Manual image annotation is the process of manually defining regions in an image and creating a textual description of those regions. Such annotations can for instance be used to train machine learning algorithms for computer vision applications.
This is a list of computer software which can be used for manual annotation of images.
Computer Vision Annotation Tool (CVAT) is a free, open source, web-based annotation tool which helps to label video and images for computer vision algorithms. CVAT has many powerful features: interpolation of bounding boxes between key frames, automatic annotation using TensorFlow OD API and deep learning models in Intel OpenVINO IR format, shortcuts for most of critical actions, dashboard with a list of annotation tasks, LDAP and basic authorizations, etc. It was created for and used by a professional data annotation team. UX and UI were optimized especially for computer vision annotation tasks.
Encord is an automated annotation platform for AI-assisted image annotation, video annotation, and dataset management.
Data Management: Compile your raw data into curated datasets, organize datasets into folders, and send datasets for labeling.
AI-assisted Labeling: Automate 97% of your annotations with 99% accuracy using auto-annotation features powered by Meta's Segment Anything Model or GPT-4's LLaVA.
Collaboration: Integrate human-in-the-loop seamlessly with customized Workflows - create workflows with the no-code drag and drop builder to fit your data ops & ML pipelines.
Quality Assurance: Robust annotator management & QA workflows to track annotator performance and increase label quality.
Integrated Data Labeling Services for all Industries: outsource your labeling tasks to an expert workforce of vetted, trained and specialized annotators to help you scale.
Video Labeling Tool: provides the same support for video annotation. One of the leading video annotation tools with positive customer reviews, providing automated video annotations without frame rate errors. Robust Security Functionality: label audit trails, encryption, FDA, CE Compliance, and HIPAA compliance.
Integrations: Advanced Python SDK and API access (+ easy export into JSON and COCO formats).
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^Costa, Bryan; Sweeney, Edward; Mendez, Arnold (October 2022). "Leveraging Artificial Intelligence to Annotate Marine Benthic Species and Habitats". Noaa Technical Memorandum Nos Nccos. 306. doi:10.25923/7kgv-ba52.