Best AI tools for< Annotate Datasets >

Patee.io is an AI-powered platform that helps businesses automate their data annotation and labeling tasks. With Patee.io, businesses can easily create, manage, and annotate large datasets, which can then be used to train machine learning models. Patee.io offers a variety of features that make it easy to annotate data, including a user-friendly interface, a variety of annotation tools, and the ability to collaborate with others. Patee.io also offers a number of pre-built models that can be used to automate the annotation process, saving businesses time and money.

Cogitotech is an AI tool that specializes in data annotation and labeling expertise. The platform offers a comprehensive suite of services tailored to meet training data needs for computer vision models and AI applications. With a decade-long industry exposure, Cogitotech provides high-quality training data for industries like healthcare, financial services, security, and more. The platform helps minimize biases in AI algorithms and ensures accurate and reliable training data solutions for deploying AI in real-life systems.

Globose Technology Solutions Pvt Ltd (GTS) is an AI data collection company that provides various datasets such as image datasets, video datasets, text datasets, speech datasets, etc., to train machine learning models. They offer premium data collection services with a human touch, aiming to refine AI vision and propel AI forward. With over 25+ years of experience, they specialize in data management, annotation, and effective data collection techniques for AI/ML. The company focuses on unlocking high-quality data, understanding AI's transformative impact, and ensuring data accuracy as the backbone of reliable AI.

Shaip is a human-powered data processing service specializing in AI and ML models. They offer a wide range of services including data collection, annotation, de-identification, and more. Shaip provides high-quality training data for various AI applications, such as healthcare AI, conversational AI, and computer vision. With over 15 years of expertise, Shaip helps organizations unlock critical information from unstructured data, enabling them to achieve better results in their AI initiatives.

V7 is an AI data engine for computer vision and generative AI. It provides a multimodal automation tool that helps users label data 10x faster, power AI products via API, build AI + human workflows, and reach 99% AI accuracy. V7's platform includes features such as automated annotation, DICOM annotation, dataset management, model management, image annotation, video annotation, document processing, and labeling services.

Pulan is a comprehensive platform designed to assist in collecting, curating, annotating, and evaluating data points for various AI initiatives. It offers services in Natural Language Processing, Data Annotation, and Computer Vision across multiple industries such as Agriculture, Medical, Life Sciences, Government, Automotive, Insurance & Finance, Logistics, Software & Internet, Manufacturing, Retail, Construction, Energy, and Food & Beverage. Pulan provides a one-stop destination for reliable data collection and curation by industry experts, with a vast inventory of millions of datasets available for licensing at a fraction of the cost of creating the data oneself.

OpenTrain AI is a data labeling marketplace that leverages artificial intelligence to streamline the process of labeling data for machine learning models. It provides a platform where users can crowdsource data labeling tasks to a global community of annotators, ensuring high-quality labeled datasets for training AI algorithms. With advanced AI algorithms and human-in-the-loop validation, OpenTrain AI offers efficient and accurate data labeling services for various industries such as autonomous vehicles, healthcare, and natural language processing.

Innovatiana is a data labeling outsourcing platform that offers high-quality datasets for artificial intelligence models. They specialize in image, audio/video, and text data labeling tasks, providing ethical outsourcing with a focus on impact and transparency. Innovatiana recruits and trains their own team in Madagascar, ensuring fair pay and good working conditions. They offer competitive rates, secure data handling, and high-quality labeled data to feed AI models. The platform supports various AI tasks such as Computer Vision, Data Collection, Data Moderation, Documents Processing, and Natural Language Processing.

Datature is an all-in-one platform for building and deploying computer vision models. It provides tools for data management, annotation, training, and deployment, making it easy to develop and implement computer vision solutions. Datature is used by a variety of industries, including healthcare, retail, manufacturing, and agriculture.

Satlas is an AI-powered platform that provides geospatial data generated by AI models. The platform showcases how our planet is changing by revealing insights into marine infrastructure, renewable energy infrastructure, and tree cover. Satlas employs state-of-the-art AI architectures and training algorithms in computer vision to enhance low-resolution satellite imagery and produce high-resolution images on a global scale. The AI-generated geospatial datasets are freely available for offline analysis, along with AI models and training labels. The platform is developed and maintained by PRIOR and colleagues at the Allen Institute for AI, aiming to advance computer vision and create AI systems that understand and reason about the world.

Roboflow is an AI tool designed for computer vision tasks, offering a platform that allows users to annotate, train, deploy, and perform inference on models. It provides integrations, ecosystem support, and features like notebooks, autodistillation, and supervision. Roboflow caters to various industries such as aerospace, agriculture, healthcare, finance, and more, with a focus on simplifying the development and deployment of computer vision models.

CVAT is an open-source data annotation platform that helps teams of any size annotate data for machine learning. It is used by companies big and small in a variety of industries, including healthcare, retail, and automotive. CVAT is known for its intuitive user interface, advanced features, and support for a wide range of data formats. It is also highly extensible, allowing users to add their own custom features and integrations.

LightPDF is an AI-powered, free online PDF editor, converter, and reader. It offers a wide range of PDF tools, including the ability to convert PDFs to and from other formats, edit PDFs, add watermarks, split and merge PDFs, rotate PDFs, annotate PDFs, optimize PDFs, compress PDFs, perform OCR on PDFs, and protect PDFs. LightPDF also offers a variety of AI-powered features, such as an AI chatbot that can answer questions about documents and an AI-powered OCR engine that can convert scanned PDFs and images to text.

Tube Memo is an AI-powered tool designed to facilitate effortless note-taking from YouTube videos. It allows users to capture transcripts, organize notes, and generate summaries from videos. The tool enhances productivity by providing features like timestamped transcripts, AI-powered summaries, content organizing, and the ability to easily share and download notes. Users can collaborate with team members, categorize and tag memos for efficient searching, and access their notes across various devices. Tube Memo aims to streamline the process of extracting key insights from video content, making it a valuable asset for students, professionals, content creators, and researchers.

UPDF is an AI-integrated PDF editor, converter, annotator, and reader that offers a comprehensive set of features for seamless PDF editing. It provides cross-platform support on Windows, Mac, iOS, and Android devices. With UPDF AI capabilities, users can summarize, translate, and chat with PDF, making it a versatile tool for various tasks. The application is user-friendly, well-priced, and reliable, catering to both individual and enterprise needs. UPDF also offers localized interface in 11 languages and responsive customer support.

Encord is a complete data development platform designed for AI applications, specifically tailored for computer vision and multimodal AI teams. It offers tools to intelligently manage, clean, and curate data, streamline labeling and workflow management, and evaluate model performance. Encord aims to unlock the potential of AI for organizations by simplifying data-centric AI pipelines, enabling the building of better models and deploying high-quality production AI faster.

UBIAI is a powerful text annotation tool that helps businesses accelerate their data labeling process. With UBIAI, businesses can annotate any type of document, including PDFs, images, and text. UBIAI also offers a variety of features to make the annotation process easier and more efficient, such as auto-labeling, multi-lingual annotation, and team collaboration. With UBIAI, businesses can save time and money on their data labeling projects.

DeepVinci is an AI-powered platform that helps businesses automate their workflows and make better decisions. It offers a range of features, including data annotation, model training, and predictive analytics.

Cogniroot is an AI-powered platform that helps businesses automate their data annotation and data labeling processes. It provides a suite of tools and services that make it easy for businesses to train their machine learning models with high-quality data. Cogniroot's platform is designed to be scalable, efficient, and cost-effective, making it a valuable tool for businesses of all sizes.

OpenAI01.net is an AI tool that offers free usage with some limitations. It provides a new series of AI models designed to spend more time thinking before responding, capable of reasoning through complex tasks and solving harder problems in science, coding, and math. Users can ask questions and get answers for free, with the option to select different models based on credits. The tool excels in complex reasoning tasks and has shown impressive performance in various benchmarks.

LLM Datasets is a repository containing high-quality datasets, tools, and concepts for LLM fine-tuning. It provides datasets with characteristics like accuracy, diversity, and complexity to train large language models for various tasks. The repository includes datasets for general-purpose, math & logic, code, conversation & role-play, and agent & function calling domains. It also offers guidance on creating high-quality datasets through data deduplication, data quality assessment, data exploration, and data generation techniques.

DataDreamer is an advanced toolkit designed to facilitate the development of edge AI models by enabling synthetic data generation, knowledge extraction from pre-trained models, and creation of efficient and potent models. It eliminates the need for extensive datasets by generating synthetic datasets, leverages latent knowledge from pre-trained models, and focuses on creating compact models suitable for integration into any device and performance for specialized tasks. The toolkit offers features like prompt generation, image generation, dataset annotation, and tools for training small-scale neural networks for edge deployment. It provides hardware requirements, usage instructions, available models, and limitations to consider while using the library.

GPT4Point is a unified framework for point-language understanding and generation. It aligns 3D point clouds with language, providing a comprehensive solution for tasks such as 3D captioning and controlled 3D generation. The project includes an automated point-language dataset annotation engine, a novel object-level point cloud benchmark, and a 3D multi-modality model. Users can train and evaluate models using the provided code and datasets, with a focus on improving models' understanding capabilities and facilitating the generation of 3D objects.

AI Audio Datasets List (AI-ADL) is a comprehensive collection of datasets consisting of speech, music, and sound effects, used for Generative AI, AIGC, AI model training, and audio applications. It includes datasets for speech recognition, speech synthesis, music information retrieval, music generation, audio processing, sound synthesis, and more. The repository provides a curated list of diverse datasets suitable for various AI audio tasks.

SoM-LLaVA is a new data source and learning paradigm for Multimodal LLMs, empowering open-source Multimodal LLMs with Set-of-Mark prompting and improved visual reasoning ability. The repository provides a new dataset that is complementary to existing training sources, enhancing multimodal LLMs with Set-of-Mark prompting and improved general capacity. By adding 30k SoM data to the visual instruction tuning stage of LLaVA, the tool achieves 1% to 6% relative improvements on all benchmarks. Users can train SoM-LLaVA via command line and utilize the implementation to annotate COCO images with SoM. Additionally, the tool can be loaded in Huggingface for further usage.

Vodalus Expert LLM Forge is a tool designed for crafting datasets and efficiently fine-tuning models using free open-source tools. It includes components for data generation, LLM interaction, RAG engine integration, model training, fine-tuning, and quantization. The tool is suitable for users at all levels and is accompanied by comprehensive documentation. Users can generate synthetic data, interact with LLMs, train models, and optimize performance for local execution. The tool provides detailed guides and instructions for setup, usage, and customization.

This repository provides a curated list of papers, datasets, and resources related to the detection and mitigation of hallucinations in large language models (LLMs). Hallucinations refer to the generation of factually incorrect or nonsensical text by LLMs, which can be a significant challenge for their use in real-world applications. The resources in this repository aim to help researchers and practitioners better understand and address this issue.

Open-Sora-Plan is a project that aims to create a simple and scalable repo to reproduce Sora (OpenAI, but we prefer to call it "ClosedAI"). The project is still in its early stages, but the team is working hard to improve it and make it more accessible to the open-source community. The project is currently focused on training an unconditional model on a landscape dataset, but the team plans to expand the scope of the project in the future to include text2video experiments, training on video2text datasets, and controlling the model with more conditions.

Awesome-Segment-Anything is a powerful tool for segmenting and extracting information from various types of data. It provides a user-friendly interface to easily define segmentation rules and apply them to text, images, and other data formats. The tool supports both supervised and unsupervised segmentation methods, allowing users to customize the segmentation process based on their specific needs. With its versatile functionality and intuitive design, Awesome-Segment-Anything is ideal for data analysts, researchers, content creators, and anyone looking to efficiently extract valuable insights from complex datasets.

Zshot is a highly customizable framework for performing Zero and Few shot named entity and relationships recognition. It can be used for mentions extraction, wikification, zero and few shot named entity recognition, zero and few shot named relationship recognition, and visualization of zero-shot NER and RE extraction. The framework consists of two main components: the mentions extractor and the linker. There are multiple mentions extractors and linkers available, each serving a specific purpose. Zshot also includes a relations extractor and a knowledge extractor for extracting relations among entities and performing entity classification. The tool requires Python 3.6+ and dependencies like spacy, torch, transformers, evaluate, and datasets for evaluation over datasets like OntoNotes. Optional dependencies include flair and blink for additional functionalities. Zshot provides examples, tutorials, and evaluation methods to assess the performance of the components.

At ZenML, we believe in the importance of annotation and labeling workflows in the machine learning lifecycle. This repository showcases a curated list of open-source data annotation and labeling tools that are actively maintained and fit for purpose. The tools cover various domains such as multi-modal, text, images, audio, video, time series, and other data types. Users can contribute to the list and discover tools for tasks like named entity recognition, data annotation for machine learning, image and video annotation, text classification, sequence labeling, object detection, and more. The repository aims to help users enhance their data-centric workflows by leveraging these tools.

This repository, Online RLHF, focuses on aligning large language models (LLMs) through online iterative Reinforcement Learning from Human Feedback (RLHF). It aims to bridge the gap in existing open-source RLHF projects by providing a detailed recipe for online iterative RLHF. The workflow presented here has shown to outperform offline counterparts in recent LLM literature, achieving comparable or better results than LLaMA3-8B-instruct using only open-source data. The repository includes model releases for SFT, Reward model, and RLHF model, along with installation instructions for both inference and training environments. Users can follow step-by-step guidance for supervised fine-tuning, reward modeling, data generation, data annotation, and training, ultimately enabling iterative training to run automatically.

HuixiangDou is a **group chat** assistant based on LLM (Large Language Model). Advantages: 1. Design a two-stage pipeline of rejection and response to cope with group chat scenario, answer user questions without message flooding, see arxiv2401.08772 2. Low cost, requiring only 1.5GB memory and no need for training 3. Offers a complete suite of Web, Android, and pipeline source code, which is industrial-grade and commercially viable Check out the scenes in which HuixiangDou are running and join WeChat Group to try AI assistant inside. If this helps you, please give it a star ⭐

Comet Opik is a repository containing two main services: a frontend and a backend. It provides a Python SDK for easy installation. Users can run the full application locally with minikube, following specific installation prerequisites. The repository structure includes directories for applications like Opik backend, with detailed instructions available in the README files. Users can manage the installation using simple k8s commands and interact with the application via URLs for checking the running application and API documentation. The repository aims to facilitate local development and testing of Opik using Kubernetes technology.

Embedded inference of Deep Learning models is quite challenging due to high compute requirements. TI’s Edge AI software product helps optimize and accelerate inference on TI’s embedded devices. It supports heterogeneous execution of DNNs across cortex-A based MPUs, TI’s latest generation C7x DSP, and DNN accelerator (MMA). The solution simplifies the product life cycle of DNN development and deployment by providing a rich set of tools and optimized libraries.

Awesome MLOps is a curated list of tools related to Machine Learning Operations, covering areas such as AutoML, CI/CD for Machine Learning, Data Cataloging, Data Enrichment, Data Exploration, Data Management, Data Processing, Data Validation, Data Visualization, Drift Detection, Feature Engineering, Feature Store, Hyperparameter Tuning, Knowledge Sharing, Machine Learning Platforms, Model Fairness and Privacy, Model Interpretability, Model Lifecycle, Model Serving, Model Testing & Validation, Optimization Tools, Simplification Tools, Visual Analysis and Debugging, and Workflow Tools. The repository provides a comprehensive collection of tools and resources for individuals and teams working in the field of MLOps.

Helps annotate project guidelines.

An assistant for annotating and improving fiction writing, chapter by chapter.

Python code annotator and test generator

I write Qiskit code for quantum algorithms with annotations.

Expert in PDF tasks and tool advice.

Tipps zu AutoCAD 2023 & StadtCAD24, Fokus auf AutoCAD

A detailed expert trained on all 1,823 pages of Apple PencilKit, offering complete coding solutions. Saving time? https://www.buymeacoffee.com/parkerrex ☕️❤️

A visual analysis expert who guesses image locations.