Search Results for "label"
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Showing 47 open source projects for "label"
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Out-of-the-box scripts. Around-the-clock monitoring. Unmatched automation capabilities. Start doing more with less and exceed service delivery expectations.
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Whether natural disaster, cyberattack, or plain-old human error, data can disappear in the blink of an eye. ConnectWise BCDR (formerly Recover) delivers reliable and secure backup and disaster recovery backed by powerful automation and a 24/7 NOC to get your clients back to work in minutes, not days.
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Label Studio
Label Studio is a multi-type data labeling and annotation tool
The most flexible data annotation tool. Quickly installable. Build custom UIs or use pre-built labeling templates. Detect objects on image, bboxes, polygons, circular, and keypoints supported. Partition image into multiple segments. Use ML models to pre-label and optimize the process. Label Studio is an open-source data labeling tool. It lets you label data types like audio, text, images, videos, and time series with a simple and straightforward UI and export to various model formats. It can... -
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Label Sleuth
Open source no-code system for text annotation and building of text
An open-source no-code system for text annotation and building text classifiers. No AI knowledge needed. From task definition to working model in just a few hours! While domain experts label their data, Label Sleuth automatically trains in the background-appropriate machine learning models. To avoid wasted labeling effort, Label Sleuth employs active learning techniques to guide the user in what they should be labeled next. Domain experts can quickly start labeling their data through... -
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labelme Image Polygonal Annotation
Image polygonal annotation with Python
Labelme is a graphical image annotation tool. It is written in Python and uses Qt for its graphical interface. Image annotation for polygon, rectangle, circle, line and point. Image flag annotation for classification and cleaning. Video annotation. (video annotation). GUI customization (predefined labels / flags, auto-saving, label validation, etc). Exporting VOC-format dataset for semantic/instance segmentation. (semantic segmentation, instance segmentation). Exporting COCO-format dataset... -
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Autolabel
Label, clean and enrich text datasets with LLMs
Autolabel is a Python library to label, clean and enrich datasets with Large Language Models (LLMs). Autolabel data for NLP tasks such as classification, question-answering and named entity recognition, entity matching and more. Seamlessly use commercial and open-source LLMs from providers such as OpenAI, Anthropic, HuggingFace, Google and more. -
BrightGauge, a ConnectWise solution, was started in 2011 to fill a missing need in the small-to-medium IT Services industry: a better way to manage data and provide the value of work to clients. BrightGauge Software allows you to display all of your important business metrics in one place through the use of gauges, dashboards, and client reports. Used by more than 1,800 companies worldwide, BrightGauge integrates with popular business solutions on the market, like ConnectWise, Continuum, Webroot, QuickBooks, Datto, IT Glue, Zendesk, Harvest, Smileback, and so many more. Dig deeper into your data by adding, subtracting, multiplying, and dividing one metric against another. BrightGauge automatically computes these formulas for you. Want to show your prospects how quick you are to respond to tickets? Show off your data with embeddable gauges on public sites.
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Scikit-LLM
Seamlessly integrate LLMs into scikit-learn
Seamlessly integrate powerful language models like ChatGPT into sci-kit-learn for enhanced text analysis tasks. At the moment the majority of the Scikit-LLM estimators are only compatible with some of the OpenAI models. Hence, a user-provided OpenAI API key is required. Additionally, Scikit-LLM will ensure that the obtained response contains a valid label. If this is not the case, a label will be selected randomly (label probabilities are proportional to label occurrences in the training set... -
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NanoDet-Plus
Lightweight anchor-free object detection model
Super fast and high accuracy lightweight anchor-free object detection model. Real-time on mobile devices. NanoDet is a FCOS-style one-stage anchor-free object detection model which using Generalized Focal Loss as classification and regression loss. In NanoDet-Plus, we propose a novel label assignment strategy with a simple assign guidance module (AGM) and a dynamic soft label assigner (DSLA) to solve the optimal label assignment problem in lightweight model training. We also introduce a light... -
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Raster Vision
Open source framework for deep learning satellite and aerial imagery
Raster Vision is an open source framework for Python developers building computer vision models on satellite, aerial, and other large imagery sets (including oblique drone imagery). There is built-in support for chip classification, object detection, and semantic segmentation using PyTorch. Raster Vision allows engineers to quickly and repeatably configure pipelines that go through core components of a machine learning workflow: analyzing training data, creating training chips, training... -
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Autodistill
Images to inference with no labeling
Autodistill uses big, slower foundation models to train small, faster supervised models. Using autodistill, you can go from unlabeled images to inference on a custom model running at the edge with no human intervention in between. You can use Autodistill on your own hardware, or use the Roboflow hosted version of Autodistill to label images in the cloud. -
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Cleanlab
The standard data-centric AI package for data quality and ML
... label issues and other data issues, so you can train reliable ML models. All features of cleanlab work with any dataset and any model. Yes, any model: PyTorch, Tensorflow, Keras, JAX, HuggingFace, OpenAI, XGBoost, scikit-learn, etc. If you use a sklearn-compatible classifier, all cleanlab methods work out-of-the-box. -
With the world of work changed forever, it’s essential to manage your workplace and assets together to effectively create a high-performing environment. The Eptura experience combines the power of workplace management software with asset management, enabling you to effectively operate your building and facilitate hybrid work.
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DeepCamera
Open-Source AI Camera. Empower any camera/CCTV
... technologies to detect intruders with traditional surveillance cameras. The source code is here It leverages Yolov7 as a person detector, FastReID for person feature extraction, Milvus the local vector database for self-supervised learning to identify unseen persons, Labelstudio to host images locally and for further usage such as label data and train your own classifier. It also integrates with Home-Assistant to empower smart homes with AI technology. -
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smclarify
Fairness aware machine learning. Bias detection and mitigation
Fairness Aware Machine Learning. Bias detection and mitigation for datasets and models. A facet is column or feature that will be used to measure bias against. A facet can have value(s) that designates that sample as "sensitive". Bias detection and mitigation for datasets and models. The label is a column or feature which is the target for training a machine learning model. The label can have value(s) that designates that sample as having a "positive" outcome. A bias measure is a function... -
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Compose
A machine learning tool for automated prediction engineering
... by using a label maker and a labeling function. The label maker automatically extracts data along the time index to generate labels. The process starts by setting the first cutoff time after the minimum amount of data. Then subsequent cutoff times are spaced apart using gaps. Starting from each cutoff time, a window determines the amount of data, also referred to as a data slice, to pass into a labeling function. -
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MONAI
AI Toolkit for Healthcare Imaging
The MONAI framework is the open-source foundation being created by Project MONAI. MONAI is a freely available, community-supported, PyTorch-based framework for deep learning in healthcare imaging. It provides domain-optimized foundational capabilities for developing healthcare imaging training workflows in a native PyTorch paradigm. Project MONAI also includes MONAI Label, an intelligent open source image labeling and learning tool that helps researchers and clinicians collaborate, create... -
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Streamline Analyst
AI agent that streamlines the entire process of data analysis
Streamline Analyst is a cutting-edge, open-source application powered by Large Language Models (LLMs) designed to revolutionize data analysis. This Data Analysis Agent effortlessly automates all the tasks such as data cleaning, preprocessing, and even complex operations like identifying target objects, partitioning test sets, and selecting the best-fit models based on your data. With Streamline Analyst, results visualization and evaluation become seamless. -
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snorkel
A system for quickly generating training data with weak supervision
... and systems structure to the messy and often entirely manual process of training data creation and management, starting by empowering users to programmatically label, build, and manage training data. Snorkel Flow, an end-to-end machine learning platform for developing and deploying AI applications. Snorkel Flow incorporates many of the concepts of the Snorkel project with a range of newer techniques around weak supervision modeling, data augmentation, multi-task learning, data slicing and structuring. -
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Featuretools
An open source python library for automated feature engineering
An open source Python framework for automated feature engineering. Featuretools automatically creates features from temporal and relational datasets. Featuretools uses DFS for automated feature engineering. You can combine your raw data with what you know about your data to build meaningful features for machine learning and predictive modeling. Featuretools provides APIs to ensure only valid data is used for calculations, keeping your feature vectors safe from common label leakage problems. You... -
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PML
The easiest way to use deep metric learning in your application
... into it. Anchor-positive pairs are formed by embeddings that share the same label, and anchor-negative pairs are formed by embeddings that have different labels. Loss functions can be customized using distances, reducers, and regularizers. In the diagram below, a miner finds the indices of hard pairs within a batch. These are used to index into the distance matrix, computed by the distance object. For this diagram, the loss function is pair-based, so it computes a loss per pair. -
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Codeball AI
AI Code Review that finds bugs and fast-tracks your code
Codeball is a code review AI that scores pull requests on a grade from 0 (needs careful review) to 1. Use Codeball to add labels to help you focus, auto-approve PRs, and more. The Codeball action is easy to use (sane defaults) and is highly customizable to fit your workflow when needed. Label PRs when you should review them with caution. Stay sharp, don't let the bugs pass through. Identifies and approves or labels safe PRs. Save time by fast-tracking PRs that are easy to review. Fully... -
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MEKA
A Multi-label Extension to Weka
Multi-label classifiers and evaluation procedures using the Weka machine learning framework. -
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Universal Data Tool
Collaborate & label any type of data, images, text, or documents etc.
An open-source tool and library for creating and labeling datasets of images, audio, text, documents and video in an open data format. The Universal Data Tool can be used by anyone on your team, no data or programming skills needed. Simplicity without sacrificing any powerful developer features and integrations. Use the Universal Data Tool directly from a web browser or with a Windows, Mac or Linux desktop application. Join a link to a collaborative session and see dataset samples from team... -
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Awesome Community Detection Research
A curated list of community detection research papers
A collection of community detection papers. A curated list of community detection research papers with implementations. Similar collections about graph classification, classification/regression tree, fraud detection, and gradient boosting papers with implementations. -
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Awesome Graph Classification
Graph embedding, classification and representation learning papers
A collection of graph classification methods, covering embedding, deep learning, graph kernel and factorization papers with reference implementations. Relevant graph classification benchmark datasets are available. Similar collections about community detection, classification/regression tree, fraud detection, Monte Carlo tree search, and gradient boosting papers with implementations. -
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Cloud Annotations
A fast, easy and collaborative open source image annotation tool
... for your project is easy inside CV Studio. For classification projects, just select and label your images. For object detection, use the integrated tool to highlight target elements in your images. Train your model using the image annotations from the previous step. Practice using cutting-edge tools like Jupyter Notebook, Watson Machine Learning, Elyra, and more. -
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bbox-visualizer
Make drawing and labeling bounding boxes easy as cake
Make drawing and labeling bounding boxes easy as cake. This package helps users draw bounding boxes around objects, without doing the clumsy math that you'd need to do for positioning the labels. It also has a few different types of visualizations you can use for labeling objects after identifying them. There are optional functions that can draw multiple bounding boxes and/or write multiple labels on the same image, but it is advisable to use the above functions in a loop in order to have... -
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CNN Explainer
Learning Convolutional Neural Networks with Interactive Visualization
In machine learning, a classifier assigns a class label to a data point. For example, an image classifier produces a class label (e.g, bird, plane) for what objects exist within an image. A convolutional neural network, or CNN for short, is a type of classifier, which excels at solving this problem! A CNN is a neural network: an algorithm used to recognize patterns in data. Neural Networks in general are composed of a collection of neurons that are organized in layers, each with their own...