Best Image Annotation Tools for TensorFlow

Compare the Top Image Annotation Tools that integrate with TensorFlow as of June 2025

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This a list of Image Annotation tools that integrate with TensorFlow. Use the filters on the left to add additional filters for products that have integrations with TensorFlow. View the products that work with TensorFlow in the table below.

What are Image Annotation Tools for TensorFlow?

Image annotation tools are used to automatically process and label digital images using advanced techniques in machine learning, AI, and computer vision. These tools can accurately recognize important features in images, such as objects, characters, or facial expressions. This data can then be used for various purposes such as automatic image tagging and sorting. Image annotation is becoming an increasingly popular tool for organizing large databases of images and videos. Compare and read user reviews of the best Image Annotation tools for TensorFlow currently available using the table below. This list is updated regularly.

1

Vertex AI

Google

Image Annotation in Vertex AI is a powerful tool for preparing visual data for training computer vision models. By labeling and tagging objects, features, or regions of interest in images, businesses can create more accurate and specialized models for tasks like object detection and facial recognition. Vertex AI provides automated and manual annotation tools that can handle large volumes of image data, ensuring high-quality annotations for machine learning models. New customers receive $300 in free credits, enabling them to test the platform’s image annotation capabilities. With this feature, businesses can accelerate the development of visual AI solutions, increasing the accuracy and reliability of their models.

713 Ratings

Starting Price: Free ($300 in free credits)

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2

V7 Darwin

V7

V7 Darwin is a powerful AI-driven platform for labeling and training data that streamlines the process of annotating images, videos, and other data types. By using AI-assisted tools, V7 Darwin enables faster, more accurate labeling for a variety of use cases such as machine learning model training, object detection, and medical imaging. The platform supports multiple types of annotations, including keypoints, bounding boxes, and segmentation masks. It integrates with various workflows through APIs, SDKs, and custom integrations, making it an ideal solution for businesses seeking high-quality data for their AI projects.

Starting Price: $150

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3

Diffgram Data Labeling

Diffgram

Your AI Data Platform Quality Training Data for Enterprise Data Labeling Software for Machine Learning Free on your Kubernetes Cluster Up to 3 Users. TRUSTED BY 5,000 HAPPY USERS WORLDWIDE Images, Video, Text Spatial Tools Quadratic Curves, Cuboids, Segmentation, Box, Polygons, Lines, Keypoints, Classification Tags, and More Use the exact spatial tool you need. All tools are easy to use, fully editable, and powerful ways to represent your data. All tools are available in Video. Attribute Tools More Meaning. More degrees of freedom through: Radio buttons. Multiple select. Date pickers. Sliders. Conditional logic. Directional Vectors. And more! You can capture complex knowledge and encode it into your AI. Streaming Data Automation Up to 10x Faster then manual labeling

Starting Price: Free

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4

Label Studio

Label Studio

The most flexible data annotation tool. Quickly installable. Build custom UIs or use pre-built labeling templates. Configurable layouts and templates adapt to your dataset and workflow. Detect objects on images, boxes, polygons, circular, and key points supported. Partition the image into multiple segments. Use ML models to pre-label and optimize the process. Webhooks, Python SDK, and API allow you to authenticate, create projects, import tasks, manage model predictions, and more. Save time by using predictions to assist your labeling process with ML backend integration. Connect to cloud object storage and label data there directly with S3 and GCP. Prepare and manage your dataset in our Data Manager using advanced filters. Support multiple projects, use cases, and data types in one platform. Start typing in the config, and you can quickly preview the labeling interface. At the bottom of the page, you have live serialization updates of what Label Studio expects as an input.

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5

Segments.ai

Segments.ai

Segments.ai is an advanced data labeling platform that allows users to label data from multiple sensors simultaneously, improving the speed and accuracy of labeling for robotics and autonomous vehicle (AV) applications. It supports 2D and 3D labeling, including point cloud annotation, and enables users to label moving and stationary objects with ease. The platform leverages smart automation tools like batch mode and ML-powered object tracking, streamlining workflows and reducing manual labor. By fusing 2D image data with 3D point cloud data, Segments.ai offers a more efficient and consistent labeling process, ideal for high-volume, multi-sensor projects.

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