Every labeling and data exploration journey starts with creating a new project. The project consists of a dataset, the UI to label and explore it, a machine learning model to assist you with labeling, and possibly several external collaborators or your team’s members.
Starting a new labeling project in Heartex is as easy as pressing the “Create from scratch” or “Use template” button projects dashboard page. Administrators and Data Science users can start new projects.
The first step in creating your project is to provide a project name. The name will be the internal reference for the project which users will see on their pages. Below, we fill out the name and description for the classifier project:
Each project has it’s own UI for the labeling. The configuration is based on HTML-like tags, which internally are mapped into the associated React classes. You can check out editor page or tags reference to get a better understanding of what’s supported. For popular scenarios, there are pre-configured templates available here
You can modify the config after the project is created, but only if there are no completions created.
The project dashboard serves as the central page for a Heartex user. Each project has its dashboard page, which is created when you start a new project. The page provides an overview of significant project statistics. Depending on permission, different user roles get different parts of the dashboard shown to them. For example, Lead Annotators will only see the Data Manager.
Each project can be extensively configured and tailored for your particular labeling scenario.
Configure instruction. It should describe what an expert should do in each task. There is support for reach text and auto-saving
Number of completions of the task before it’s considered as Done
Inside the “More” panel, you can delete the entire project, only completions or only the tasks. You can also duplicate a project.
For your convenience, you can create a new project from predefined templates.