Search Results for "estimate"
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Showing 55 open source projects for "estimate"
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1
MESHROOM
3D reconstruction software
...The dense modeling of the scene is the result yielded by chaining two computer vision-based pipelines, “Structure-from-Motion” (SfM) and “Multi View Stereo” (MVS). Fusion of Multi-bracketing LDR images into HDR. Alignment of panorama images. Support for fisheye optics. Automatically estimate fisheye circle or manually edit it. Take advantage of motorized-head file. Easy to integrate in your Renderfarm System. Add specific rules to select the most suitable machines regarding CPU, RAM, GPU requirements of each Node. -
2
NannyML
Detecting silent model failure. NannyML estimates performance
...When the actual outcome of your deployed prediction models is delayed, or even when post-deployment target labels are completely absent, you can use NannyML's CBPE-algorithm to estimate model performance. -
3
Denoising Diffusion Probabilistic Model
Implementation of Denoising Diffusion Probabilistic Model in Pytorch
Implementation of Denoising Diffusion Probabilistic Model in Pytorch. It is a new approach to generative modeling that may have the potential to rival GANs. It uses denoising score matching to estimate the gradient of the data distribution, followed by Langevin sampling to sample from the true distribution. If you simply want to pass in a folder name and the desired image dimensions, you can use the Trainer class to easily train a model. -
4
SAM 3D Body
Code for running inference with the SAM 3D Body Model 3DB
SAM 3D Body is a promptable model for single-image full-body 3D human mesh recovery, designed to estimate detailed human pose and shape from just one RGB image. It reconstructs the full body, including feet and hands, using the Momentum Human Rig (MHR), a parametric mesh representation that decouples skeletal structure from surface shape for more accurate and interpretable results. The model is trained to be robust in diverse, in-the-wild conditions, so it handles varied clothing, viewpoints, and backgrounds while maintaining strong accuracy across multiple human-pose benchmarks. ... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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5
3D Gaussian Splatting
Original reference implementation of "3D Gaussian Splatting"
...The project is widely used in computer graphics, spatial capture, virtual production, research, and experimental 3D reconstruction workflows. It relies on image-based reconstruction pipelines such as COLMAP to estimate camera positions before optimizing the Gaussian representation. Overall, Gaussian Splatting has become a foundational reference implementation for modern real-time radiance field rendering. -
6
Basketball Reference
NBA Stats API via Basketball Reference
...I initially wrote this library as an exercise for creating my first PyPi package, hope you find it valuable! This library was created for another Python project where I was trying to estimate an NBA player's productivity. A lot of sports-related APIs are expensive - luckily, Basketball Reference provides a free service which can be scraped and translated into a usable API. -
7
VGGT
[CVPR 2025 Best Paper Award] VGGT
...The design emphasizes consistent geometric reasoning: outputs from one head (e.g., correspondences or tracks) reinforce others (e.g., pose or depth), making the system more robust to challenging viewpoints and textures. The repo provides inference pipelines to estimate geometry from monocular inputs, stereo pairs, or brief sequences, together with evaluation harnesses for common geometry benchmarks. Training utilities highlight data curation and augmentations that preserve geometric cues while improving generalization across scenes and cameras. -
8
US Job Market Visualizer
A research tool for visually exploring Bureau of Labor Statistics
...The repository includes tools for scraping BLS pages, converting them to structured data, and building the visualization dataset. An LLM scoring pipeline can evaluate occupations using custom criteria supplied through prompts. The included AI exposure layer is intended as an exploratory estimate rather than a prediction of job elimination. A generated prompt file also packages the complete dataset for data-grounded analysis with language models. -
9
Causal ML
Uplift modeling and causal inference with machine learning algorithms
Causal ML is a Python package that provides a suite of uplift modeling and causal inference methods using machine learning algorithms based on recent research [1]. It provides a standard interface that allows users to estimate the Conditional Average Treatment Effect (CATE) or Individual Treatment Effect (ITE) from experimental or observational data. Essentially, it estimates the causal impact of intervention T on outcome Y for users with observed features X, without strong assumptions on the model form. An important lever to increase ROI in an advertising campaign is to target the ad to the set of customers who will have a favorable response in a given KPI such as engagement or sales. ... -
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10
NBA Sports Betting Machine Learning
NBA sports betting using machine learning
...Using this dataset, the project constructs matchup features that represent team performance trends and contextual information about each game. Machine learning models are then trained to estimate the probability that a team will win a game as well as whether the total score will fall above or below the sportsbook’s predicted total. In addition to predicting outcomes, the project evaluates expected value to determine whether a potential bet offers a statistical advantage compared with sportsbook odds. -
11
TokenCost
Easy token price estimates for 400+ LLMs. TokenOps
TokenCost is an open-source developer utility designed to estimate the cost of using large language model APIs by calculating token usage and translating it into real monetary values. The tool focuses on helping developers understand how much their prompts and generated completions cost when interacting with commercial AI models. It works by counting tokens in prompts and responses before or after sending requests and then applying pricing information associated with different models. ... -
12
SteadyDancer
Harmonized and Coherent Human Image Animation
SteadyDancer is a research-oriented motion stabilization and dancer tracking system designed to analyze and correct motion in videos, making captured performances appear smoother and more stable while preserving expressiveness. It employs computer vision and motion modeling to estimate and reduce unwanted jitters, shakes, or camera wobbles — particularly in dance or movement sequences where traditional smoothing would distort intentional motion. By differentiating between intentional rhythmic motion and unintentional instability, SteadyDancer applies adaptive filtering that enhances video quality without flattening the core movement dynamics. ... -
13
Koila
Prevent PyTorch's `CUDA error: out of memory` in just 1 line of code
Koila is a lightweight Python library designed to help developers avoid memory errors when training deep learning models with PyTorch. The library introduces a lazy evaluation mechanism that delays computation until it is actually required, allowing the framework to better estimate the memory requirements of a model before execution. By building a computational graph first and executing operations only when necessary, koila reduces the risk of running out of GPU memory during the forward pass of neural network training. This approach enables developers to experiment with larger batch sizes and more complex architectures while maintaining stable training behavior. ... -
14
Cleanlab
The standard data-centric AI package for data quality and ML
cleanlab helps you clean data and labels by automatically detecting issues in a ML dataset. To facilitate machine learning with messy, real-world data, this data-centric AI package uses your existing models to estimate dataset problems that can be fixed to train even better models. cleanlab cleans your data's labels via state-of-the-art confident learning algorithms, published in this paper and blog. See some of the datasets cleaned with cleanlab at labelerrors.com. This package helps you find label issues and other data issues, so you can train reliable ML models. ... -
15
Robyn
Experimental, AI/ML-powered and open sourced Marketing Mix Modeling
...Robyn takes in historical data (spends on different marketing channels, conversions, or revenue, and optional context or organic-media variables) and uses a combination of techniques, regularized regression (Ridge), time-series decomposition (trend, seasonality, holiday effects), and hyperparameter optimization (via evolutionary algorithms), to estimate the incremental impact of each marketing channel. It explicitly models “carry-over” (adstock) and diminishing-returns (saturation) effects per channel, enabling realistic modeling of how advertising persists over time and saturates. -
16
GNNPCSAFT
Smart Thermodynamic Modeling with Graph Neural Networks
The GNNPCSAFT app is an implementation of our project that focuses on using Graph Neural Networks (GNN) to estimate the pure-component parameters of the Equation of State PC-SAFT. We developed this app so the scientific community can access the model's results easily. In this app, the estimated pure-component parameters can be used to calculate thermodynamic properties and compare them with experimental data from the ThermoML Archive. -
17
GNNPCSAFT Web App
Smart Thermodynamic Modeling with Graph Neural Networks
The GNNPCSAFT Web App is an implementation of our project that focuses on using Graph Neural Networks (GNN) to estimate the pure-component parameters of the Equation of State PC-SAFT. We developed this app so the scientific community can access the model's results easily. In this app, the estimated pure-component parameters can be used to calculate thermodynamic properties and compare them with experimental data from the ThermoML Archive. - CPU-compatible desktop build The standard desktop release requires AVX2. ... -
18
SPPAS
SPPAS - the automatic annotation and analyses of speech
...SPPAS is able to produce automatically speech annotations from a recorded speech sound and its orthographic transcription. SPPAS is helpful for the analysis of any annotated data: estimate statistical distributions, make requests, manage files, visualize annotations. SPPAS offers a file converter from/to a wide range of formats: xra, TextGrid, eaf, trs... <https://sppas.org> -
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GNNPCSAFT Chat
Chatbot with GNNPCSAFT
The GNNPCSAFT Chat is an implementation of our project that focuses on using Graph Neural Networks (GNN) to estimate the pure-component parameters of the Equation of State PC-SAFT. We developed this app so the scientific community can access the model's results easily. In this app, you can chat with LLM models (Gemini or Ollama) with GNNPCSAFT tools, allowing you to ask questions about the PC-SAFT parameters of various compounds, predict thermodynamic properties, and get insights into the GNNPCSAFT's performance... -
20
Tempico software
Software to control and analyze Tausand Tempico timing data
...The software generates histograms from captured data, supports lifetime measurements via single-photon correlation (SPC), and displays real-time graphs with adjustable fitting options. It includes a 'Counts Estimation' panel to estimate count rates per channel over time, and a 'Time Stamping' feature to record timing of events. Users can view, configure, and control the device directly from the application, as well as save both raw data and graphical results for later analysis. Tempico Software is ideal for researchers working with photon timing and lifetime studies. -
21
footswitch2
Audio Transcription software for Linux (Vlc) with a foot pedal
Footswitch 2 is a media player for transcribers on Linux. Written in python and using the python bindings for VLC it allows a transcriber to control the audio or video with a USB footpedal, and includes a set of macros that integrate into LibreOffice. This allows the transcriber to control the media player from within Libreoffice as well, making it useful for those who do not yet own a footpedal/footswitch. Control of the media player from LibreOffice can be via Hotkeys or an integrated... -
22
GrainSizeTools script
A Python script for estimating the grain size from thin sections
Homepage & docs: http://marcoalopez.github.io/GrainSizeTools/ GrainSizeTools is a free, open-source, cross-platform script written in Python that provides several tools for (1) estimating average grain size in polycrystalline materials, (2) characterizing the nature of the distribution of grain sizes (either from apparent distributions or approximating 3D grain size distributions via stereology), and estimating differential stress via paleopizometers. The script requires as the input the... -
23
ALAMODE
Ab initio simulator for thermal transport and lattice anharmonicity
ALAMODE is designed for analyzing lattice anharmonicity and lattice thermal conductivity of solids. By using an external DFT package such as VASP and Quantum ESPRESSO, you can extract harmonic and anharmonic force constants straightforwardly with ALAMODE. Using the anharmonic force constants, you can also calculate lattice thermal conductivity from first principles. For more information about ALAMODE, please visit the following webpages: Documentation :... -
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footswitch3
Audio Transcription software for Linux (Gstreamer) with a foot pedal
Footswitch 3 is a media player for transcribers on Linux. Written in python using the python bindings for Gstreamer it allows a transcriber to control the audio or video with a foot pedal, and includes a set of macros that integrate into LibreOffice. This allows the transcriber to control the media player from within Libreoffice as well, making it useful for those who do not yet own a foot pedal/foot switch. Control of the media player from LibreOffice can be via Hotkeys or an integrated... -
25
Haircut_EQ
Fetches the historical Haircut data (%) of Equities and Gold Bonds
Haircut is the amount of margin money deducted while pledging the Equites/ Mutual Funds / Bonds for trading. A haircut value of 13% means that, if a share worth of Rs 100 is pledged for trading, then Rs. 13 will be deducted and Rs. 87 will be given as collateral margin for trading. It is based on previous closing price. This program is used to identify the real value of a share with date. It fetches the historical Haircut data (%) and Price of an equity listed in NSE, India at a...
