The Explore tab is a useful project curation tool that allows you to view your data through more selective criteria than just file names. Import images, videos, documents, and annotations from your computer or cloud storages such as AWS, Google Cloud, Microsoft Azure, and more. In the case of text annotation, the use of computer vision is directed more towards tags, labels, and attributes rather than classes. Type your project details, add classes and attributes, and add contributors. Subscribe to receive new blog posts and latest discoveries in the industry from SuperAnnotate. SuperAnnotate for agriculture. With the arrival of large language models, AI is now learning to communicate. If interested, please send your CV to jobs@superannotate. With SuperAnnotate’s automation and active. Finding the right annotation workforce. D. In the context of machine learning, diffusion models generate new data by reversing a diffusion process, i. Access a global marketplace of 400+ vetted annotation service teams. SuperAnnotate is a platform that helps you create, manage, and improve your custom GenAI models and data labels with high-quality training data and annotation services. Image annotation is the process of selecting objects in images and labeling them by their names. 3. Video upload formats permitted in SuperAnnotate. Training this kind of large, complex models requires a robust data annotation workflow with quality management measures and smooth iteration cycles. 4%. Advanced tooling for higher-quality annotations: By leveraging SuperAnnotate’s feature-packed toolkit, OneCup managed. Research and educational materials, case studies, and product updates. Company history: With a mission to build and shape better technology, Keymakr started as a 10-people-company back in 2015. View the status of all your items and projects to track their progress. Compatibility issues That is why image classification techniques analyze a given image in the form of pixels and accomplish this by treating the picture as an array of matrices, the size of which is determined by the image resolution. . SuperAnnotate is the all-in-one AI data infrastructure platform that helps ML and data teams save time on building accurate AI models with the highest quality training data — SuperData. Given the team’s academic background, they have recently. In other words, pre-processing text data aims to format the text in a way the model can understand and learn from to mimic human understanding. With every release, we strive to bring new features to SuperAnnotate to help you create top-quality training data. There is a massive functionality gap between free and commercial image annotation tools. Image (Legacy) Editor. We may maintain pages for SuperAnnotate on social media platforms, such as Medium, Facebook, Twitter, and LinkedIn. This post will cover the top 7 considerations to help you scale your CV and annotation pipeline. By using unsupervised and semi-supervised learning algorithms. The pixels of the digital image are taken and grouped into what we know as “classes. 7. The platform provides a range of annotation services, including image annotation, text annotation, and. SuperAnnotate, San Mateo, California. Product. SuperAnnotate is the world's leading platform for building the highest quality training datasets for computer vision and NLP. Here are some examples: Population bias: When user demographics, statistics, and data, in general, differs in the platform you’re extracting data from (social media, for instance) vs. Understanding computer vision. So the YOLO algorithm and the zoo of its state-of-the-art modifications are a happy medium. It uses machine learning algorithms to identify whether the emotional tone of a text is positive, negative, or neutral. LLMs and GenAI. Image annotation can be understood as the process of labeling images to outline the target characteristics of your data on a human level. Training dataset accuracy increased by 2x. This article discusses SuperAnnotate’s features that speed up the quality assurance process substantially. Note that users with pending invitations are also counted as team members. By leveraging the power of transfer learning, data augmentation, and pre-trained networks, we can train new models that solve the task. Edge AI itself is not a physical, tangible entity. By using SuperAnnotate's Annotation service, our AI solutions team will cover that for you. With SuperAnnotate, I’ve been able to significantly speed up the annotation process,. SuperAnnotate allows you to annotate, version, and manage ground truth data for your AI. In its broader definition, it enables robots and other machines to see. Built with quality in mind. 5. The difference between image and video annotations is that video annotation is processed through frame-by-frame image data. Instructions. Only Team Owners and Team Admins can run model trainings. The tool is designed to recognize and extract text from images, and then. The fastest annotation platform and services for training AI. Please limit your item name to 120 characters. This is a. As a part of that effort, several smart pre-annotation algorithms were integrated into the platform, allowing our users to fix the auto-generated annotations, instead of starting from scratch. Estimated Market Value (USD) in 2022. Those predictions can go on to mitigate financial risk for a bank or credit union. Image panel redesign. Collaboration system. SuperAnnotate provides comprehensive annotation tooling, robust collaboration and quality management systems,no-code neural network training and automation, as well as a data review and curation system to successfully develop and scale CV projects. Dataloop. SuperAnnotate introduces a robust data annotation workflow with quality management measures and smooth iteration cycles to. Form Label. Train, iterate, improve, and deploy. Data labeling is a stage in machine learning that aims to identify objects in raw data (such as images, video, audio, or text) and tag them with labels that help the machine learning model make accurate predictions and estimations. LLMs and GenAI Editor. SuperAnnotate supports the following image file formats when you want to upload from the local storage: JPG, JPEG, PNG, WEBP, TIFF, BMP, and TIF. SuperAnnotate is the end-to-end image, video, and document annotation platform to annotate, train, and automate your AI pipeline. If you are interested in our Academic offer, please submit the form on this page. The comment feature involves all stakeholders in the quality review process of the annotations, making collaboration and task distribution more seamless than ever. Trend 1: Computer vision on the edge. TensorFlow. In this article, I would like to present our implementation of 2 active learning algorithms ( [1], [2]) and their usage in SuperAnnotate's platform, share the code and some benchmarking data. Quality management. Clients must support Transport Layer Security. 1,559 likes · 10 talking about this · 69 were here. Appen is a leading data annotation platform that offers auto-labeling features and a wide range of annotation tools. Learn how to import, export, manage, and use annotations,. The comment feature involves all stakeholders in the quality review process of the annotations, making collaboration and task distribution more seamless than ever. Fine-tune Initial Language Model using. Stay connected. Our robust data annotation workflow with quality management measures and. Image annotation can be understood as the process of labeling images to outline the target characteristics of your data on a human level. Simple features like scrolling and zooming, all the way to complex features like. Platform. Upload data to your project. SuperAnnotate is introducing an effortless priority-score sorting! Define priority scores in bulk to annotate high-priority items first. 4. Video or Audio Project - Export annotation format. Luckily, the term is straightforward and doesn’t leave much open to interpretation — face recognition is the task of detecting a face and identifying a person’s identity from an input visual in a digital system. SuperAnnotate is a tool to annotate, train, and automate your AI pipeline with image, video, and document data. SuperAnnotate is addressing those problems with the first of its kind end-to-end application development platform for computer vision. SuperAnnotate is designed to feed quality data into. JOB ANNOUNCEMENT - IMAGE ANNOTATOR Are you interested in working with a company that is at the cutting edge of machine learning to improve AI computer. 📣 Our latest webinar - "Super-Segment Anything," attracted a broad interest, so it will be presented for the OpenCV audience as well. create_project( project_name = "Project Name", project_description = "Project Description", project_type = "Vector") 📘Project typesImage Project: VectorImage (Legacy) Project: PixelVideo Project: VideoText Project: TextTo create a Video Project and set the. A user can be the owner and/or member of different organizations and non-organizational teams at the same time. October 2021. Superannotate provides a wide range of annotation features, including bounding boxes, segmentation, and point annotation. With advanced tooling and QA, ML and automation features, data curation, robust SDK, offline access, and integrated annotation services, we enable machine learning teams to build incredibly accurate datasets and successful ML. A quick overview of computer vision. To copy one or multiple images: Select one or multiple images. With SuperAnnotate, you can: high-quality annotations. Prodigy is a powerful data labeling tool designed for machine learning workflows. With advanced tooling and QA, ML and automation features, data curation, robust SDK, offline access, and integrated annotation services, we enable machine learning teams to build incredibly accurate datasets and. Trend 3: Data-centric computer vision. Learn how to integrate SuperAnnotate with your AI pipeline. The new round of funding will be used to expand SuperAnnotate’s engineering, sales and marketing teams. You can use advanced tools and automation features to label data across multiple data types, access vetted annotation teams, and automate complex ML processes with Python SDK. March 10, 2021 3 Trends to Watch in Computer Vision By Point Nine. Subscribe to receive new blog posts and latest discoveries in the industry from SuperAnnotate. A convolutional neural network consists of an input layer, an output layer, and several hidden layers. With advanced tooling and QA, ML and automation features, data curation, robust SDK, offline access, and integrated annotation services, we enable machine learning teams to build incredibly accurate. Automating OCR through SuperAnnotate. You can use advanced tools and automation features to label data across multiple data. 7+ and was tested under Linux and Windows ( Anaconda ) platforms. The linked items are displayed in SuperAnnotate, but they aren't stored on our local se. Machine learning empowers farmers of all sizes to achieve industry-critical goals quickly and accurately. Annotation toolsThe Image Editor has 8 annotation tools: Point, Polyline, Polygon, Bounding Box, Rotated Box, Ellipse, Cuboid, and Magic Box (for OCR). online) which is available for download on Windows, Linux, and Mac. The famous DALL-E 2, Midjourney, and open-source Stable. SuperAnnotate. Can I integrate my cloud storage with SuperAnnotate?Yes, you can create an integration with SuperAnnotate to add items from your cloud storage(s) to SuperAnnotate. Attach tiled imagery URLsYou can import tiled imagery by linking them from external storages. You can upload up to 2,000 images at a time. SuperAnnotate Description. SuperAnnotate’s announcing the power of default attributes across Vector, Video, and Text Projects. Manage, version, and debug your data and create more accurate datasets faster. 3 min. Add items with AWS integration. SuperAnnotate is a super-powerful application that offers pixel and vector editors, object prediction capabilities, automatic file distribution, and accurate file management. Annotation software. Automated machine learning (AutoML) is the new fast-growing technology that aims to make data science more productive and accessible for everyone. Join hundreds of leading companies who build super high-quality training data up to 5x faster using SuperAnnotate’s intuitive data curation and robust project management features. If it’s entity, then the instance is an annotation. Active learning algorithms help deep learning engineers select a subset of images from a large unlabeled pool of data in such a way that obtaining annotations of those images will result in a maximal increase of model accuracy. The platform enables robust and efficient collaboration between ML and Data teams to create, generate, version, debug, and manage ground truth data and build. The data labeling tools in question need to be reliable, efficient, require minimal human intervention, and generally provide features that you don’t currently acquire in-house. June 14, 2023. With world-class support. It is free software available in Windows, Mac and Linux OS. annotator_email: The assigned annotator’s email address. It specializes in high-volume and complex data and helps a wide range of deep-learning teams automate their data preparation processes. However, a robust team, project, data itself, and quality management system are crucial as well, especially when it comes to larger projects. February 11, 2021 SuperAnnotate Partners With OpenCV to Spread Visual ML By. 9 min/scan. Did this page help you? Why don't I see the name of the team that I've been invited to?After you click on the invitation link received via email, you’ll be. SuperAnnotate supports the SuperAnnotate annotation format and other common annotation formats (COCO, YOLO, and VOC). The comment feature involves all stakeholders in the quality review process of the annotations, making collaboration and task distribution more seamless than ever. Create a training model to automate your project and speed up the annotation process all while delivering quality results. Build robust CI/CD pipelines using SuperAnnotate’s toolkit of neural networks, Python SDK, webhooks, and advanced orchestration. Annotation services. Custom pricing is available as well as starter, pro and enterprise plans. In text annotation, sentence components, or structures are highlighted by. url: Item’s URL. This feature is available for. 02. Everything from parcel segmentation, crop detection, and plant/tree/flower counting. From teams to user management, from annotation to quality assurance, and from data training to sustainable scaling, we provide the best tools for an effective annotation automation process. Within SuperAnnotate there are 3 levels of Quality Assurance. 3 min. To download your project: Go to the Downloads tab. What’s new - September 2020. Neural network training Create a training model to automate your project and speed up the annotation process all while delivering quality results. This increases the security of your data and ensures safe remote access. Semantic/Instance Segmentation. AdSign in to your account Sign in with Google Sign in with SSO Or Email * Password * Forgot password?SuperAnnotate is a company that offers a fast and easy way to annotate, manage, and automate AI projects using computer vision. 6. Unfortunately, many annotation tools and platforms lack these features, and that’s why SuperAnnotate. SuperAnnotate supports the following video file formats that HTML5 supports: OGG, WEBM, and MP4. The package officially supports Python 3. Vahan Petrosyan. Superannotate is an end-to-end image and Video annotation platform that streamlines and automates computer vision workflows. The main idea here is to add random noise to data and then undo the process to get the original data distribution from the noisy data. Platform. With advanced tooling and QA, ML and automation features, data curation, robust SDK, offline access, and integrated annotation services, we enable machine learning teams to build incredibly accurate datasets and. When trying to scale annotation pipelines, teams face substantial challenges in creating, managing, and maintaining the constant inflow of high-quality training data within their computer vision pipelines. LiDAR (Light Detection and Ranging) is a remote sensing technology that uses lasers to measure distances and generate precise three-dimensional information about the shape and characteristics of its surrounding objects. 3 min. Two-factor authentication. Click Copy. SuperAnnotate offers a cloud-based solution, making it a flexible choice for businesses of all sizes. Pros. Level 1: instance-based. Lay a solid foundation for successful. , information loss due to noise intervention. It’s always easy to stay in touch with their team and. “Finding new annotation teams to work with is very easy through the SuperAnnotate platform and communicating back and forth with our annotations is super easy on the platform as well,” Gamliel stated. Spacept, like many other computer vision companies, was in need of high-quality outsourced annotators to work on their large-scale projects. 03. These events pertain to projects, exports, folders, or items. It contains 60 video clips and 21,646 corresponding ground truth maps with pixel-wise annotation of salient objects. MLOps has definitely been one of the biggest AI trends in 2022, with more companies and platforms leveraging it to increase the pace of model development and production. The accuracy of the data annotation services that they provide is a large indicator of the quality of the tools that are being used. Product updates: October 23, 2022. In this whitepaper, we concentrated on active learning algorithms, which help deep learning engineers select a subset of images from a large unlabeled pool of data in such a way, that obtaining annotations of those images will result in a maximal increase of model accuracy. 7+ and was tested under Linux. This proposes a situation where on one hand, national security can immensely improve as a result of this while on the other hand, governments may misuse this. Sign in with Google Sign in with SSO . Whether it will be convolutional neural networks or recurrent neural networks, the activation function decides how to proceed. Import images, videos,. Better AI unlocks a better world, yet there are countless companies and individuals running the same race as you to own the keys for that world. The fastest annotation platform and services for training AI. September 21, 2023. With his demonstrated experience in technology, startups, and management, Tigran brings his unique outlook to the current AI landscape. The famous DALL-E 2, Midjourney, and open-source. SuperAnnotate for insurance. 4 min. SuperAnnotate for healthcare. At SuperAnnotate, we provide a multitude of tools for the entire pipeline to obtain high-quality training data. csv", annotation_status = "QualityCheck") superannotatecli attach-image-urls --project “Project. SuperAnnotate is the leading platform for building, fine-tuning, iterating, and managing your AI models faster with the highest-quality training data. You can't upload more than 50,000 images, whether it's in a root folder or a folder. Form Label. The annotation files should have the following naming conventions: Project typeAnnotation file naming conventionImage (Legacy)<item_name>. 01. 12 min. Apply now to get your free credits. At SuperAnnotate, we have been dealing with this extensively, which led us to put our experience together and present 6 key considerations. 9 min. We had our own system, but we wanted it to accomplish additional tasks, like create new annotations types or annotate videos—activities that V7 helped us complete. SuperAnnotate. Built by CV researchers, SuperAnnotate aims to democratize the access of building, training, and deploying CV models for real-life applications. SuperAnnotate stood out from other vendors by offering a collaborative approach tailored to Prairie Robotics' specific needs, solving the biggest challenge it was facing at the time. At SuperAnnotate, we provide a multitude of tools for the entire pipeline to obtain high-quality training data. SuperAnnotate application expects the SAML assertions in a specific format, which requires you to add custom attribute mappings to your SAML token attributes configuration. The evolution of computer vision. June 14, 2022. The investment follows a four-month period during. SuperAnnotate requires read,. VOT2016 is a video dataset for visual object tracking. Object detection is a pivotal aspect of computer vision that involves identifying and locating specific objects within an image or video frame. “Also, since the annotators were. “The curation tool/Explore has improved a lot in just the last year, and it is awesome! The efficiency of the QA workflow and the ability to review data and take actions in bulk saves us a tremendous amount of time, speeding up. SuperAnnotate stands as a premium-quality ground-truth data provider across the field, where you can annotate, version, and manage data. Create projectTo create a project:Pythonsa. SuperAnnotate is already serving over 200 companies, including 20% of the Fortune 20 and over 10000 individual AI enthusiasts. SuperAnnotate was selected by AEDIT because it was the only end-to-end platform they were able to find, providing robust tooling, deep pipeline integration, and high-quality annotation services. Real-time object detection tasks require both algorithmic accuracy and performance time in frames per second as much as possible, and most of the time, it's a trade-off between these metrics. SuperAnnotate for sports Machine learning empowers coaches, referees, sport professionals and even sponsoring brands to achieve unparalleled control over the games and sporting events. Read writing from SuperAnnotate on Medium. Object detection and instance segmentation: COCO’s bounding boxes and per-instance segmentation extend through 80 categories providing enough flexibility to play with scene variations and. The history of YOLO: The origin of the YOLOv1 algorithm. ) platform, allowing our users to “fix” the auto-generated annotations,. 12 min. The evolution of YOLO: Object detection algorithms. It considers the analysis of a variety of data from audio to visual and then later utilizes that information to execute different processes. Web Server for Chrome, or your own web server of choice. Product. Co-founder and CEO at SuperAnnotate. Join our upcoming webinar “Deriving Business Value from LLMs and RAGs. Tigran Petrosyan, the co-founder and CEO of SuperAnnotate, invites leading industry and. To annotate datasets for computer vision models, it is made for computer vision teams, AI. Forecasted Market Value (USD. How SuperAnnotate helped Percepto cut the time to complete annotation projects by 60%. The image annotation market is estimated to be worth $1. The following screenshot shows the list of default attributes. Why SuperAnnotate? Have complete visibility and gain full control over your projects, pipeline, and data with an industry-leading annotation platform and an integrated service marketplace. News. What could b. Also, it's currently the largest context window among the commercially available models (surpassing Claude 2 with a 100,000 tokens context. You can cancel the preparation stage by clicking Cancel instead. The procedure can be broken down into two phases: explorative, when the algorithms explore patterns, and descriptive, when algorithms group and attribute the found patterns to the initial data. October 30, 2023. SuperAnnotate for security. Keras. 5 Million To Help Automate The Computer Vision Pipeline By Forbes. Choose an attribute (optional). Collaboration system. The company received 92 reviews with 4. Computer vision for drones also enables them to capture and identify obstacles in real-time and dodge any possible collisions. SuperAnnotate provides innovative solutions for a breadth of industries and use cases, from autonomous driving to robotics, and more. 03. ; Click Prepare Download. Only Team Owners and Team Admins can create and manage integrations. expert annotation teams to manage your annotation projects. With SuperAnnotate, customers create better performing models in less time all while streamlining their ML pipelines. Machine learning completely modernizes the security industry and provides tools to automate lengthy paperwork, minimize data leakage and even detect risky or fraudulent events. Also, we are very excited to introduce you to SuperAnnotate's new similarity search tool! Embeddings. Simply said, modern deep learning operates networks with multiple layers (and the more layers, the ‘deeper’ the network) where the output of one level is the input for the other. We promise to get back to you as soon as possible. Basic knowledge of HTML, CSS, JavaScript, and Chrome DevTools. This is done in the UI. Join our live product demo and engage with our team during the Q&A session. The. SuperAnnotate python SDK is available on PyPI: pip install superannotate. Unlike image classification tasks, assigning a singular label to an entire image, object detection algorithms discern multiple objects in an image and. SuperAnnotate allows you to create high-quality training datasets for various computer vision tasks, including object detection, instance, and semantic segmentation, keypoint annotation, cuboid annotation, and video. 6. SuperAnnotate AI provides super-fast (10-20x) and pixel accurate image annotation based on our AI-powered one-click object selection tech. Learn more Stay updated. Data labeling is a stage in machine learning that aims to identify objects in raw data (such as images, video, audio, or text) and tag them with labels that help the machine learning model make accurate predictions and estimations. SuperAnnotate’s advanced automation features helped AEDIT automate its data training processes. October 25, 2022. Our users prefer SDK integration as it minimizes manual processes, reduces workflow complexity, and helps complete tasks way faster than existing alternatives. Generate a dataset of your annotations. Learn more. SuperAnnotate also helped Percepto find and manage skilled outsourced annotation teams on the platform. Here, bounding box annotations help machines estimate the level of damage so that insurance companies. Chance of authoritarianism — By essentially automating facial recognition and detection, governments are able to monitor and track individuals’ movements among society. Learn how SuperAnnotate enhanced the Segment Anything Model's capabilities in an advanced environment on its all-in-one AI data infrastructure platform. Add a comment on an item to communicate mistakes and annotation requirements. Let us know whether you agree once you check it out. SuperAnnotate for insurance. At SuperAnnotate, we utilize our Vector Editor for OCR use cases: 1) First, we place bounding boxes for the named entity recognition. Installation. Lay a solid foundation for successful project execution by providing your team with detailed project instructions. Pillow (PIL Fork) TorchVision. Upload annotations to migrate your work from one project to another or from another platform to SuperAnnotate and continue where you left off. Trend 2: Computer vision as a service. Product. SuperAnnotate is designed to build and feed. 01. . If you are interested in requesting a demo, please submit the form on this page. To set a default attribute, choose an attribute from the drop-down list under Default attribute, then click Save. With advanced tooling and QA, ML and automation features, data curation, Orchestration, and integrated workforce marketplace, we enable machine learning teams to build and manage incrediblyDiseases like brain tumors, blood clotting, and a handful of neurological disorders are detected through CT scans and MRI, both of which function based off of well-trained ML models with considerable medical image data. 03. Computer vision is not only resourceful when it comes to analyzing existing data, but it goes forward another step to utilize diverse data, recognize patterns, and generate data-driven predictions. AUA kick-starts collaboration with SuperAnnotate. The package officially supports Python 3. SuperAnnotate. Subscribe for new updates. The annotations you upload should follow the SuperAnnotate annotation format, whose structure is based on JSON. Annotation workflow. Various alternatives pricing & plans. IntelinAir built an in-house tool and explored other. At SuperAnnotate, we provide a multitude of tools for the entire pipeline to obtain high-quality training data. 📘To move around an image. Select Upload Images. Potential market. SuperAnnotate can help Enterprise users install an on-prem infrastructure on their hardware to use their data stored in local storages. Everyone from researchers to startups to enterprises all over. Check full API Reference of SDK functions here. Approve/Disapprove items and instances. 9/5 score in the world's largest software marketplace. With advanced tooling and QA, ML and automation features, data curation, robust SDK, offline access, and integrated annotation services, we enable machine learning teams to build incredibly accurate datasets and. Orchestrate. . Why leading organizations choose SuperAnnotate. SuperAnnotate python SDK is available on PyPI: pip install superannotate. Product. We promise to get back to you as soon as possible. Check out what we've been working on!Magic PolygonThe Magic Polygon is a new tool in the Image Editor that automates the polygon annotation process. Models that perform object detection are trained with a surplus of annotated visuals in order to. In a world where data is the new oil, language is no longer just a human specialty. The first round of predictions using SuperAnnotate’s predictions model. Collaboration system. Leadership: Very talented, accessible and empathetic. VOT2016 is a video dataset for visual object tracking. The latter ones keep expanding, opening up room for wider applications of bounding boxes. With advanced tooling and QA, ML and automation features, data curation, robust SDK, offline access, and integrated annotation services, we enable machine learning teams to build incredibly accurate. a dataset of your annotations. Aerial imagery continuously reveals innovative opportunities for industries like construction, agriculture, and more. Learn more about browser compatibility. This is the start of our continuous. . The CB Insights research team evaluated over 6,000 companies from across the globe. Bounding box annotated images advance the object detection of visual perception models by spotting targets across multiple industries. Video or Audio Editor. 4 min. e. SuperAnnotate combined the two most important features they needed: a robust annotation platform and professional experts available on. You can cancel the preparation stage by clicking Cancel instead. Lay a solid foundation for successful. October 27, 2022. . The explanation will be based on the following example: The annotations JSON in a Image Project contains four main fields: metadata, instances, tags, and comments. Image Editor. Before an item is complete, it goes through several annotation stages. Product updates: Special edition! December 25, 2022. However, this kind of complex, sophisticated models require a robust data annotation workflow with quality management measures and smooth iteration cycles. Select New Step to add more steps. 4. On-prem data storage: Install an on-prem. With advanced annotation and QA tools, data. Increased operational efficiency, and automated workflow. Key results: Model accuracy increased from 80. Product updates, case studies, research articles, and more to help you keep up with the latest industry trends. 6 billion industry by 2022. The new Pipelines feature allows you to push real-time actions from SuperAnnotate to your application whenever a certain event occurs. annotations for predefined classes. View the status of all your items and projects to track their progress.