Segments.ai is described as 'The platform for computer vision experts to iterate more quickly between data labeling, model training and failure case discovery' and is an app. There are more than 25 alternatives to Segments.ai for a variety of platforms, including Web-based, SaaS, Self-Hosted, Windows and Linux apps. The best Segments.ai alternative is Oslovision, which is free. Other great apps like Segments.ai are UniversalDataTool, Amazon SageMaker Data Labeling, VGG Image Annotator (VIA) and Meta SAM 2.
Image annotation tool for modern computer vision. Easy to use, great for teams of all sizes. Hooks into training pipelines, designed around the latest State of the Art computer vision models.
Oslovision is the most popular Web-based & SaaS alternative to Segments.ai.
Oslovision is the most popular free alternative to Segments.ai.
The Universal Data Tool is a User Interface for editing and annotating Images (Computer Vision, Bounding Boxes, Segmentation), Text (Named Entity Recognition, Classification) or general purpose data entry. to view and edit any data defined in the extensible the .udt.
UniversalDataTool is the most popular Windows, Mac & Linux alternative to Segments.ai.
UniversalDataTool is the most popular Open Source alternative to Segments.ai.
Amazon SageMaker enables you to label raw data, such as images, text files, and videos, and generate labeled synthetic data to create high-quality datasets for training machine learning (ML) models. SageMaker offers two options, Amazon SageMaker Ground Truth Plus and Amazon...
VGG Image Annotator is a simple and standalone manual annotation software for image, audio and video. VIA runs in a web browser and does not require any installation or setup.
VGG Image Annotator (VIA) is the most popular Self-Hosted alternative to Segments.ai.
SAM 2 is the first unified model for segmenting objects across images and videos. You can use a click, box, or mask as the input to select an object on any image or frame of video.
Computer Vision Annotation Tool (CVAT) is a web-based tool which helps to annotate video and images for Computer Vision algorithms.
A family of foundation models producing universal features suitable for image-level visual tasks (image classification, instance retrieval, video understanding) as well as pixel-level visual tasks (depth estimation, semantic segmentation).
A desktop application with a UX built for through-put, HyperLabel is a complete toolset for quality labeling process management and training data creation.
doccano is an open source text annotation tool for humans. It provides annotation features for text classification, sequence labeling and sequence to sequence tasks.
Supervisely helps people with and without machine learning expertise to create state-of-the-art computer vision applications. We care about entire workflow from raw data to building and deploying neural networks for your special task without coding.
Appen's enterprise crowdsourcing solutions offer a cost-conscious, elastic workforce which gives companies immediate, high-quality work.
Appen is the most popular commercial alternative to Segments.ai.
A complete solution for your training data problem with fast labeling tools, human workforce, data management, a powerful API and automation features.
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