Struggling to choose between Computer Vision Annotation Tool (CVAT) and Supervisely? Both products offer unique advantages, making it a tough decision.
Computer Vision Annotation Tool (CVAT) is a Ai Tools & Services solution with tags like image-annotation, video-annotation, computer-vision, open-source.
It boasts features such as Image, video and 3D point cloud annotation, Multiple user management with different roles, Predefined tags and automatic annotation, Interpolation of bounding boxes across frames, Review and acceptance workflows, REST API, Integration with deep learning frameworks and pros including Open source and free, Active development and support community, Powerful annotation capabilities, Collaborative workflows, Integrates with popular ML/DL frameworks.
On the other hand, Supervisely is a Ai Tools & Services product tagged with nocode, annotation, neural-networks, computer-vision, machine-learning.
Its standout features include Image annotation, Video annotation, 3D annotation, Model training, Model deployment, Collaboration, Version control, Integrations, and it shines with pros like No-code platform, Streamlines computer vision workflows, Robust annotation capabilities, Built-in model training, Team collaboration features, Integrates with popular frameworks.
To help you make an informed decision, we've compiled a comprehensive comparison of these two products, delving into their features, pros, cons, pricing, and more. Get ready to explore the nuances that set them apart and determine which one is the perfect fit for your requirements.
CVAT is an open source computer vision annotation tool for labeling images and video. It allows for collaborative annotation of datasets with features like predefined tags, interpolation of bounding boxes across frames, and review/acceptance workflows.
Supervisely is a no-code platform for computer vision and machine learning. It allows users to annotate data, train neural networks, and deploy models without coding. Supervisely streamlines computer vision workflows.