Labelme vs MakeSense.ai

Labelme is an AI-powered desktop annotation tool for creating image training datasets, aimed at researchers, engineers, and teams. Annotation options include polygons, rectangles, oriented rectangles, circles, lines, points, masks, and rich attributes. Local model support includes SAM, SAM2, SAM3, EfficientSAM, and YOLO-World. SAM3 accepts box and text prompts; SAM2 and EfficientSAM support point prompts, while YOLO-World returns bounding boxes. The maker says images, annotations, and exports stay on the user’s machine, without cloud processing or telemetry. Model weights are downloaded on first use; afterward, annotation and AI assistance can work offline, including in air-gapped setups using transferred models or the offline pack. Pro adds conversion and dataset tools, with exports including YOLO, YOLO-OBB, Pascal VOC, masks, visualizations, and statistics. The application is GPL-3.0, while the Pro toolkit is closed source. It runs on Apple Silicon macOS, 64-bit Windows, and 64-bit Linux; Intel Macs are supported only through v7.0.4. Starter costs $49, paid once, Pro $79, paid once, and Pro (Lifetime) $249, paid once.

MakeSense.ai is a browser-based tool for labeling photos and preparing datasets for computer vision projects. It supports point, line, rectangle, polygon, and label annotations, with model-assisted labeling through YOLOv5, SSD pretrained on COCO, and PoseNet. Users can load their own YOLOv5 models exported to TensorFlow.js format. Export options include CSV, YOLO, VOC XML, VGG JSON, and COCO JSON; imports include YOLO, VOC XML, and COCO JSON. The available format combinations vary by annotation type, and some are not yet supported. The project says images are not sent to a server and AI features run using TensorFlow.js. It works in a browser across operating systems, and documented local and Docker setups are available; Docker serves the application on localhost:3000. The project describes it as suitable for small computer vision deep-learning projects and dataset preparation. It was founded in 2019, is licensed under GPL-3.0, and credits Piotr Skalski as author and copyright holder. The Free plan costs nothing.