Search Results for "noise"
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Showing 35 open source projects for "noise"
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QualityScaler
Image/video AI upscaler app (BSRGAN)
Qualityscaler is a Windows app that uses BSRGAN Artificial Intelligence to enhance, enlarge and reduce noise in photographs and videos. QualityScaler is completely written in Python, from the backend to the front end. Image/list of images upscale. Video upscale. Drag&drop files [image / multiple images/video] Automatic image tiling and merging to avoid gpu VRAM limitation. Resize image/video before upscaling. Multiple Gpu support. Compatible images - png, jpeg, bmp, webp, tif. Compatible video... -
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SpeechRecognition
Speech recognition module for Python
Library for performing speech recognition, with support for several engines and APIs, online and offline. Recognize speech input from the microphone, transcribe an audio file, save audio data to an audio file. Show extended recognition results, calibrate the recognizer energy threshold for ambient noise levels (see recognizer_instance.energy_threshold for details). Listening to a microphone in the background, various other useful recognizer features. The easiest way to install this is using pip... -
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JobFunnel
Scrape job websites into a single spreadsheet with no duplicates.
Scrape job websites into a single spreadsheet with no duplicates. Automated tool for scraping job postings into a .csv file. You can search for jobs with YAML configuration files or by passing command arguments. By performing regular scraping and reviewing, you can cut through the noise of even the busiest job markets. Run funnel with your settings YAML to populate your master CSV file with jobs from available providers. JobFunnel can be easily automated to run nightly with crontab. If you have... -
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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. Mix in another sound, e.g. a background noise. Useful if your original sound is clean and you want to simulate an environment where... -
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HDBSCAN
A high performance implementation of HDBSCAN clustering
HDBSCAN - Hierarchical Density-Based Spatial Clustering of Applications with Noise. Performs DBSCAN over varying epsilon values and integrates the result to find a clustering that gives the best stability over epsilon. This allows HDBSCAN to find clusters of varying densities (unlike DBSCAN), and be more robust to parameter selection. In practice this means that HDBSCAN returns a good clustering straight away with little or no parameter tuning -- and the primary parameter, minimum cluster size... -
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Recurrent Interface Network (RIN)
Implementation of Recurrent Interface Network (RIN)
Implementation of Recurrent Interface Network (RIN), for highly efficient generation of images and video without cascading networks, in Pytorch. The author unawaredly reinvented the induced set-attention block from the set transformers paper. They also combine this with the self-conditioning technique from the Bit Diffusion paper, specifically for the latents. The last ingredient seems to be a new noise function based around the sigmoid, which the author claims is better than cosine scheduler... -
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PhySO
Physical Symbolic Optimization
Physical symbolic optimization (PhySO) - A symbolic optimization package built for physics. Symbolic regression module uses deep reinforcement learning to infer analytical physical laws that fit data points, searching in the space of functional forms. -
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Trafilatura
Python & command-line tool to gather text on the Web
... by avoiding the noise caused by recurring elements (headers, footers, links/blogroll etc.) and second by including information such as author and date in order to make sense of the data. The extractor tries to strike a balance between limiting noise (precision) and including all valid parts (recall). It also has to be robust and reasonably fast, it runs in production on millions of documents. -
9
Diffusers
State-of-the-art diffusion models for image and audio generation
... lines of code. Interchangeable noise schedulers for different diffusion speeds and output quality. Pretrained models that can be used as building blocks, and combined with schedulers, for creating your own end-to-end diffusion systems. We recommend installing Diffusers in a virtual environment from PyPi or Conda. For more details about installing PyTorch and Flax, please refer to their official documentation. -
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PyTorch Implementation of SDE Solvers
Differentiable SDE solvers with GPU support and efficient sensitivity
This library provides stochastic differential equation (SDE) solvers with GPU support and efficient backpropagation. examples/demo.ipynb gives a short guide on how to solve SDEs, including subtle points such as fixing the randomness in the solver and the choice of noise types. examples/latent_sde.py learns a latent stochastic differential equation, as in Section 5 of [1]. The example fits an SDE to data, whilst regularizing it to be like an Ornstein-Uhlenbeck prior process. The model can... -
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Imagen - Pytorch
Implementation of Imagen, Google's Text-to-Image Neural Network
Implementation of Imagen, Google's Text-to-Image Neural Network that beats DALL-E2, in Pytorch. It is the new SOTA for text-to-image synthesis. Architecturally, it is actually much simpler than DALL-E2. It consists of a cascading DDPM conditioned on text embeddings from a large pre-trained T5 model (attention network). It also contains dynamic clipping for improved classifier-free guidance, noise level conditioning, and a memory-efficient unit design. It appears neither CLIP nor prior network... -
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Code_TYMPAN
Open source software calculating industrial noise in the environment
Code_TYMPAN™ is an open source software for calculating industrial noise in the environment. It allows dealing with 3D realistic geometries and has a convenient Human Machine Interface to help engineers to build 3D models and to achieve analysis needed in environmental noise studies. Code_TYMPAN™ allows developing your own calculation method from basic components and geometrical solvers. It includes a solver based on ISO 9613 extended to industrial applications. In 4.2.x version, a Python API... -
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pysoundanalyser
a python program to generate, visualize, and manipulate short sounds
pysoundanalyser is a Python application that can be used to generate, visualize, and manipulate short sounds through a graphical user interface. Visualization functions include visualization of the power spectrum, the spectrogram, the autocorrelation, and the autocorrelogram of a sound. Manipulation functions include filtering, concatenating, cutting, and scaling the level of a sound. Several types of sounds can also be generated including, pure tones, harmonic complex tones, noise of different... -
14
pyrpl
PyRPL turns your Red Pitaya into a powerful analog feedback device.
The Red Pitaya is a commercial, affordable FPGA board with fast analog inputs and outputs. This makes it useful for quantum optics experiments, in particular as a digital feedback controller for analog systems. 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... -
15
imgaug
Image augmentation for machine learning experiments
imgaug is a library for image augmentation in machine learning experiments. It supports a wide range of augmentation techniques, allows to easily combine these and to execute them in random order or on multiple CPU cores, has a simple yet powerful stochastic interface and can not only augment images but also key points/landmarks, bounding boxes, heatmaps and segmentation maps. Affine transformations, perspective transformations, contrast changes, gaussian noise, dropout of regions, hue... -
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Image Super-Resolution (ISR)
Super-scale your images and run experiments with Residual Dense
The goal of this project is to upscale and improve the quality of low-resolution images. This project contains Keras implementations of different Residual Dense Networks for Single Image Super-Resolution (ISR) as well as scripts to train these networks using content and adversarial loss components. Docker scripts and Google Colab notebooks are available to carry training and prediction. Also, we provide scripts to facilitate training on the cloud with AWS and Nvidia-docker with only a few... -
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PySptools
Hyperspectral algorithms for Python
..., PPI * material count: HfcVd, HySime * noise: Savitzky Golay, MNF, whiten * sigproc: bilateral * sklearn: HyperEstimatorCrossVal, HyperSVC and others * spectro: convex hull quotient, features extraction (tetracorder style), USGS06 lib interface * util: load_ENVI_file, load_ENVI_spec_lib, corr, cov and others The library do an extensive use of the numpy numeric library and can achieve good speed. The library is mature enough and is very usable even if the development is at a beta step. -
18
Inelastica
Transport code and tools based on SIESTA and TranSIESTA (DFT-NEGF)
NOTE: The Inelastica project moved to https://github.com/tfrederiksen/inelastica/ in February 2018. Pre- and post-processing tools for SIESTA (DFT, quantum chemistry) and TranSIESTA (quantum transport): (1) Calculate phonon frequencies, e-ph couplings, and inelastic contributions to the conductance (IETS). (2) Access Hamiltonian etc from Python. Some code documentation and installation instructions are available at this mediawiki page: http://dipc.ehu.es/frederiksen/inelastica/index.php. -
19
aeneas
Automagically synchronize audio and text (aka forced alignment)
aeneas is a Python/C library and a set of tools to automagically synchronize audio and text (aka forced alignment). aeneas automatically generates a synchronization map between a list of text fragments and an audio file containing the narration of the text. In computer science this task is known as (automatically computing a) forced alignment. -
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Astrophotography Lab
A collection of useful tools for astrophotographers
Astrophotography Lab (APLab) is a free program intended for anyone interested in astrophotography. It has two main purposes: - Interpreting data extracted from your astrophotos to produce useful information. - Using this information as a help for further improving your imaging results. The program consists of four main tools: an analyser tool, a calculator tool, a simulator tool and a plotting tool. The tools are connected, allowing you to transfer information between them, and easily... -
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SnowMicroPyn
Python based reader for SnowMicroPen® .pnt measurements
SnowMicroPyn is an opensource reader for SnowMicroPen® files in binary .pnt format. The reader is Python based and published as source code as well as compiled executable for Windows, Linux and Mac. The software is preliminary, thus please report bugs. For further information, please read the Readme.txt in the download section. The SnowMicroPen® (SMP) is developed by the WSL Institute for Snow and Avalanche Research, Davos. The SMP is the first high-resolution snow penetrometer. It is... -
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ImpraStorage
ImpraStorage provided a private imap access to store large files
ImpraStorage provided a private imap access to store large files. Each file stored on the server is split in severals random parts. Each part also contains random noise data (lenght depends on a crypt key) to ensure privacy and exclude easy merge without the corresponding key. An index of files stored is encrypt (with the symmetric-key algorithm Kirmah) and regularly updated. Once decrypt, it permit to perform search on the server and download each part. transfert process is transparent... -
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... (simulate a random order - based on crypted key - to randomize data) - mix (mix data according to a generated map - based on crypted key - with addition of noise) Process is as follow : ======== encrypt : file > [ compress > ] encrypt > [randomiz data > mix data > compress > ] file.kmh decrypt: file.kmh > [ uncompress > unmix data > unrandomiz data] > decrypt > [uncompress > ] file ======== for encrypt/decrypt large binary files, use the fastest alternative : split/merge
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DeDAY
MLE survival analysis: Gompertz, Weibull, Logistic and mixed morality.
... and in-dependent mortality. Mixed models partition mortality into exogenous and endogenous components, so that the intrinsic survivorship can be estimated without the interference from extrinsic noise. DeDAY supports both interval-censored data and exact event-time data. Using MLE (Maximum Likelihood Estimate), DeDAY fits statistic model to the data. DeDAY also calculates the variances and the multi-dimensional confidence limits of model parameters. DeDAY is free for academic users. -
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RNNLIB is a recurrent neural network library for sequence learning problems. Applicable to most types of spatiotemporal data, it has proven particularly effective for speech and handwriting recognition. full installation and usage instructions given at http://sourceforge.net/p/rnnl/wiki/Home/