Top 10 Image Labeling Tool With Advanced Features in 2023
With the rise of machine learning and artificial intelligence, image labeling has become a crucial aspect of many industries, from autonomous driving to e-commerce. But with so many image labeling tools out there, how do you choose the best one for your needs? Well, fear not!
In this blog, we'll be taking a deep dive into the top 10 image labeling tools of 2023, helping you make an informed decision and take your image labeling game to the next level.
So, let's get started!
Image labeling tool of 2023
Here is a list of the top 10 image labeling tools that you can use to label images for your model training:
1. Amazon SageMaker Ground Truth
Amazon SageMaker Ground Truth is an AI-powered platform that enables users to create high-quality training data for machine learning models. It offers a range of annotation tools, including image classification, object detection, and semantic segmentation.
2. CVAT
Computer Vision Annotation Tool (CVAT) is an open-source image annotation tool that offers a range of annotation types, including bounding boxes, polygons, and segmentation. It also supports collaborative annotation and quality control.
3. Labellerr
Labellerr is an AI-powered image annotation tool that uses a smart-feedback tool that helps AI-first organizations develop computer vision AI to bring automation to their data pipeline. It offers a range of annotation types, including bounding boxes, polygons, automated object detection, and automated semantic segmentation. It also has built-in quality control features to ensure accurate annotations.
One of the few annotation tool that got mentions in the IBM Research paper submitted at NeurIPS 2020 as published in Journal of Machine Learning Research. Download the report.
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4. Labelbox
Labelbox is an image annotation platform that offers a range of annotation tools, including bounding boxes, polygons, and semantic segmentation. It also has built-in quality control features to ensure accurate annotations.
Labelbox also provides features for collaboration and quality control, such as team management, annotation review, and consensus labeling. With Labelbox, teams can accelerate the development of their AI models and improve their accuracy and performance.
5. V7 Labs
V7 Labs is a software development company that focuses on creating cutting-edge solutions using artificial intelligence and machine learning. They specialize in developing computer vision and natural language processing technologies to solve complex problems in various industries, including healthcare, finance, and e-commerce.
6. VGG Image Annotator (VIA)
VGG Image Annotator (VIA) is an open-source image annotation tool developed by the Visual Geometry Group (VGG) at the University of Oxford. It provides an easy-to-use interface for annotating images with various types of annotations such as points, lines, polygons, rectangles, and more. VIA also supports the annotation of attributes, which allows users to add additional information to annotations.
VIA can be used for various applications such as object detection, image segmentation, and image classification. It supports importing and exporting annotations in various formats such as CSV, JSON, and PASCAL VOC. VIA can be run on a local machine or on a web server, and it can also be customized to support specific annotation tasks.
7. Dataturks
Dataturks is a cloud-based platform for image annotation and data labeling. It offers a range of annotation types, including bounding boxes, polygons, and semantic segmentation. It also has built-in quality control features to ensure accurate annotations.
Dataturks also provides integrations with popular machine learning frameworks such as TensorFlow, PyTorch, and Keras. Overall, Dataturks aims to make data annotation faster, easier, and more accurate, allowing ML teams to focus on building better models.
8. Hasty.ai
Hasty.ai is a platform for data labeling and annotation that uses AI to assist in the annotation process. It offers a range of annotation types, including bounding boxes, polygons, and semantic segmentation.
9. Roboflow
Roboflow is a cloud-based platform for data labeling and annotation. It offers a range of annotation types, including bounding boxes, polygons, and semantic segmentation. It also has built-in quality control features to ensure accurate annotations.
10. SuperAnnotate
SuperAnnotate is a web-based image annotation tool that offers a range of annotation types, including bounding boxes, polygons, and segmentation. It also supports collaborative annotation and quality control.
Conclusion
In conclusion, the world of image labeling has evolved significantly with the advent of machine learning and artificial intelligence. The use of accurate image labeling is crucial for various industries, including healthcare, e-commerce, and autonomous driving.
We have explored the top 10 image labeling tools of 2023, and they all offer unique features to address the growing demand for efficient and accurate image labeling.
Each tool has its own strengths, ranging from active learning to quality control features, making them suitable for various businesses of all sizes.
Overall, it's important to choose an image labeling tool that meets your specific needs and requirements. Consider the type of annotation tasks you need to complete, the level of accuracy required, and the scalability of the platform.
The top 10 image labeling tools we've explored offer a range of features to help you achieve high-quality annotations and streamline your operations. With the right tool, you can take your image labeling game to the next level and gain a competitive edge in your industry.