posterior probabilities, and understand Bayesian... -
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Python Milter
Python API for Sendmail Milters.
Python API for Sendmail Milters. Related modules provide features such as content filtering, SPF, and reputation tracking. Changes are posted first to https://github.com/sdgathman/pymilter and related repos. -
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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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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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Texar
Toolkit for Machine Learning, Natural Language Processing
Texar is a toolkit aiming to support a broad set of machine learning, especially natural language processing and text generation tasks. Texar provides a library of easy-to-use ML modules and functionalities for composing whatever models and algorithms. The tool is designed for both researchers and practitioners for fast prototyping and experimentation. Texar was originally developed and is actively contributed by Petuum and CMU in collaboration with other institutes. A mirror of this repository is maintained by Petuum Open Source. ... -
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pysourceinfo
RTTI for Python Source and Binary Files
The 'pysourceinfo' package provides source information on Python runtime objects based on 'inspect', 'sys', 'os', and 'imp'. The covered objects include packages, modules, functions, methods, scripts, and classes by two views: - File System View - packages, modules, and linenumbers - based on files and paths - Runtime Object View - callables, classes, and containers - based on in-memory RTTI / introspection The supported platforms are: - Linux, BSD, Unix, OS-X, Cygwin, and Windows - Python2, Python3 - CPython, PyPy Object addresses within modules - Object Identifier OID - and the display of the runtime call flow are supported by 'PyStackInfo'. ... -
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PyTorch Natural Language Processing
Basic Utilities for PyTorch Natural Language Processing (NLP)
...It’s built with the very latest research in mind, and was designed from day one to support rapid prototyping. PyTorch-NLP comes with pre-trained embeddings, samplers, dataset loaders, metrics, neural network modules and text encoders. It’s open-source software, released under the BSD3 license. With your batch in hand, you can use PyTorch to develop and train your model using gradient descent. For example, check out this example code for training on the Stanford Natural Language Inference (SNLI) Corpus. Now you've setup your pipeline, you may want to ensure that some functions run deterministically. ... -
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setupjavax
Provides Java and integrated Jython/Pyhon + Java builds
The ‘setupjavax‘ package provides extension modules for the build of Java and Jython packages. 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. -
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yapyutils
Utilities for platform indepentent low-level system APIs.
...The more complex and complete data packages are provided for higher application layer functionality. The current release contains: * *yapyutils.modules* A utility to locate and load modules by a given name and/or file system path name, based on the *sys.path* variable. * *yapyutils.files* Search and location of files, e.g. modules and configuration files. * *yapyutils.help* Simple help for command line interfaces. * *yapyutils.config* Configuration file support, in particular for the initial setup of software packages. -
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X-JHBuild is a framework for working with multiple repositories. It makes use of JHBuild and is specialized for working with modules that use Git as VCS.
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SSD
A PyTorch Implementation of Single Shot MultiBox Detector
...It is built to help users train, evaluate, and experiment with object detection models using PyTorch rather than the original Caffe implementation. The repository includes the major components needed for an object detection workflow, including training scripts, evaluation scripts, demos, and utility modules. It supports commonly used benchmark datasets such as PASCAL VOC and MS COCO, and it also provides scripts to simplify downloading and setting up those datasets. For training visibility, the project includes support for Visdom so users can monitor loss in real time through a browser-based interface. Its structure makes it useful both as a reference implementation for learning SSD and as a base for custom experimentation in detection research or practical computer vision projects. -
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BCAW Tool
Bio Codon Analysis Workflow Tool
BCAWT was developed using python 3.7 with build in and third-party modules. The usage of BCAWT is made to be very easy where users have only to input a fasta format file containing genes to be analyzed, and a bunch of analysis will be performed with 23 different output files -
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This program is an email antivirus/antispam gateway. It is an interface to the postfix or sendmail (or any other smtpd), which runs antivirus and/or spamchecker. Its modular architecture can use any combination of antivirus/spamchecker according to co
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RouterSploit
Exploitation Framework for Embedded Devices
RouterSploit is an open-source exploitation framework focused on embedded devices such as routers, cameras, and IoT gadgets. It offers modules for exploits, scanners, and credentials testing, making it a valuable tool for security professionals and researchers. Inspired by Metasploit, it provides a CLI for executing attacks, testing device vulnerabilities, and simulating real-world exploitation scenarios in a legal and ethical manner.
