xtreme1-io/xtreme1

Xtreme1 is an all-in-one data labeling and annotation platform for multimodal data training and supports 3D LiDAR point cloud, image, and LLM.

What it solves

Xtreme1 is an all-in-one platform designed to streamline the creation of high-quality multimodal training data. It addresses the inefficiencies in data annotation, curation, and ontology management for machine learning projects, specifically targeting computer vision and Large Language Models (LLMs).

How it works

The platform provides a suite of AI-powered tools for labeling and managing datasets. It supports a wide range of modalities, including 2D/3D images, LiDAR, and sensor fusion datasets. It integrates built-in pre-labeling and interactive models (such as YOLOR and OpenPCDet) to speed up the annotation process. For LLMs, it includes a beta version of an RLHF (Reinforcement Learning from Human Feedback) annotation tool.

Who it’s for

It is intended for machine learning engineers and data scientists who need to label, curate, and monitor the quality of multimodal datasets for tasks like object detection, semantic segmentation, and LLM alignment.

Highlights

  • Multimodal Support: Handles 2D/3D object detection, segmentation, and LiDAR-camera fusion.
  • AI-Assisted Labeling: Built-in interactive models for pre-labeling to reduce manual effort.
  • Ontology Management: A configurable center for managing general classes and hierarchies.
  • LLM Tooling: Includes a beta RLHF annotation tool for Large Language Models.
  • Quality Control: Tools for finding and fixing labeling errors and visualizing model results for evaluation.