Detectron2 Framework

Detectron2 is a widely used object detection and instance segmentation framework leveraging deep learning, primarily employing Mask R-CNN architectures with various backbone configurations. Current research focuses on applying Detectron2 across diverse domains, including underwater object detection, defect identification in materials (e.g., synthetic fibers, magnesium alloy castings), and document layout analysis for various scripts (e.g., Bengali). This versatility highlights Detectron2's significance for automating visual inspection tasks in various industries and advancing research in computer vision, particularly in scenarios requiring precise object localization and segmentation.