At the Active Community, we are elated to announce the release of Encord Active 0.1.75, marking a significant milestone in our ongoing commitment to delivering unparalleled user experiences. This isn't just any update; we've made changes to redefine how you interact with our platform. Gone is Streamlit, paving the way for a more agile, quicker, and responsive UI.  As always, our primary objective is to ensure that you have the smoothest experience possible, and with this latest release, we've achieved just that. Discover the transformative features and improvements we've meticulously integrated into Encord Active 0.1.75! {{light_callout_start}} Encord Active provides a data-centric approach for improving model performance by helping you discover and correct erroneous labels through data exploration, model-assisted quality metrics, and one-click labeling integration. With Encord Active you can: Slice your visual data across metrics functions to identify data slices with low performance. Flag poor-performing slices and send them for review. Export your new data set and labels. Visually explore your data through interactive embeddings, precision/recall curves, and other advanced visualizations. Check out the project on GitHub, and hey, if you like it, leave us a 🌟🫡. {{light_callout_end}} Highlights of Major Features and Changes No more streamlit: New native UI At the heart of the Encord Active 0.1.75 release is the evolution of our user interface. While Streamlit served us well as the primary UI in our initial stages, we recognized its limitations, particularly for an open-source tool designed for scalability and production-level performance. From constraints like its numerous dependencies and limited potential for custom frontend components to a lack of Google  Colab integration, Streamlit posed challenges that hindered our vision. We took this as a cue to redesign and introduce a new native UI that's faster and offers a significantly smoother experience. By transitioning to a dedicated backend-frontend setup, we've eradicated previous complications and set the stage for a more performant Encord Active in future iterations. You'll now experience custom frontend components, seamless integration with Google Colab, a more responsive Explorer interface for delving deep into image datasets, enhanced usability, and swift loading times—a direct response to feedback from our community, who voiced concerns about sluggish interfaces with large datasets. By cutting ties with Streamlit and its inherent limitations, we have ushered in an era of increased speed and responsiveness—vital for effectively handling large computer vision datasets. With this release, Encord Active gets a completely new look and feel. We think that it is fresh enough to get a brand new command: encord-active start The start command has now replaced the previous visualize command. Prediction import We’ve streamlined the prediction imports via the SDK. They follow the same fundamental structure, and the documentation should be clearer. 10x improvement when tagging large datasets We have supercharged data tagging efficiency, achieving a remarkable 10x performance boost when tagging large amounts of data at once. Now, Encord Active can seamlessly handle large data batches simultaneously. This improvement improves your flow and makes data tagging lightning-fast. Deep Dive into Key Features Native UI While Streamlit was instrumental during our inception, its inherent challenges limited our scalability and adaptability. The all-new native UI in Encord Active 0.1.75 presents a clear, intuitive, responsive design built to serve our users' evolving needs. Direct Google Colab integration A significant advantage of moving away from Streamlit is the seamless integration with Google Colab. This feature paves the way for smoother workflows, especially for those using Google Colab for their data and ML tasks. No more `ngrok` or `nginx` integrations are required! We have put together a notebook for you to test this out. Run it directly from this notebook. Responsive Explorer interface and a button to hide annotations Exploring large image datasets? Our revamped Explorer is designed to ensure you navigate your datasets with unparalleled ease and speed. We have also added a button you can toggle under the Explorer tab to show or hide annotations in your images. Custom frontend components These allow for a more tailored user experience, giving you the tools and views you need without the fluff. Bug Fixes Video predictions Importing predictions for videos had a bug that assigned predictions to the wrong frames in videos (and image groups). This is now resolved. Classification predictions We have also addressed a crucial issue in our latest release concerning classification predictions. You can now trust that your classification predictions will be imported accurately and seamlessly. Optimized data migrations We have optimized data migration processes to be more efficient. We've addressed the issue where object embeddings, a compute-intensive task, were unnecessarily calculated in certain scenarios. With this release, expect more streamlined migrations and reduced computational overhead. Docker file release and include `liggeos` In our previous releases, the Docker file was wrong, so the Docker version did not get released. We've rectified this oversight. With this fix, this release is now fully Docker-ready for smoother installations and deployments. We have also included `liggeos` in the Docker image during build when trying to set up a project. That fixes issue #598.  Got rid of the ` encord-active-components` package In our commitment to streamlining and simplifying, we've made a pivotal change in this release. We've eliminated the separate `encord-active-components` package, opting instead to directly distribute the build bundled with its essential components. This move ensures a more integrated and efficient deployment for you. Explorer: signed URLs from AWS displayed "empty" cards We've rectified an issue where signed URLs from AWS displayed "empty" cards in the explorer. Expect consistent and accurate data representation for your AWS-stored content. On Our Radar Big video projects We've seen the import process crash when importing projects with many/long videos (more than an hour of video in total). The issue is typically a lack of disk space from inflating videos into separate frames. We suggest using smaller projects with shorter videos for now. With one of the following releases, video support will be much more reliable and eliminate the need for inflating videos into frames. Project subsetting Project subsetting is slow. We’re working to make this work much faster. We’ve also noticed complications when projects came from a local import (via the `init` command or `import --coco` command). We’re working on fixing this before the next release. Filtering the “Explorer” by tags If you have added a filter on the Explorer that includes Data or Label tags and then remove tags from some of the shown items, the Explorer won’t remove the items immediately. A page refresh will, however, show the correct results. What's No Longer Available? Most of the features in previous versions of Encord Active are still there. Below, we’ve listed the features that are no longer available. Export to CSV and COCO file formats Prediction confusion matrix We plan to bring back the confusion matrix, and if you’re missing the export features, please let us know in the Active community. Community Contributions This release wouldn't have been possible without the feedback and contributions from our community. We'd like to extend our heartfelt gratitude to everyone who played a part, especially those who highlighted the challenges with Streamlit and pushed for improved UI responsiveness. Your voices were instrumental in shaping this release.  {{light_callout_start}} Join our Active community for support, share your thoughts, and request features.{{light_callout_start}} Get the update now 🚀 pip install --upgrade encord-active See the releases (0.1.70 - 0.1.75) for more information Check the documentation for a quick start guide ⚠️ Remember to run `encord-active start` and not `encord-active visualize` in your project directory.

Improved Performance and Onboarding Focused on getting you up and running as quickly as possible, a simplified home page points out the essentials.  When navigating through annotation tasks, we are now loading image annotation tasks ahead of time to get one step closer to a native application experience. All the convenience of the cloud and the responsiveness of a desktop application showing that you can have your Encord cake and eat it too. A crucial early step, before you examine, annotate, or otherwise review your data, is connecting your cloud storage solution to Encord. Between multi-cloud, permissions and CORS it can be an arduous process. So — we’ve revamped the integration process into a guided step-by-step process in the app, and added the ability to confirm against storage resource URLs immediately after to give you complete and immediate feedback that your setup is in working order. Once you’ve onboarded your data integration, we’ve also made getting started with the SDK a one-step process. Simply generate your API key on the platform, and supply the file path of the downloaded private key when initiating your Encord SDK client. No copy-pasting and no fuss.  Require Annotations in Labeling Tasks Annotation tasks can be numerous and complex. In order to remove some of the burden of annotation and review, it can often be helpful to enforce that at least one of a particular annotation is present in a task. In addition to ongoing support for required specific nested attributes on objects and classifications, Encord has added support for ontology objects and classes to be required as well — enforcing that at least one of the indicated instance labels is present in a labeling task. We’ve paired this strict requirement enforcement with an improved issues drawer so annotators can quickly resolve outstanding issues and submit high quality annotation work.  Enhanced Workflow Collaboration with Collaborator Router and Simplified Queues We’ve simplified and separated the workflows task queue interface from the data inspection features. For team members — move through your annotate and review tasks with greater clarity. For admins, cleaner separation between data review and task control interfaces will keep you focused on the goal. We’re also adding a collaborator router so that you can route annotation tasks based on who made the most recent annotation submission or review judgement. Perfect for training newer annotation or review team members, or setting up partnerships and collaborations within wider projects and annotation workflows.  DICOM Updates Improvements in the label editor functionality are often especially relevant for DICOM annotation workloads. For example, the polygon tool’s new ability to show measurement vertex angles in the label editor with DICOM annotations can add value to your labelling workloads. Head over to the DICOM Update Blog to see the details, and other DICOM updates for this month. Around the web and around the world Encord is here to keep you up-to-date on the rapidly evolving world of AI. Check out these explainers for a deep-dive into the inner-workings of the latest in AI. Meta AI's CoTracker: It is Better to Track Together FastViT: Hybrid Vision Transformer with Structural Reparameterization Meta AI’s Photorealistic Unreal Graphics (PUG) Thanks for reading — as always, the inbox at product@encord.com is always open — we’d love to hear your thoughts on the feedback on the above! Talk to you soon,

We wrapped up July with some important advancements in workflows, model training, and DICOM. We’ve complemented these improvements with a new documentation system to make it easier to learn all the details of how the platform and the SDK work. Read on below to catch up with all the news! Track micro-model training data We wrapped up July with some important advancements in workflows, model training, and DICOM. We’ve complemented these improvements with a new documentation system to make it easier to learn all the details of how the platform and the SDK work. Read on below to catch up with all the news! After your automation-powered annotation workflows generate lots of labels — use enhanced sorts and filters in the export interface to get exactly the labels you want. We’ve added the ability to filter exports by dataset — a quick way to get what you need. Check out our docs on exporting labels from the web-app to learn more.  Route workflow tasks according to who took the latest action It’s often appropriate to change you QC in annotation workflows based on the workflow participant. It can help when training new staff, or creating good communication partnerships between label annotators and reviewers. To address these needs, we’re introducing the Collaborator Router which will you to route tasks through your annotation and QC workflows according to the last actor! A versatile workflows component -- contact us if you would like to discuss how collaborator routing can enhance your QC and annotation workflows!   Improved Documentation and Active Learning Notebooks Master the annotate, automate, debug active learning cycle with ease using our new documentation and notebook guides. This new centralized setup provides a clear and comprehensive overview of Encord's full range of capabilities. Coupled with an enhanced search and a vote-based feedback interface, you can quickly find precise nuggets of information easier than ever before and let us know what’s working and what isn’t. As part of the migration, the new documentation may have invalidated a couple previous bookmarks — simply search and re-book your go-to content to stay productive!  Once you’re oriented — jump into the details with end to end tutorials and active learning workflows prepared in our Encord Notebooks repository! Everything you need to get up and running with Encord Active and your active learning projects in one place! As always — reach out for any workflows or tutorials you feel will accelerate your active learning initiatives! DICOM Visual Enhancements: 3D Volumes and Zoom Per Window  When working with modalities that support multiple views, you can now zoom and pan them separately to fully understand the data at hand. Seamlessly navigate through high-resolution scans with ease, zooming in to scrutinize the finest details and panning across images effortlessly. Combined with the ability to render medical scans in 3D, the upgraded DICOM tool provides a seamless experience that empowers you to make more informed diagnoses and more precise annotations. {{light_callout_start}} Catch up on the full details of feature details in the DICOM update blog. {{light_callout_end}} Did you know?  You can use our Python SDK to view label logs —  providing comprehensive analytics on actions taken in the label editor — for example who created and edited certain annotations. Filters can be adjusted and combined to suit your all your needs - whether you’re interested in viewing logs for a particular time period, or want to see all actions taken on a data unit. Follow the steps in this recipe to get started, or consult the SDK’s API documentation, here! Around the web and around the world The world of AI moving fast, but Encord’s got your back. Check out these explainers for a deep-dive into the inner-workings of the latest in AI. Meta-Transformer: Framework for Multimodal Learning LLaMA 2: Meta AI’s Latest Open Source Large Language Model Text2Cinemagraph: Synthesizing Artistic Cinemagraphs Thanks for reading — as always, the inbox at product@encord.com is always open — we’d love to hear your thoughts on the feedback on the above!