Search Results for "python signal"
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Showing 104 open source projects for "python signal"
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URH (Universal Radio Hacker)
Universal Radio Hacker: Investigate Wireless Protocols Like A Boss
Universal Radio Hacker (URH) is a tool for investigating unknown wireless communication protocols. It supports signal capturing, decoding, modulation analysis, and protocol reverse engineering through an intuitive graphical interface. URH is used in research, security testing, and hobbyist electronics for understanding proprietary RF systems, IoT device communication, and embedded protocols. -
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reverse-SynthID
Reverse engineering Gemini's SynthID detection
Reverse-SynthID is a research-focused project that analyzes and reverse-engineers Google’s SynthID watermarking system used in AI-generated images. It leverages signal processing and spectral analysis techniques to identify hidden watermark patterns without access to proprietary encoding methods. The project introduces a multi-resolution “SpectralCodebook” that maps watermark characteristics across different image sizes. Using this approach, it can detect SynthID watermarks with high... -
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FISSURE
The RF and reverse engineering framework for everyone
FISSURE is an open-source radio frequency analysis and signal intelligence framework built to support software-defined radio research, wireless security experimentation, and protocol reverse engineering. The project brings together tools for capturing, inspecting, decoding, replaying, and analyzing RF signals across a wide range of wireless technologies. It is designed as a practical environment for researchers and operators who need to move from raw spectrum observation to structured... -
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pyAudioAnalysis
Python Audio Analysis Library: Feature Extraction, Classification
pyAudioAnalysis is an open-source Python library designed for audio signal analysis, machine learning, and music information retrieval tasks. The project provides a collection of tools that allow developers to extract meaningful features from audio files and use those features for classification, segmentation, and analysis. The library supports multiple audio processing workflows, including feature extraction from raw audio signals, training of machine learning models, and automatic audio segmentation. ... -
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RuView
Turn WiFi signals into real-time human sensing and spatial awareness.
RuView is an edge AI perception system that transforms ordinary WiFi signals into real-time environmental sensing and human pose estimation. Built on the concept of WiFi DensePose, it analyzes disturbances in WiFi Channel State Information (CSI) caused by human movement to reconstruct body position, breathing patterns, heart rate, and presence. Unlike traditional vision systems, RuView operates without cameras, wearables, or cloud connectivity, making it a privacy-first sensing solution. The... -
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POT
Python Optimal Transport
This open source Python library provides several solvers for optimization problems related to Optimal Transport for signal, image processing and machine learning. -
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INTERCEPT
Unites the best signal intelligence tools
iNTERCEPT is a web-based interface that brings multiple software-defined radio and signal-intelligence style tools under one consistent dashboard, making complex workflows more approachable. Rather than requiring you to learn a different UI and setup process for each underlying utility, it provides a single place to start modes, view results, and monitor activity from a browser. The project’s goal is accessibility: lowering the skill and setup barrier so learners and authorized testers can... -
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Librosa
Python library for audio and music analysis
Librosa is a powerful Python library for analyzing and processing audio and music signals. Built on top of NumPy, SciPy, and matplotlib, it provides a wide range of tools for feature extraction, time-series manipulation, audio display, and music information retrieval. Whether you're building machine learning models for audio classification or visualizing spectrograms, Librosa is a go-to library for researchers and developers working in audio signal processing. -
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TorchAudio
Data manipulation and transformation for audio signal processing
The aim of torchaudio is to apply PyTorch to the audio domain. By supporting PyTorch, torchaudio follows the same philosophy of providing strong GPU acceleration, having a focus on trainable features through the autograd system, and having consistent style (tensor names and dimension names). Therefore, it is primarily a machine learning library and not a general signal processing library. The benefits of PyTorch can be seen in torchaudio through having all the computations be through PyTorch... -
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WiFi DensePose
Turn WiFi signals into real-time human pose estimation and detection
WiFi DensePose is a production-oriented implementation of a WiFi-based human pose estimation system that enables real-time full-body tracking using wireless signals rather than cameras. The project demonstrates how commodity mesh routers and signal processing techniques can be leveraged to infer dense human pose information, even through obstacles such as walls. It is designed to showcase the emerging field of RF-based sensing, where machine learning models interpret wireless channel data to... -
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VibeThinker
Diversity-driven optimization and large-model reasoning ability
VibeThinker is a compact but high-capability open-source language model released by WeiboAI (Sina AI Lab). It contains about 1.5 billion parameters, far smaller than many “frontier” models, yet it is explicitly optimized for reasoning, mathematics, and code generation tasks rather than general open-domain chat. The innovation lies in its training methodology: the team uses what they call the Spectrum-to-Signal Principle (SSP), where a first stage emphasizes diversity of reasoning paths (the... -
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AIOHTTP
Asynchronous HTTP client/server framework for asyncio and Python
Asynchronous HTTP Client/Server for asyncio and Python. AIOHTTP supports both client and server side of HTTP protocol. A long awaited new feature is tracing client request life cycle to figure out when and why client request spends a time waiting for connection establishment, getting server response headers etc. Now it is possible by registering special signal handlers on every request processing stage. -
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hls4ml
Machine learning on FPGAs using HLS
hls4ml is an open-source framework that enables machine learning models to be implemented directly on hardware such as FPGAs and ASICs using high-level synthesis techniques. The system converts trained neural network models from common machine learning frameworks into hardware description code suitable for ultra-low-latency inference. This approach allows machine learning algorithms to run directly on specialized hardware, making them suitable for applications that require extremely fast... -
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Atheris
A Coverage-Guided, Native Python Fuzzer
Atheris is a coverage-guided fuzzer for CPython that treats Python as a first-class fuzzing target, enabling rapid discovery of crashes and logic errors in pure-Python code and native extensions. It hooks into Python’s interpreter to collect fine-grained coverage and uses that signal to evolve inputs, pushing programs into previously unexplored code paths. Because many Python libraries are thin wrappers over C/C++ code, Atheris is equally adept at surfacing memory safety issues in extension modules compiled with sanitizers. ... -
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PowerTrader_AI
Fully automated crypto trading powered by a custom price prediction AI
PowerTrader_AI is a fully open-source, automated cryptocurrency trading bot that combines a custom price prediction AI with a structured and tiered dollar-cost averaging (DCA) strategy to make real trading decisions on behalf of users. It continuously analyzes market data to forecast high and low price levels across multiple timeframes, using those predictions to determine when to open, scale into, or close positions automatically, which aims to take emotion out of trading and enforce... -
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SciPy
SciPy library main repository
This is the main repository for the SciPy library, one of the core packages that make up the SciPy stack. SciPy is an open source software used in the fields of mathematics, science, and engineering, with modules for statistics, optimization, integration, linear algebra, signal and image processing, and many more. The SciPy library contains many of the user-friendly and efficient numerical routines, including those for numerical integration, interpolation, and optimization. SciPy is built... -
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bu-agent-sdk
An agent is just a for-loop
...The SDK emphasizes simplicity and control, avoiding heavy orchestration frameworks and instead letting developers specify exactly what tools an agent can employ and how it should signal task completion. This lightweight design means developers can rapidly prototype AI agent behavior, test custom tools, and integrate models like Anthropic’s Claude with minimal overhead. -
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AI Hedge Fund
An AI Hedge Fund Team
This repository demonstrates how to build a simplified, automated hedge fund strategy powered by AI/ML. It integrates financial data collection, preprocessing, feature engineering, and predictive modeling to simulate decision-making in trading. The code shows workflows for pulling stock or market data, applying machine learning algorithms to forecast trends, and generating buy/sell/hold signals based on the predictions. Its structure is educational: intended more as a proof-of-concept than a... -
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WhisperJAV
Uses Qwen3-ASR, local LLM, Whisper, TEN-VAD
WhisperJAV is an open-source speech transcription pipeline designed specifically for generating subtitles for Japanese adult video content. The project addresses challenges that standard speech recognition models face when transcribing this type of audio, which often includes low signal-to-noise ratios and large numbers of non-verbal vocalizations. Traditional automatic speech recognition systems can misinterpret these sounds as words, leading to inaccurate transcripts. WhisperJAV introduces... -
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HexStrike AI MCP Agents
HexStrike AI MCP Agents is an advanced MCP server
HexStrike AI is an MCP server that lets LLM agents autonomously operate a large catalog of offensive-security tools. Its goal is to bridge “language models” and practical pentest workflows—enumeration, exploitation, vulnerability discovery, and bug bounty reconnaissance—under safe, auditable controls. The server exposes typed tools and guardrails so agent prompts translate to concrete, parameterized actions rather than brittle shell strings. It ships with curated tool adapters, task... -
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FinGPT
Open-Source Financial Large Language Models
FinGPT is an open-source, finance-specialized large language model framework that blends the capabilities of general LLMs with real-time financial data feeds, domain-specific knowledge bases, and task-oriented agents to support market analysis, research automation, and decision support. It extends traditional GPT-style models by connecting them to live or historical financial datasets, news APIs, and economic indicators so that outputs are grounded in relevant and recent market conditions... -
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Audiomentations
A Python library for audio data augmentation
A Python library for audio data augmentation. Inspired by albumentations. Useful for deep learning. Runs on CPU. Supports mono audio and multichannel audio. Can be integrated in training pipelines in e.g. Tensorflow/Keras or Pytorch. Has helped people get world-class results in Kaggle competitions. Is used by companies making next-generation audio products. -
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SleepFM-Clinical
Improve human sleep through scientifically
SleepFM-Clinical is a specialized version of SleepFM designed for clinical and research environments, offering an adaptive audio modulation system aimed at improving human sleep through scientifically guided soundscapes. Rather than simply playing static white noise or ambient tracks, it uses a closed-loop, frequency-modulated framework that responds to user-specific sleep patterns and physiological signals to tailor sound in ways that can enhance sleep onset and depth. The clinical release... -
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AudioMuse-AI
AudioMuse-AI is an Open Source Dockerized environment
AudioMuse-AI is an open-source system designed to automatically generate playlists and analyze music libraries using artificial intelligence and audio signal processing techniques. The platform runs locally in a Dockerized environment and performs detailed sonic analysis on audio files to understand characteristics such as tempo, mood, and acoustic similarity. By analyzing the underlying audio content rather than relying on external metadata services, the system can organize large personal... -
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audioFlux
A library for audio and music analysis, feature extraction
A library for audio and music analysis, and feature extraction. Can be used for deep learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc. audioflux is a deep learning tool library for audio and music analysis, feature extraction. It supports dozens of time-frequency analysis transformation methods and hundreds of corresponding time-domain and frequency-domain feature combinations. It can be provided to deep learning networks for training and is used to...
