xtreme1-io/xtreme1

What it solves

Xtreme1 is an all-in-one platform designed to streamline the process of creating high-quality multimodal training data. It addresses the inefficiency and complexity of data annotation, curation, and ontology management for machine learning projects, specifically targeting computer vision (2D/3D) and Large Language Models (LLMs).

How it works

The platform provides a suite of AI-fueled tools for labeling and managing data across different modalities. It supports 2D/3D object detection, semantic/instance segmentation, and LiDAR-camera fusion. For LLMs, it includes a beta version of an RLHF (Reinforcement Learning from Human Feedback) annotation tool. It also features a configurable Ontology Center to manage classes and attributes, tools for data curation (visualizing and debugging), and model result visualization for evaluation.

Who it’s for

It is built for machine learning engineers and data scientists who need to label and build datasets for computer vision (including LiDAR and sensor fusion) and LLM training.

Highlights

• Multimodal Support: Labeling for images, 3D LiDAR, and 2D/3D sensor fusion datasets.
• AI-Assisted Labeling: Built-in pre-labeling and interactive models for detection, segmentation, and classification.
• LLM Tooling: Dedicated RLHF annotation tools for Large Language Models.
• Data Quality Control: Tools to find and fix labeling errors and monitor data quality.
• Ontology Management: A configurable center for managing general classes and hierarchies.
• Model Evaluation: Visualization of model results to assist in evaluation.