Best Video Annotation Tools in Europe

Video Annotation in Vertex AI enables businesses to label and tag objects, actions, and features in video data, which is crucial for training computer vision models that can analyze and interpret dynamic visual content. Vertex AI offers automated and manual annotation tools that support a wide range of video processing tasks, from object detection to activity recognition. By annotating videos, businesses can train more accurate and effective machine learning models for video analytics. New customers receive $300 in free credits to experiment with video annotation tools and apply them to their own datasets. This capability enables businesses to leverage video data for powerful AI applications in industries such as security, entertainment, and sports analysis.

Clarifai is a leading AI platform for modeling image, video, text and audio data at scale. Our platform combines computer vision, natural language processing and audio recognition as building blocks for developing better, faster and stronger AI. We help our customers create innovative solutions for visual search, content moderation, aerial surveillance, visual inspection, intelligent document analysis, and more. The platform comes with the broadest repository of pre-trained, out-of-the-box AI models built with millions of inputs and context. Our models give you a head start; extending your own custom AI models. Clarifai Community builds upon this and offers 1000s of pre-trained models and workflows from Clarifai and other leading AI builders. Users can build and share models with other community members. Founded in 2013 by Matt Zeiler, Ph.D., Clarifai has been recognized by leading analysts, IDC, Forrester and Gartner, as a leading computer vision AI platform. Visit clarifai.com

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.

Amazon Rekognition makes it easy to add image and video analysis to your applications using proven, highly scalable, deep learning technology that requires no machine learning expertise to use. With Amazon Rekognition, you can identify objects, people, text, scenes, and activities in images and videos, as well as detect any inappropriate content. Amazon Rekognition also provides highly accurate facial analysis and facial search capabilities that you can use to detect, analyze, and compare faces for a wide variety of user verification, people counting, and public safety use cases. With Amazon Rekognition Custom Labels, you can identify the objects and scenes in images that are specific to your business needs. For example, you can build a model to classify specific machine parts on your assembly line or to detect unhealthy plants. Amazon Rekognition Custom Labels takes care of the heavy lifting of model development for you, so no machine learning experience is required.

Manage unstructured data and pipelines to develop AI solutions at amazing speed. Enterprise-grade data platform for vision AI. Dataloop is a one-stop shop for building and deploying powerful computer vision pipelines data labeling, automating data ops, customizing production pipelines and weaving the human-in-the-loop for data validation. Our vision is to make machine learning-based systems accessible, affordable and scalable for all. Explore and analyze vast quantities of unstructured data from diverse sources. Rely on automated preprocessing and embeddings to identify similarities and find the data you need. Curate, version, clean, and route your data to wherever it’s needed to create exceptional AI applications.

With Automaton AI’s ADVIT, create, manage and develop high-quality training data and DNN models all in one place. Optimize the data automatically and prepare it for each phase of the computer vision pipeline. Automate the data labeling processes and streamline data pipelines in-house. Manage the structured and unstructured video/image/text datasets in runtime and perform automatic functions that refine your data in preparation for each step of the deep learning pipeline. Upon accurate data labeling and QA, you can train your own model. DNN training needs hyperparameter tuning like batch size, learning, rate, etc. Optimize and transfer learning on trained models to increase accuracy. Post-training, take the model to production. ADVIT also does model versioning. Model development and accuracy parameters can be tracked in run-time. Increase the model accuracy with a pre-trained DNN model for auto-labeling.