RectLabel

RectLabel is an innovative open-source offline image annotation tool designed to facilitate and streamline object detection and segmentation tasks. This tool is tailored for users who require a versatile and efficient solution for various annotation needs, offering a comprehensive set of features to enhance the accuracy and speed of image annotation processes.

Main Features:

Diverse Annotation Tools: RectLabel provides a range of annotation tools including bounding boxes, polygons, cubic-bezier curves, lines, and points. This variety allows users to annotate images in a way that best suits their specific object detection and segmentation requirements.

Segment Anything Models: Users can label polygons and pixels using advanced Segment Anything models, enabling precise and detailed annotations.

Automatic Labeling with Core ML: The tool supports automatic labeling using Core ML models, which can significantly speed up the annotation process.

Text Recognition: Automatic text recognition for lines and words is available, making it easier to annotate images with textual elements.

Export Formats: RectLabel allows exporting annotations in various formats such as COCO, Labelme, CreateML, YOLO, DOTA, and CSV, ensuring compatibility with different machine learning frameworks and platforms.

Application Scenarios:

Aerial Image Analysis: In aerial image analysis, users can label oriented bounding boxes to identify objects from an overhead perspective, which is crucial in fields like urban planning and environmental monitoring.

Medical Imaging: For medical imaging, RectLabel’s ability to label keypoints with a skeleton and use brushes and superpixels for pixel labeling is invaluable, aiding in the identification and segmentation of anatomical structures.

Retail and Inventory Management: In retail, the tool can be used for automatic text recognition to annotate product labels and barcodes, aiding in inventory management and automated checkout systems.

Conclusion: 

RectLabel stands out as a comprehensive and user-friendly image annotation tool, ideal for professionals and researchers in fields requiring detailed object detection and segmentation. Its extensive feature set, combined with the flexibility of various export formats, makes it a valuable asset for a wide range of applications, from aerial imagery to medical imaging and retail. This tool not only enhances the efficiency of annotation tasks but also contributes to the advancement of machine learning models in diverse domains.