xtreme1

Why we included this project

Teams building training sets that mix cameras and LiDAR, in domains like autonomous driving or robotics, will find this one of the more complete open-source labeling platforms around. It covers 2D image annotation, 3D point-cloud labeling, and fused camera-LiDAR views in one workflow, so you do not need to cobble together separate tools. Pre-labeling models from YOLOR, RITM, and OpenPCDet let annotators fix AI suggestions instead of drawing everything by hand, and the ontology center keeps class hierarchies consistent across datasets. RLHF support, still in beta, lets the same platform prepare preference data for fine-tuning LLMs. For teams running ongoing data pipelines, the data management, error-finding, and model-result visualization features help keep training data clean.