Save Time & Cost On Data Labeling With Auto-Label Feature

Imagine you're building an AI model to recognize different types of flowers in photos. Traditionally, labeling each flower by hand would take hours and would require a dedicated team.

With Auto-Label, team can easily achieve initial annotations, significantly reducing the time and cost associated with manual labeling tasks.

This innovative feature empowers users to effortlessly generate initial annotations, ensuring a rapid and efficient labeling process.

By automating this crucial task, Labellerr's Auto-Label feature not only saves valuable time but also reduces operational costs, enabling companies to allocate resources more effectively.

Here's where Labellerr's Auto-Label comes in:

Auto-labeling is the process where AI predicts the label by itself. Reducing or replacing the human in the loop from the labeling process. Model-assisted labeling and active learning-based labeling are a few examples.

With Auto-Label, simply upload your photos and let the AI do the initial work. It analyzes the images and will automatically do the work.

You can then quickly review and refine these suggestions, significantly reducing the time and effort needed for accurate labeling.

Why is Auto-Label needed?

Companies often face the challenge of manually annotating large volumes of data, which can be time-consuming and resource-intensive.

Labellerr's new Auto-Label feature addresses this need by automating the data annotation process, allowing users to annotate images swiftly and accurately without the need for dedicated operational teams.

Manual data labeling can be a significant bottleneck in many industries, from computer vision research to machine learning model training.

Labellerr's Auto-Label feature streamlines this process, enabling companies to generate annotations quickly and effortlessly.

By reducing the need for manual annotation, users can save valuable time and resources, enabling them to focus on higher-value tasks such as model refinement and analysis.

Labellerr Auto-Label: Powerful Features

Zero-shot labeling: Generate labels for unlabeled images without any prior training data.

Foundation model powered: Leverage advanced AI models for accurate and efficient labeling.

No manual labeling: Simply define the object/class and let the AI handle the rest. Batch processing: label thousands of images in minutes with a single click.

Easy review and validation: Filter by confidence score and quickly refine the results.

Faster training: Get your AI models trained and deployed quicker with readily labeled data.

How to Use AutoLabel in Labellerr

1. Create a free Labellerr account and set up a new project in your workspace.

2. Click on the image data type, then click save and next. Upload the receipt images, and then click on Create dataset.

3. Now we will configure our labels by adding objects to them. We will be creating three objects Paper, Receipt Bounding Box, Receipt Polygon.

4. Make sure to select Enable autolabel and LabelGPT in the misc.properties for all the objects. Finally, click on save and next in the current project guidelines.

5. Now in the dashboard, click on Start Labeling to start labelling the images. Now click on Use Autolabel to automatically label images.

For a more hands-on tutorial, you can watch the following video on YouTube:

Conclusion

In summary, Labellerr's Auto-Label feature revolutionizes the data annotation process, offering unparalleled speed, accuracy, and cost efficiency.

Whether you're a startup looking to streamline your workflow or an enterprise seeking to scale your annotation efforts, Labellerr is your trusted partner in data labeling.

Try it today and experience the future of automated annotation!

Frequently Asked Questions

Q1) What is Labellerr?

Labellerr is a data annotation tool designed to streamline the process of labeling data for machine learning and AI projects. It offers automated labeling features to help users annotate images quickly and accurately.

Q2) What is Labellerr's Auto Label feature?

Auto Label feature is a powerful tool that automatically annotates images, saving time and resources for users who need to label large volumes of data for machine learning projects.

Q3) What are the benefits of using Labellerr's Auto Label feature?

By automating the data annotation process,  Auto Label feature saves users valuable time and resources. It eliminates the need for manual labeling, enabling ML teams to generate thousands of labels in just minutes.