Roboflow provides a comprehensive platform for managing your computer vision datasets. When you upload your images or videos to Roboflow, they can be added to various project types including Object Detection, Single-Label Classification, Multi-Label Classification, Instance Segmentation, and Semantic Segmentation projects. However, the specific metadata information like the number of images, test/train/validate split or count, and the storage location of each set is not explicitly mentioned in the provided extracts.
Roboflow supports various image and video formats, and also various annotation formats for object detection, classification, and segmentation. You can upload your data using the Web User Interface, Roboflow’s API, or by forking/downloading a publicly available image dataset from Roboflow Universe.
As for how Roboflow stores uploaded and augmented images, the extracts mention that Roboflow can seamlessly integrate with cloud storage services like AWS S3, Azure Blob Storage, and Google Cloud Storage. It also mentions that Roboflow creates versioned, point-in-time snapshots of your project’s images and annotations, which you can use to run reproducible experiments. However, the specific details about the storage of augmented images are not provided in the extracts.
Please note that Roboflow strongly believes in data ownership. When you upload your images and videos, they remain yours. Roboflow does not own them.
For more detailed information, you may want to refer to the Roboflow Documentation or Roboflow Help Pages.
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