Best AI tools for< Add Annotations >

**万兴科技** is an AI-powered tool that helps users create and edit PDF documents. It offers a wide range of features, including the ability to convert PDFs to other formats, edit text and images, and add annotations. **万兴科技** is a valuable tool for anyone who needs to work with PDFs on a regular basis.

Connected Papers is a search engine for academic papers that uses artificial intelligence to help users find and explore relevant research. It allows users to search for papers by keyword, author, or title, and then explore the connections between them. Connected Papers also provides a variety of tools to help users organize and manage their research, including the ability to create custom collections of papers, add notes and annotations, and share their research with others.

EchoScribe is an AI-powered transcription and note-taking tool that helps you capture, organize, and share your ideas and conversations. With EchoScribe, you can easily record and transcribe audio and video, add notes and annotations, and collaborate with others in real-time. EchoScribe is perfect for students, journalists, researchers, and anyone who needs to capture and share information efficiently.

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.

Clarity AI is an AI-powered technology platform that offers a Sustainability Tech Kit for sustainable investing, shopping, reporting, and benchmarking. The platform provides built-in sustainability technology with customizable solutions for various needs related to data, methodologies, and tools. It seamlessly integrates into workflows, offering scalable and flexible end-to-end SaaS tools to address sustainability use cases. Clarity AI leverages powerful AI and machine learning to analyze vast amounts of data points, ensuring reliable and transparent data coverage. The platform is designed to empower users to assess, analyze, and report on sustainability aspects efficiently and confidently.

EnhanceAI is a tool that allows you to add AI-powered autocomplete to any website in just 2 minutes. It integrates with all major no-code tools and UI frameworks, and it's easy to use. Just add a few lines of code to your website, and you're good to go. EnhanceAI uses OpenAI's GPT models, so you can be sure that you're getting the most accurate and up-to-date AI technology. With EnhanceAI, you can create AI-powered forms, surveys, text inputs, and more. You can also use EnhanceAI to generate creative content, such as art prompts and sales copy. EnhanceAI is the perfect tool for anyone who wants to add AI to their website or product.

Feelsy is a social media sentiment analysis tool that helps businesses understand how their audience feels about their content. With Feelsy, businesses can track the sentiment of their Instagram comments in real-time, identify the content that resonates most with their audience, and measure the effectiveness of their social media campaigns.

Supertranslate is an AI-powered tool that allows users to automatically add English subtitles to videos in any language. It leverages OpenAI's Whisper, the world's most accurate speech-to-text engine, to provide high-quality subtitles. The tool offers a fluid subtitle editor that enables users to intuitively split, merge, and adjust timecodes of the generated subtitles. Supertranslate is designed to be user-friendly and efficient, making it the fastest way to subtitle videos without the need for manual transcription.

Double Subtitles is an AI-powered tool that helps you add subtitles to your videos quickly and easily. With 90% of mobile videos being watched on mute, it's more important than ever to make sure your viewers can understand your content. Double Subtitles uses advanced AI algorithms to generate accurate, precise, and fast subtitles. It's 90% more accurate, 20x faster, and 3x lower cost than the competition. Plus, you can customize the style of your subtitles to match your brand. With Double Subtitles, you can be sure that your viewers will understand your content, no matter how they're watching it.

DocGPT.ai is an AI-powered tool designed to enhance productivity and efficiency in various tasks such as email writing, document generation, content creation, SEO optimization, data enrichment, and more. It seamlessly integrates with Google Workspace applications to provide users with advanced AI capabilities for content generation and management. With support for multiple AI models and a wide range of features, DocGPT.ai is a comprehensive solution for individuals and businesses looking to streamline their workflows and improve their content creation processes.

AI Mail Assistant is a Gmail add-on powered by OpenAI's ChatGPT that helps users streamline their email communication. It offers a range of features including generating quick and accurate email responses, summarizing emails, translating messages, and improving the grammar and wording of drafts. The tool is designed to save time, avoid language barriers and mistakes, and ensure clear and professional communication.

Puppetry is an AI tool that enables video content creators, game artists, educators, and marketers to create engaging and informative videos using AI puppets. It provides a comprehensive toolset for face animation, allowing users to generate talking videos and craft compelling scripts with the power of ChatGPT. With features like AI voice and avatar creation, realistic avatars, advanced technology, and intuitive user interface, Puppetry offers a versatile solution for creating AI-driven avatars and animated faces.

VEED.IO is an online video editor that uses AI to help users create professional-quality videos quickly and easily. With VEED.IO, users can add subtitles, remove background noise, and more. VEED.IO is also a great tool for creating videos for social media, marketing, and education.

Nova AI is a cloud-based video editing platform that provides users with a wide range of tools and features to create and edit videos. The platform is designed to be easy to use, even for beginners, and it offers a variety of features that are typically only found in professional video editing software. With Nova AI, users can trim, cut, merge, and resize videos, as well as add text, images, and music. The platform also includes a number of AI-powered features, such as automatic subtitle generation, text-to-speech, and video translation. Nova AI is a powerful and versatile video editing platform that is suitable for a wide range of users, from beginners to professionals.

Editby is an AI-powered content creation tool that helps users create SEO-optimized content that ranks on Google and social media. It offers a range of features to help users create high-quality content, including AI-powered recommendations, trending content suggestions, and plagiarism detection. Editby also integrates with a variety of platforms, making it easy to publish content anywhere you need it.

Zeemo AI is a powerful caption generator and AI tool that enables users to add subtitles to videos effortlessly. With the ability to transcribe audio and video, translate captions into multiple languages, and create dynamic visual effects, Zeemo AI streamlines the video captioning process for content creators, educators, and businesses. The platform offers a user-friendly interface, supports over 113 languages, and provides accurate captions with high recognition accuracy. Zeemo AI aims to enhance video accessibility and engagement across various social media platforms.

SubTitles.Love is an AI-powered online subtitles editor that helps users easily add subtitles to their videos. The tool offers features such as auto speech recognition, support for 10+ languages, and simple editing capabilities. Users can upload any video format, tune subtitles with high accuracy, and customize the appearance before downloading the subtitled video. SubTitles.Love aims to save time and enhance audience engagement by providing automatic subtitles, resizing for social media, and affordable pricing. The platform is trusted by bloggers, podcast makers, and content producers for its quality service and community-driven approach.

Bytecap is an AI application that allows users to immerse their videos with custom AI captions. It offers features such as auto creation of 99% accurate captions using advanced speech recognition, customization of captions with fonts, colors, emojis, effects, music, and highlights, and AI-generated hook titles and descriptions for boosting engagement. Bytecap supports over 99 languages, provides complete caption control, and offers trendy sounds and background music options. The application caters to video editors, content creators, podcasters, and streamers, enabling them to save time, expand reach, and increase brand awareness. Bytecap ensures privacy and security, offers free trial options, and allows users to edit captions after creation.

Alva Solutions is an AI-powered browser extension application that aims to simplify browsing experience by providing a range of AI browser extensions. The application offers diverse browser extensions such as Alva AI, Alva Network, and Snap AI, each designed to enhance productivity and streamline tasks. Users can benefit from features like AI-powered assistance, network insights, and voice recording capabilities. Alva Solutions prioritizes user privacy and data security, offering a safe environment with premium protection features. With a user-friendly interface and intuitive dashboard, users can easily manage and control their extensions. The application also fosters a community environment through various social media platforms, providing users with updates, tutorials, and engaging discussions.

ChatBuild AI is a website that allows users to create custom trained AI chatbots for their website in minutes. No coding experience is needed. Users can upload files to train their chatbot, and ChatBuild AI will generate a custom chatbot that is trained on the user's own data. ChatBuild AI also offers global support, so users can use their chatbot in any language.

Aiohttp pydantic is an aiohttp view to easily parse and validate requests. You define using function annotations what your methods for handling HTTP verbs expect, and Aiohttp pydantic parses the HTTP request for you, validates the data, and injects the parameters you want. It provides features like query string, request body, URL path, and HTTP headers validation, as well as Open API Specification generation.

Jarvis is an AI note-taking assistant for Joplin, powered by online and offline LLMs (such as OpenAI's ChatGPT or GPT-4, Hugging Face, Google PaLM, Universal Sentence Encoder). You can chat with it (including prompt templates), use your personal notes as additional context in the chat, automatically annotate notes, perform semantic search, or compile an automatic review of the scientific literature.

This Helm chart bootstraps an Airflow deployment on a Kubernetes cluster using the Helm package manager. The version of this chart does not correlate to any other component. Users should not expect feature parity between OSS airflow chart and the Astronomer airflow-chart for identical version numbers. To install this helm chart remotely (using helm 3) kubectl create namespace airflow helm repo add astronomer https://helm.astronomer.io helm install airflow --namespace airflow astronomer/airflow To install this repository from source sh kubectl create namespace airflow helm install --namespace airflow . Prerequisites: Kubernetes 1.12+ Helm 3.6+ PV provisioner support in the underlying infrastructure Installing the Chart: sh helm install --name my-release . The command deploys Airflow on the Kubernetes cluster in the default configuration. The Parameters section lists the parameters that can be configured during installation. Upgrading the Chart: First, look at the updating documentation to identify any backwards-incompatible changes. To upgrade the chart with the release name `my-release`: sh helm upgrade --name my-release . Uninstalling the Chart: To uninstall/delete the `my-release` deployment: sh helm delete my-release The command removes all the Kubernetes components associated with the chart and deletes the release. Updating DAGs: Bake DAGs in Docker image The recommended way to update your DAGs with this chart is to build a new docker image with the latest code (`docker build -t my-company/airflow:8a0da78 .`), push it to an accessible registry (`docker push my-company/airflow:8a0da78`), then update the Airflow pods with that image: sh helm upgrade my-release . --set images.airflow.repository=my-company/airflow --set images.airflow.tag=8a0da78 Docker Images: The Airflow image that are referenced as the default values in this chart are generated from this repository: https://github.com/astronomer/ap-airflow. Other non-airflow images used in this chart are generated from this repository: https://github.com/astronomer/ap-vendor. Parameters: The complete list of parameters supported by the community chart can be found on the Parameteres Reference page, and can be set under the `airflow` key in this chart. The following tables lists the configurable parameters of the Astronomer chart and their default values. | Parameter | Description | Default | | :----------------------------- | :-------------------------------------------------------------------------------------------------------- | :---------------------------- | | `ingress.enabled` | Enable Kubernetes Ingress support | `false` | | `ingress.acme` | Add acme annotations to Ingress object | `false` | | `ingress.tlsSecretName` | Name of secret that contains a TLS secret | `~` | | `ingress.webserverAnnotations` | Annotations added to Webserver Ingress object | `{}` | | `ingress.flowerAnnotations` | Annotations added to Flower Ingress object | `{}` | | `ingress.baseDomain` | Base domain for VHOSTs | `~` | | `ingress.auth.enabled` | Enable auth with Astronomer Platform | `true` | | `extraObjects` | Extra K8s Objects to deploy (these are passed through `tpl`). More about Extra Objects. | `[]` | | `sccEnabled` | Enable security context constraints required for OpenShift | `false` | | `authSidecar.enabled` | Enable authSidecar | `false` | | `authSidecar.repository` | The image for the auth sidecar proxy | `nginxinc/nginx-unprivileged` | | `authSidecar.tag` | The image tag for the auth sidecar proxy | `stable` | | `authSidecar.pullPolicy` | The K8s pullPolicy for the the auth sidecar proxy image | `IfNotPresent` | | `authSidecar.port` | The port the auth sidecar exposes | `8084` | | `gitSyncRelay.enabled` | Enables git sync relay feature. | `False` | | `gitSyncRelay.repo.url` | Upstream URL to the git repo to clone. | `~` | | `gitSyncRelay.repo.branch` | Branch of the upstream git repo to checkout. | `main` | | `gitSyncRelay.repo.depth` | How many revisions to check out. Leave as default `1` except in dev where history is needed. | `1` | | `gitSyncRelay.repo.wait` | Seconds to wait before pulling from the upstream remote. | `60` | | `gitSyncRelay.repo.subPath` | Path to the dags directory within the git repository. | `~` | Specify each parameter using the `--set key=value[,key=value]` argument to `helm install`. For example, sh helm install --name my-release --set executor=CeleryExecutor --set enablePodLaunching=false . Walkthrough using kind: Install kind, and create a cluster We recommend testing with Kubernetes 1.25+, example: sh kind create cluster --image kindest/node:v1.25.11 Confirm it's up: sh kubectl cluster-info --context kind-kind Add Astronomer's Helm repo sh helm repo add astronomer https://helm.astronomer.io helm repo update Create namespace + install the chart sh kubectl create namespace airflow helm install airflow -n airflow astronomer/airflow It may take a few minutes. Confirm the pods are up: sh kubectl get pods --all-namespaces helm list -n airflow Run `kubectl port-forward svc/airflow-webserver 8080:8080 -n airflow` to port-forward the Airflow UI to http://localhost:8080/ to confirm Airflow is working. Login as _admin_ and password _admin_. Build a Docker image from your DAGs: 1. Start a project using astro-cli, which will generate a Dockerfile, and load your DAGs in. You can test locally before pushing to kind with `astro airflow start`. `sh mkdir my-airflow-project && cd my-airflow-project astro dev init` 2. Then build the image: `sh docker build -t my-dags:0.0.1 .` 3. Load the image into kind: `sh kind load docker-image my-dags:0.0.1` 4. Upgrade Helm deployment: sh helm upgrade airflow -n airflow --set images.airflow.repository=my-dags --set images.airflow.tag=0.0.1 astronomer/airflow Extra Objects: This chart can deploy extra Kubernetes objects (assuming the role used by Helm can manage them). For Astronomer Cloud and Enterprise, the role permissions can be found in the Commander role. yaml extraObjects: - apiVersion: batch/v1beta1 kind: CronJob metadata: name: "{{ .Release.Name }}-somejob" spec: schedule: "*/10 * * * *" concurrencyPolicy: Forbid jobTemplate: spec: template: spec: containers: - name: myjob image: ubuntu command: - echo args: - hello restartPolicy: OnFailure Contributing: Check out our contributing guide! License: Apache 2.0 with Commons Clause

AIGT is a repository containing scripts for deep learning in guided medical interventions, focusing on ultrasound imaging. It provides a complete workflow from formatting and annotations to real-time model deployment. Users can set up an Anaconda environment, run Slicer notebooks, acquire tracked ultrasound data, and process exported data for training. The repository includes tools for segmentation, image export, and annotation creation.

Spark NLP is a state-of-the-art Natural Language Processing library built on top of Apache Spark. It provides simple, performant, and accurate NLP annotations for machine learning pipelines that scale easily in a distributed environment. Spark NLP comes with 36000+ pretrained pipelines and models in more than 200+ languages. It offers tasks such as Tokenization, Word Segmentation, Part-of-Speech Tagging, Named Entity Recognition, Dependency Parsing, Spell Checking, Text Classification, Sentiment Analysis, Token Classification, Machine Translation, Summarization, Question Answering, Table Question Answering, Text Generation, Image Classification, Image to Text (captioning), Automatic Speech Recognition, Zero-Shot Learning, and many more NLP tasks. Spark NLP is the only open-source NLP library in production that offers state-of-the-art transformers such as BERT, CamemBERT, ALBERT, ELECTRA, XLNet, DistilBERT, RoBERTa, DeBERTa, XLM-RoBERTa, Longformer, ELMO, Universal Sentence Encoder, Llama-2, M2M100, BART, Instructor, E5, Google T5, MarianMT, OpenAI GPT2, Vision Transformers (ViT), OpenAI Whisper, and many more not only to Python and R, but also to JVM ecosystem (Java, Scala, and Kotlin) at scale by extending Apache Spark natively.

X-AnyLabeling is a robust annotation tool that seamlessly incorporates an AI inference engine alongside an array of sophisticated features. Tailored for practical applications, it is committed to delivering comprehensive, industrial-grade solutions for image data engineers. This tool excels in swiftly and automatically executing annotations across diverse and intricate tasks.

Construction-Hazard-Detection is an AI-driven tool focused on improving safety at construction sites by utilizing the YOLOv8 model for object detection. The system identifies potential hazards like overhead heavy loads and steel pipes, providing real-time analysis and warnings. Users can configure the system via a YAML file and run it using Docker. The primary dataset used for training is the Construction Site Safety Image Dataset enriched with additional annotations. The system logs are accessible within the Docker container for debugging, and notifications are sent through the LINE messaging API when hazards are detected.

MME-RealWorld is a benchmark designed to address real-world applications with practical relevance, featuring 13,366 high-resolution images and 29,429 annotations across 43 tasks. It aims to provide substantial recognition challenges and overcome common barriers in existing Multimodal Large Language Model benchmarks, such as small data scale, restricted data quality, and insufficient task difficulty. The dataset offers advantages in data scale, data quality, task difficulty, and real-world utility compared to existing benchmarks. It also includes a Chinese version with additional images and QA pairs focused on Chinese scenarios.

Aria is a Zotero plugin that serves as an AI Research Assistant powered by Large Language Models (LLMs). It offers features like drag-and-drop referencing, autocompletion for creators and tags, visual analysis using GPT-4 Vision, and saving chats as notes and annotations. Aria requires the OpenAI GPT-4 model family and provides a configurable interface through preferences. Users can install Aria by downloading the latest release from GitHub and activating it in Zotero. The tool allows users to interact with Zotero library through conversational AI and probabilistic models, with the ability to troubleshoot errors and provide feedback for improvement.

Deep Lake is a Database for AI powered by a storage format optimized for deep-learning applications. Deep Lake can be used for: 1. Storing data and vectors while building LLM applications 2. Managing datasets while training deep learning models Deep Lake simplifies the deployment of enterprise-grade LLM-based products by offering storage for all data types (embeddings, audio, text, videos, images, pdfs, annotations, etc.), querying and vector search, data streaming while training models at scale, data versioning and lineage, and integrations with popular tools such as LangChain, LlamaIndex, Weights & Biases, and many more. Deep Lake works with data of any size, it is serverless, and it enables you to store all of your data in your own cloud and in one place. Deep Lake is used by Intel, Bayer Radiology, Matterport, ZERO Systems, Red Cross, Yale, & Oxford.

Dify is an open-source LLM app development platform that combines AI workflow, RAG pipeline, agent capabilities, model management, observability features, and more. It allows users to quickly go from prototype to production. Key features include: 1. Workflow: Build and test powerful AI workflows on a visual canvas. 2. Comprehensive model support: Seamless integration with hundreds of proprietary / open-source LLMs from dozens of inference providers and self-hosted solutions. 3. Prompt IDE: Intuitive interface for crafting prompts, comparing model performance, and adding additional features. 4. RAG Pipeline: Extensive RAG capabilities that cover everything from document ingestion to retrieval. 5. Agent capabilities: Define agents based on LLM Function Calling or ReAct, and add pre-built or custom tools. 6. LLMOps: Monitor and analyze application logs and performance over time. 7. Backend-as-a-Service: All of Dify's offerings come with corresponding APIs for easy integration into your own business logic.

Video-MME is the first-ever comprehensive evaluation benchmark of Multi-modal Large Language Models (MLLMs) in Video Analysis. It assesses the capabilities of MLLMs in processing video data, covering a wide range of visual domains, temporal durations, and data modalities. The dataset comprises 900 videos with 256 hours and 2,700 human-annotated question-answer pairs. It distinguishes itself through features like duration variety, diversity in video types, breadth in data modalities, and quality in annotations.

Slideflow is a deep learning library for digital pathology, offering a user-friendly interface for model development. It is designed for medical researchers and AI enthusiasts, providing an accessible platform for developing state-of-the-art pathology models. Slideflow offers customizable training pipelines, robust slide processing and stain normalization toolkit, support for weakly-supervised or strongly-supervised labels, built-in foundation models, multiple-instance learning, self-supervised learning, generative adversarial networks, explainability tools, layer activation analysis tools, uncertainty quantification, interactive user interface for model deployment, and more. It supports both PyTorch and Tensorflow, with optional support for Libvips for slide reading. Slideflow can be installed via pip, Docker container, or from source, and includes non-commercial add-ons for additional tools and pretrained models. It allows users to create projects, extract tiles from slides, train models, and provides evaluation tools like heatmaps and mosaic maps.

Easily integrate Large Language Models into your Python code. Simply use the `@prompt` and `@chatprompt` decorators to create functions that return structured output from the LLM. Mix LLM queries and function calling with regular Python code to create complex logic.

Microchain is a function calling-based LLM agents tool with no bloat. It allows users to define LLM and templates, use various functions like Sum and Product, and create LLM agents for specific tasks. The tool provides a simple and efficient way to interact with OpenAI models and create conversational agents for various applications.

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.

Convoscope is a suite of smart glasses and web tools designed to augment conversations by providing live proactive agents that answer questions, offer definitions, insights, and alternative viewpoints. It includes features like 'Mira' AI Assistant, Convoscope Proactive AI Agents, Language Learning app, Screen Mirror functionality, and upcoming features such as Live Captions, ADHD Glasses, and Live Language Translation. The tool supports various smart glasses models and Android 12+ phones, offering a unique experience for real-life conversations, meetings, and video calls.

JoliGEN is an integrated framework for training custom generative AI image-to-image models. It implements GAN, Diffusion, and Consistency models for various image translation tasks, including domain and style adaptation with conservation of semantics. The tool is designed for real-world applications such as Controlled Image Generation, Augmented Reality, Dataset Smart Augmentation, and Synthetic to Real transforms. JoliGEN allows for fast and stable training with a REST API server for simplified deployment. It offers a wide range of options and parameters with detailed documentation available for models, dataset formats, and data augmentation.

LL3DA is a Large Language 3D Assistant that responds to both visual and textual interactions within complex 3D environments. It aims to help Large Multimodal Models (LMM) comprehend, reason, and plan in diverse 3D scenes by directly taking point cloud input and responding to textual instructions and visual prompts. LL3DA achieves remarkable results in 3D Dense Captioning and 3D Question Answering, surpassing various 3D vision-language models. The code is fully released, allowing users to train customized models and work with pre-trained weights. The tool supports training with different LLM backends and provides scripts for tuning and evaluating models on various tasks.

Kork is an experimental Langchain chain that helps build natural language APIs powered by LLMs. It allows assembling a natural language API from python functions, generating a prompt for correct program writing, executing programs safely, and controlling the kind of programs LLMs can generate. The language is limited to variable declarations, function invocations, and arithmetic operations, ensuring predictability and safety in production settings.

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With simple prompts, AIProductGPT instantly crafts detailed AI-powered requirements (PRD) and mocks so that you team can hit the ground running

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