Requirements

Business requirements

  • The tool generates annotations, based on already marked elements, for the remaining elements of the set.

  • The tool has the ability to mark data and generate predictions if there are no base annotations, only a clean set.

  • The system should allow configuring model training parameters and selecting architectures to provide flexibility for different project needs.

Usage requirements

  • Possibility of continuing work with existing data sets.

  • Speeding up data annotation 10 times compared to humans.

System requirements

Functional:

  • The user can add projects by clicking a button, after clicking it, the project is entered into the database and the log is sent.

  • The user can add link to cloud storage where the data is stored.

  • The user can visually select data in the form of bounding boxes.

  • The user can assign a class to the selection.

  • The user can choose from pretrained/basic ML models.

  • The user can specify model hyperparameters by filling the form.

  • The user can see the results of the model in the form of numerical values and charts in the dashboard.

  • The user can download the generated annotations by pressing the appropriate button.

Non-functional:

  • It is possible to serve at least 2 clients.

  • It is possible to work with large datasets (more than 10000 images).

  • It is possible to store annotations in JSON format.