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.
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.
Auto-annotate images by integrating an existing model. Steps include importing your Dataloop SDK package, selecting the project, dataset and images you're working on, running the model which will result in annotation predictions. Once you're set you can push the annotations and view the changes directly in your Dataloop platform.
Stay tuned with the latest updates and features released