Manage Data

alwaysAI’s Dataset Management is more than an annotation tool. Once your data is in the platform, you can search and filter it to review existing datasets and combine images and annotations from across datasets to make entirely new ones.

Dataset Workflow

The workflow we use to get from raw images to training dataset is:

  1. Raw images are uploaded

  2. Images are gathered into a collection

  3. Collection is “published” as ready-to-train dataset

In order to be trainable, your images need annotations. These can be done to the raw images from the gallery view or from within a collection. The Collection is the last step before training your data; it is where you can clean your data, add or update annotations, and analyze your dataset details, like class distribution. Once you publish your dataset for training, it is immutable, and that version will be captured and stored as an object in your dataset table.

Single Image View

If you click on a single image, you will open the Single Image View. This will open a large view of the selected image, and is where you can add or edit annotations, which you can find more information about Data Annotation Section. It is also where you find information about the image, including image metadata and tags associated with the image.

Details

You can see metadata for the image in the Details section. We have provided a few common fields, including Name, Type, Created, and Dimensions. Note that the Created field is the date that the image was upload to Dataset Management, not the date the picture was taken.

Tags

In the Tags section you can view tags that have been associated with this image. This is also where you will add new tags, or remove existing tags.