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.
In this video we'll demonstrate how to annotate objects with bounding boxes and convert them to polygon in seconds. Our cloud-based labeling platform includes embedded tools and automations to help you produce high-quality datasets more efficiently.
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, and 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.
Select the object you wish to track, provide it with an annotation label, turn on the video tracker and let the magic happen as it predicts future frames and automatically labels them for you.
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