VGG Image Annotator vs YoloLabel

VGG Image Annotator (VIA) is a suite of lightweight browser tools for manually annotating images, audio, and video. The applications are distributed as single HTML files, allowing offline use without installation or setup. VIA3 handles images, video, audio, and shared or collaborative projects. VIA2 works with image files, does not support shared projects, and remains maintained. Annotation shapes include rectangles, circles, ellipses, points, polygons, and polylines. Projects can import or export annotations as CSV or JSON, while scripts support COCO and Web Annotation formats; a Python package converts VIA projects to COCO. Shared work can use a free public Version File Store maintained by the Visual Geometry Group, or a user-run VFS. VIA is built with HTML, CSS, and JavaScript without external libraries and released under the two-clause BSD license for academic and commercial use. Downloads include ZIP archives and standalone HTML files for versions 2 and 3. The makers provide a guide, FAQ, and email contacts.

YoloLabel is a free GUI for drawing object bounding boxes on images used to train YOLO neural networks. It loads JPG or PNG files from a directory and creates boxes with a two-click method. Labels can be moved, resized, copied, pasted, undone, and redone, then exported as YOLO TXT. The desktop app has downloads for Windows x64, Linux x64, and macOS on Apple Silicon, and its repository uses the MIT License. Local assisted labeling runs Ultralytics models exported to ONNX, including YOLOv5, YOLOv8, YOLO11, YOLO12, and YOLOv26, with single-image or dataset batch processing. YoloLabel AI adds cloud open-vocabulary detection through an API key and optional prompt; requests handle up to 20 images. Building from source uses Qt 6, while ONNX Runtime is optional unless local auto-labeling is required.