facebookresearch/detectron

Detectron is Facebook AI Research's original platform for computer vision research, specifically for object detection, which is the AI task of identifying and locating objects within images and video. Think of it as the research workbench where Facebook's scientists developed and tested algorithms that could look at a photo and draw boxes around every person, car, dog, or other object in it. The most famous algorithm that came out of this platform is Mask R-CNN, which won a top prize at a major computer vision conference in 2017. Unlike earlier systems that only drew bounding boxes around objects, Mask R-CNN could also draw precise outlines around each object, distinguishing the exact pixels belonging to a person versus the background behind them. This technique is called instance segmentation and is now foundational to many real-world applications. For a non-technical founder, Detectron represents the origin point of a family of technologies now used in production systems everywhere: photo apps that blur backgrounds, security cameras that detect specific people or vehicles, medical imaging that identifies anomalies, and autonomous vehicles that identify pedestrians. Important note: this original Detectron is deprecated, meaning it's no longer actively maintained. The team rewrote it from scratch as Detectron2, which is the current version to use if you need this technology. This original repository remains publicly available as a historical reference and for anyone studying the original implementations of these landmark algorithms.