Upload dataOpen DataHub

Upload data

Use project upload for data you want to annotate or include in a dataset. Use the artifact library for files that should remain files, such as weights or reference material.

Upload images or video

  1. Open your project and its Upload Data section.
  2. Choose files or drop them into the upload area.
  3. Review the recognized media and available import options.
  4. Start the upload and wait for its reported completion.
  5. Open the project data to check image orientation, labels, and metadata.

Image and video workflows share the upload entry point. Video processing can produce project frames; it is not the same operation as uploading unrelated still images. Use the controls shown for the recognized media.

Do not close the page merely because file transfer has finished if the interface still reports processing. A failed or interrupted upload should be inspected before starting a duplicate batch.

Check your first batch

Open a few examples after upload. Confirm the orientation and dimensions, look for unexpected duplicates, and check that any imported labels sit on the correct objects. A quick check now is easier than discovering an import mismatch after labeling hundreds of images.

For a video, review frames across the selected range rather than only its first frame. Choose a frame selection appropriate to the change in the scene; many near-identical frames can make a dataset larger without adding much useful variation.

Import existing labels

The SDK importer supports common dataset layouts, including YOLO, COCO, Pascal VOC, LabelMe, classification folders, and several CSV formats. Format support is specific: matching a filename extension does not establish that every annotation type in the file is supported.

After importing a labeled dataset, inspect several images with different shapes and classes. Check normalized geometry, image dimensions, split names, and class names before training or exporting.

Upload a file without adding dataset images

Open the project's files section or the account artifact library and choose its upload action. Uploading an image as an artifact does not automatically add it to the annotation dataset.

TIFF and medical-source actions are separate import workflows when available. Inspect their options and permissions before promoting a file into project data.

Work with large TIFF and GeoTIFF images

Large rasters can be viewed through a tiled image layer, so you can move around a detailed image without treating it as a normal small photograph. The original TIFF remains the scientific source; the displayed view is for navigation and annotation.

  1. Upload the TIFF through the supported upload workflow, or upload it in Files & models and choose Import as raster when offered.
  2. Review the image and its display settings in the annotator.
  3. Annotate the areas of interest on the source image.
  4. When creating training data, choose explicit raster chip settings: chip size, overlap, regions, and display bands or ranges as needed.
  5. Preview the chips and then build the version.

Training chips are RGB PNG images derived from the selected source regions. The original raster is retained. Annotation currently applies to the first TIFF page; other pages remain in the original file.

View and annotate supported DICOM frames

  1. Upload the DICOM as a project artifact in Files & models.
  2. Choose DICOM to open the viewer. Navigate frames and adjust window center, width, and function to inspect the image.
  3. To annotate it, use the available medical import action and select the frame range.
  4. Open the resulting project frames in the annotator and label them as you would other project images.

The source file is retained once, while selected frames become project annotation records. The medical source controls let you review the source and add frames later. Windowed previews do not modify the stored medical pixels.

Medical-image scope

The current viewer supports a defined subset of monochrome DICOM layouts. Unsupported compressed or color layouts return a message. This is a frame annotation workflow, not a complete clinical study-management system. Removing patient tags from displayed technical metadata does not de-identify the original file or text burned into its pixels.

Resolve a failure

Next: Annotations.