Labelo is an open-source labeling tool designed for annotating data, often used in machine learning and data science projects. It is one of the best annotation tools for labeling data. It helps to make machine learning tasks easy and efficient and provides custom labeling solutions as well. It is a scalable data annotation platform.

Purpose: Labelo, the best data annotation tool will help users label and annotate data for training machine learning models. This can encompass tasks such as object detection, image segmentation, and text classification.

Features

• User-Friendly Interface: Provides an intuitive interface for creating and managing labels.
• Customizable: Allows customization of labeling tasks according to project needs.
• Support for Various Data Types: Can handle different data formats such as images, videos, audio, and text.
• Export Options: Facilitates exporting labeled data in various formats compatible with machine learning frameworks.

Integration: This can be integrated with other tools and workflows commonly used in data science and machine learning.

Open Source: Being an open-source data labeling tool, it can be freely used and modified. This also means it has a community of contributors who help improve the tool.

Architecture

Frontend

• UI Framework: The user interface of Labelo is built using a modern JavaScript framework React.
• Components:
  • Annotation Tool: A key component for drawing and labeling.
  • Review Tool: A feature for reviewing labeled tasks.
  • Dashboard: For managing projects, viewing datasets, and tracking progress.
  • User Management: For handling user accounts and permissions.
  • Organization Management: For creating and managing different organizations.

Backend

• Web Server: Typically implemented using a framework like Django.
• API: RESTful API endpoints to handle requests from the frontend.
• Database: A relational PostgreSQL and SQLite database for storing metadata, user data, and project configurations.

Labelo Projects Page

Labelo is the best data annotation platform. Labelo’s project management page offers a comprehensive interface for managing multiple projects and organizing your workspace efficiently.

Create New Projects: Easily create new projects by clicking on the “Create Project” button. You can define the project’s name, description, and specific settings during creation.

Project Actions: For each project, you can perform actions like editing project details, deleting the project, or archiving completed projects.

Create and Manage Workspaces: Create new workspaces and move projects between them as needed. You can edit, delete, or archive each workspace. This is useful for organizing projects by client, team, or type of task.

Search Bar: A search bar at the top of the project page enables you to quickly find specific projects by name or keyword.

Filters: Use filters to narrow down your project list based on various criteria such as project status (active, archived), creation date, or assigned team members.

Views: Projects are displayed in grid format, showing project cards with thumbnails as well as in list view to see projects in a more detailed, tabular format. 

Below is a detailed view of the project.

Below shown is the list view of the project page. From the list view, we have the option to bulk delete the projects. For that, you can choose the projects that are to be deleted and simply click on the delete button. 

Labelo Tasks Page

The task page in Labelo is designed to provide a detailed view and management capabilities for the tasks within a project. 

Import and Export: Easily add new data to your project by using the import feature. Once tasks are annotated, you can export the labeled data in the desired format (e.g., COCO, JSON, CSV, etc.).

Actions: Can perform multiple actions on tasks such as Assigning annotators and reviewers, Deleting annotations and predictions,s, etc.

Task Filters: Use filters to narrow down the list of tasks. You can filter tasks based on different parameters.

Views: Tasks are displayed in a grid format, showing thumbnails or previews of each task. Switch to a list view to see tasks in a more detailed, tabular format.

The image of the task page in grid view is given below.

Labelo Labeling Interface

The labeling interface in Labelo is designed to provide a comprehensive and user-friendly environment for annotating images and other data types.

Choose the labels: Annotators can choose from a predefined set of labels. These labels are usually set up during the project configuration and can represent different objects or classes.

Labeling the dataset: The dataset imported can be labeled using different predefined labels according to your preferences from the interface.

Add Comments: Annotators can add comments to specific annotations or the entire image. This feature is useful for providing additional context, asking questions, or making notes about particular parts of the image.

Viewing Annotation History: Access the history panel to see a chronological list of changes. Click on any entry to view details or revert to that version.

Workflow

To start and complete a labeling project with Labelo, follow these steps:

1. Install Labelo: Set up the tool on your machine or server.
2. Create a New Project: Open Labelo and create a new project for your labeling task.
3. Import Data: Upload your dataset (images, text, video, audio, etc.) into the project.
4. Configure Labeling Interface: Customize the labeling interface based on your specific requirements.
5. Label Your Data: Use the provided tools to annotate your data.
6. Review Annotations: Review the labeled data for accuracy and consistency.
7. Export Labeled Data: Once labeling is complete, export the annotated dataset in the desired format.

Labelo stands out as a versatile and efficient annotation tool, designed to meet the diverse needs of data labeling projects. Whether you’re working on an image, text, or video annotation, Labelo simplifies the process with its intuitive interface, robust features, and seamless integration capabilities. By streamlining the annotation workflow, Labelo not only enhances productivity but also ensures high-quality data outputs.