BlueEye Data is specialized in making annotations for images. Annotation for big-size images with a lot of details can be painful and time consuming. BlueEye Data guarantees to save a ton of your time on this matter. With both manual and AI-supported annotation tools, it is simpler than ever to label objects in images.

The current BlueEye version supports these annotation types:

• ​​Segmentation mask
• Bounding box
• Point
• Cuboid
• Polygon
• Lines & Splines

To start a data labelling for images project, simply follow these three steps:

Step 1: Click on Project that you are invited to see project info

Step 2: Go to Dataset page by clicking on Dataset menu

This page will display the projects that are assigned to you

Step 3: Go to Labeling tool and start labelling

There are 3 ways to Start Labeling

• Way 1: Click on Start Labeling button on Dataset page

If you are a Reviewer/ Project Manager/ Admin, you can see it as **Start Review** instead. In this case, the system will automatically open the first file on the first dataset on the Labeling tool.

• Way 2: Click on Start Labeling button on a specific dataset page

You can see the Start Labeling button after navigating to one of the datasets listed above.

If you are a Reviewer/ Project Manager/ Admin, you can see it as **Start Review** instead. In this case, the system will automatically open the first file on the first dataset on the Labeling tool.

• Way 3: Click on file name of the file that you want to label on a specific dataset page

In this case, the system will open exactly this selected file on the Labeling tool.

Image Labelling Tool Interface Overviews

This tool is used by Labelers and Reviewers, after starting a project and access labelling tool, this is the interface they will see

It can be broken down into 11 sections:

1. Home button: back to the Homepage where all projects are

2. Class list: show all classes needed to label in a project
   

Tap on the class field to show all classes created by Project Manager. When labeling, users will choose the class that needs to be labelled and then choose the corresponding tool.

3. Additional controls: guide link and hotkeys

4. Instruments pane: tools used to create annotation

BlueEye Data maximizes support for Labelers by only showing the supported tools needed for labeling in the Tool panel after users choose appropriate classes. This feature helps users avoid confusion while making annotations.

1. Move tool: Allow users to move the current image on the Editor to see the area that is needed to annotate.
2. Auto adjust iris tool: This tool helps users quickly annotate for Iris area for Facial Landmark project
3. Bounding box tool: Allow users to draw a bounding box around the object that is needed to annotate.
4. Landmark-point tool: Allow users to label for facial landmarks.
5. Polygon tool: Allow users to draw a polygon for the object that is needed to annotate.
6. Polyline tool: Allow users to draw lines for an object.
7. Cuboid tool: Allow users to draw a cuboid for an object.
8. Smart tool segmentation: Allow users to segment the object by modeling auto-generation.
9. Smart tool object tracking: Help users label the object automatically after one bounding box is created manually.
10. Text box tool: Allow users to make annotations for text and note that text.

Hover on each tool icon on the toolbar, you can view the name of the tools and hotkeys to choose it.

5. Source list: display all images on the current dataset by stat

Labeling tool only supports users working on separate datasets. So users can see all assigned sources which are on the current dataset and filter by each status.

Current image that is displayed on the main editor that focuses and borders on the list.

Users can track issues on each image with the flag icon attached on that. This symbol informs the number of open issues/total issues on that image. It helps users know and resolve issues quickly.

6. Action button: save and commit your work on the current image

7. Main screen: current image and annotation

This is the main working area of users. The purpose of this screen is:

• Display image as editor. Users can draw, zoom or move this section by using the corresponding tool.
• Display annotation after users have created

8. Image settings: adjust brightness and contrast of the current image

This section supports some settings that allow the user to adjust brightness, contrast or opacity of the current image. It helps to see the object and makes it easy to make the label.

9. Items list: list of annotations of the current image

This section displays all annotations that have been created from the Main screen and group by class name.

The selected instance will be synchronously highlighted on the Main screen as well.

10. Issue panel: list of issues created on the current media

Support interaction between Reviewers and Labelers when Reviewers assess Labelers’ annotation results. The system helps Reviewers easily create an issue and Labelers track issues on the current media.

11. Window control: hide and show windows on screen