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PixelAnnotationTool - Annotate quickly images.
Software that allows you to manually and quickly annotate images in directories. The method is pseudo manual because it uses the algorithm watershed marked of OpenCV. The general idea is to manually provide the marker with brushes and then to launch the algorithm. If at first pass the segmentation needs to be corrected, the user can refine the markers by drawing new ones on the erroneous areas (as shown on video below). Donating is very simple - and secure. Please click here to make a donation.
opencv computer-vision deep-learning annotation tool pixel qt5 ground-truth annotation-tool image-labeling labeling-tool pixel-wise image-seg-tooluniversal-data-tool - Collaborate & label any type of data, images, text, or documents, in an easy web interface or desktop app
Try it out at udt.dev, download the desktop app or run on-premise. The Universal Data Tool is a web/desktop app for editing and annotating images, text, audio, documents and to view and edit any data defined in the extensible .udt.json and .udt.csv standard.
machine-learning csv computer-vision deep-learning image-annotation desktop dataset named-entity-recognition classification labeling image-segmentation hacktoberfest semantic-segmentation annotation-tool text-annotation labeling-tool entity-recognition annotate-images image-labeling-tool text-labelingdoccano - Open source annotation tool for machine learning practitioners.
doccano is an open source text annotation tool for humans. It provides annotation features for text classification, sequence labeling and sequence to sequence tasks. So, you can create labeled data for sentiment analysis, named entity recognition, text summarization and so on. Just create a project, upload data and start annotating. You can build a dataset in hours. You can try the annotation demo.
machine-learning natural-language-processing vuejs vue nuxt dataset datasets nuxtjs annotation-tool text-annotation data-labelingcvat - Computer Vision Annotation Tool (CVAT) is a web-based tool which helps to annotate video and images for Computer Vision algorithms
CVAT is completely re-designed and re-implemented version of Video Annotation Tool from Irvine, California tool. It is free, online, interactive video and image annotation tool for computer vision. It is being used by our team to annotate million of objects with different properties. Many UI and UX decisions are based on feedbacks from professional data annotation team. Code released under the MIT License.
video-annotation computer-vision computer-vision-annotation deep-learning image-annotation annotation-tool annotation labeling labeling-tool image-labeling image-labelling-tool bounding-boxes boundingbox image-classification annotations imagenet detection recognition tensorflowRUBRIX - Python framework to explore, label, and monitor data for NLP
Rubrix is a production-ready Python framework for exploring, annotating, and managing data in NLP projects. Most annotation tools treat data collection as a one-off activity at the beginning of each project. In real-world projects, data collection is a key activity of the iterative process of ML model development. Once a model goes into production, you want to monitor and analyze its predictions, and collect more data to improve your model over time. Rubrix is designed to close this gap, enabling you to iterate as much as you need.
nlp elasticsearch data-science machine-learning natural-language-processing pytorch artificial-intelligence weak-supervision knowledge-graph developer-tools active-learning annotation-tool weakly-supervised-learning human-in-the-loop mlops text-labelingprodigy-recipes - 🍳 Recipes for the Prodigy, our fully scriptable annotation tool
This repository contains a collection of recipes for Prodigy, our scriptable annotation tool for text, images and other data. In order to use this repo, you'll need a license for Prodigy – see this page for more details. For questions and bug reports, please use the Prodigy Support Forum. If you've found a mistake or bug, feel free to submit a pull request. ✨ Important note: The recipes in this repository aren't 100% identical to the built-in recipes shipped with Prodigy. They've been edited to include comments and more information, and some of them have been simplified to make it easier to follow what's going on, and to use them as the basis for a custom recipe.
nlp data-science machine-learning natural-language-processing computer-vision annotation artificial-intelligence spacy prodigy active-learning annotation-tool data-annotation labeling-tool machine-teachingflat - FoLiA Linguistic Annotation Tool -- Flat is a web-based linguistic annotation environment based around the FoLiA format (http://proycon
FLAT is a web-based linguistic annotation environment based around the FoLiA format (http://proycon.github.io/folia), a rich XML-based format for linguistic annotation. FLAT allows users to view annotated FoLiA documents and enrich these documents with new annotations, a wide variety of linguistic annotation types is supported through the FoLiA paradigm. It is a document-centric tool that fully preserves and visualises document structure. FLAT is written in Python using the Django framework. The user interface is written using javascript with jquery. The FoLiA Document Server (https://github.com/proycon/foliadocserve) , the back-end of the system, is written in Python with CherryPy and is used as a RESTful webservice.
nlp annotation-tool web-application folia computational-linguistics linguisticspangea - Panoramic Graph Environment Annotation toolkit, for collecting audio and text annotations in panoramic graph environments such as Matterport3D and StreetLearn
The Panoramic Graph Environment Annotation toolkit, abbreviated as PanGEA, is a lightweight and customizable codebase for collecting audio and text annotations in panoramic graph environments, such as Matterport3D and StreetLearn. PanGEA has been used to collect the RxR dataset of multilingual navigation instructions, and to perform human wayfinding evaluations of machine-generated navigation instructions. The src directory contains the core components used to create a plugin.
nlp computer-vision crowdsourcing annotation-toolpiaf - Question Answering annotation platform - Plateforme d'annotation
As a prerequisite, you need to have installed Docker & Docker-compose on your computer.
natural-language-processing ai annotation question-answering annotation-tool text-annotation piafdata-annotator-for-machine-learning - Data annotator for machine learning allows you to centrally create, manage and administer annotation projects for machine learning
Data Annotator for Machine Learning (DAML) is an application that helps machine learning teams facilitating the creation and management of annotations. DAML project team welcomes contributions from the community. For more detailed information, see CONTRIBUTING.md.
deep-learning image-annotation annotation named-entity-recognition annotation-tool text-annotation tabular labeling-toolauto-labeling-pipeline - doccano auto labeling pipeline helps doccano to annotate a document automatically
Auto labeling pipeline helps doccano to annotate a document automatically. This package is intended to be used from the inside of doccano. You shouldn't use this package directly.
machine-learning natural-language-processing annotation-tool text-annotation data-labeling doccanoawesome-annotation-tools - A curated list of awesome data annotation tools
A curated list of awesome annotation tools. Please feel free to pull requests to add links. Caution: This is based on my survey about a year ago. I will update it asap.
awesome annotation awesome-list annotation-tool data-labelingjupyterlab-prodigy - 🧬 A JupyterLab extension for annotating data with Prodigy
This repo contains a JupyterLab extension for Prodigy, our scriptable annotation tool for creating training data for machine learning models. It lets you run Prodigy within a JupyterLab tab, and annotate as you develop your models and applications. In order to use this extension, you'll need a license for Prodigy – see this page for more details. For questions, please use the Prodigy Support Forum. If you've found a bug, feel free to submit a pull request. To use this extension, you need JupyterLab >= 2.0.0 ⚠️ and Prodigy.
nlp data-science machine-learning natural-language-processing computer-vision jupyter annotation artificial-intelligence spacy jupyterlab prodigy active-learning annotation-tool data-annotation labeling-tool machine-teaching jupyterlab-extension
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