Search, sort, filter, clone & merge millions and millions of items using the data management system for ML and AI data. Filters include data type, class names, annotation types and much, much more.
Use Dataloop AI's Python SDK to cluster and classify millions of images In this video you can watch how volumes of data are clustered and then mass classified with our SDK. Add your own ML and redefine mass labeling…
If you have large amounts of data and need to improve your time to deliver labeled datasets, then this feature is for you: integrate your models (or use our built-in models) and watch as your data gets automatically labeled. It's that simple.
Building waste management AI apps? Sort, filter and categorize recyclable items using a suite of tools including semantic segmentation, polygons and more. One platform. More tools. Less work. Works with all industries.
Generate more accurate data for your vehicle inspection AI. Whether it's identifying scratches with pixel-level accurate semantic segmentation, detecting dents with polygons, or everything else under the hood.
Grab video snapshots of specific plays and begin labeling images. Make pixel-accurate annotations of player positions, movements and environment. Replay the scene directly from your image snapshot and gain context from the video scene.
Using Dataloop's function-as-a-service (FaaS) environment, build data pipelines. In this video, we trigger a face detection model to automatically detect, annotate, and crop faces.
Use Dataloop functions to augment data and get 100s of new images instantly. With this function, you can ensure your data is diverse enough to properly train your models.
Monitor sound sequences with audio classification to detect mechanical malfunctions. In this video, we demonstrate how you can help your AI models "listen" to automotive sounds in order to better detect and react to mechanical malfunctions using audio-based predictive analysis.
Stay tuned with the latest updates and features released