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# Intro
Xtreme1 is an all-in-one open-source platform for Multimodal training data.
Xtreme1 unlocks efficiency in data annotation, curation, and ontology management for tackling machine learning challenges in computer vision and LLM. The platform's AI-fueled tools elevate your annotation to the next efficiency level, powering your projects in 2D/3D Object Detection, 3D Instance Segmentation, and LiDAR-Camera Fusion like never before.
A long-term free plan is offered in the Xtreme1 Cloud version. Click to [🎉 Use Cloud for Free](https://app.basic.ai/login).
# Documentation
🎆 Welcome aboard! If you have any questions or doubts about features, installation, development, and deployment, you can always refer to our documentation.
[📙 Find our docs here! ](https://docs.xtreme1.io/xtreme1-docs/)
# Find Us
[Twitter](https://twitter.com/Xtreme1io) | [Medium](https://medium.com/multisensory-data-training) | [Issues](https://github.com/xtreme1-io/xtreme1/issues)
# Key features
Image Annotation (B-box, Segmentation) - [YOLOR](https://github.com/WongKinYiu/yolor) & [RITM](https://github.com/saic-vul/ritm_interactive_segmentation) | Lidar-camera Fusion Annotation - [OpenPCDet](https://github.com/open-mmlab/OpenPCDet) & [AB3DMOT](https://github.com/xinshuoweng/AB3DMOT)
:-------------------------:|:-------------------------:
 | 
:one: Supports data labeling for images, 3D LiDAR and 2D/3D Sensor Fusion datasets
:two: Built-in pre-labeling and interactive models support 2D/3D object detection, segmentation and classification
:three: Configurable Ontology Center for general classes (with hierarchies) and attributes for use in your model training
:four: Data management and quality monitoring
:five: Find labeling errors and fix them
:six: Model results visualization to help you evaluate your model
:seven: RLHF for Large Language Models :new: (beta version)
Image Data Curation (Visualizing & Debug) - [MobileNetV3](https://github.com/xiaolai-sqlai/mobilenetv3) & [openTSNE](https://github.com/pavlin-policar/openTSNE) | RLHF Annotation tool for LLM (beta version)
:-------------------------:|:-------------------------:
 | 
# Quick start
* Get access to [Xtreme1 online version](https://app.basic.ai/#/login/) without any installation :rocket:
* [Install and Quick start](https://docs.xtreme1.io/xtreme1-docs/get-started/quick-start) :cd:
* [Install with Docker](https://docs.xtreme1.io/xtreme1-docs/get-started/install-with-docker) 🐋
* [Build Xtreme1 from source code](https://docs.xtreme1.io/xtreme1-docs/get-started/install-from-source) :wrench:
## Download package
Download the latest release package and unzip it.
```bash
wget https://github.com/xtreme1-io/xtreme1/releases/download/v0.9/xtreme1-v0.9.zip
unzip -d xtreme1-v0.9 xtreme1-v0.9.zip
```
## Start all services
```bash
docker compose up
```
Visit [http://localhost:8190](http://localhost:8190) in the browser (Google Chrome is recommended) to try out Xtreme1!
## ⚠️ Install built-in models
You need to explicitly specify a model profile to enable model services.
```bash
docker compose --profile model up
```
## Enable model services
> Make sure you have installed [NVIDIA Driver](https://docs.nvidia.com/datacenter/tesla/tesla-installation-notes/index.html) and [NVIDIA Container Toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html#docker). But you do not need to install the CUDA Toolkit, as it already contained in the model image.
```bash
# You need set "default-runtime" as "nvidia" in /etc/docker/daemon.json and restart docker to enable NVIDIA Container Toolkit
{
"runtimes": {
"nvidia": {
"path": "nvidia-container-runtime",
"runtimeArgs": []
}
},
"default-runtime": "nvidia"
}
```
If you use **Docker Desktop** + **WSL2.0**, please find this [issue #144](https://github.com/xtreme1-io/xtreme1/issues/144) for your reference.
# License
This software is licensed under the Apache 2.0 LICENSE. Xtreme1 is a trademark of LF AI & Data Foundation.
Xtreme1 is now hosted in [LF AI & Data Foundation](https://medium.com/multisensory-data-training/xtreme1-the-first-open-source-labeling-annotation-and-visualization-project-is-debuting-at-the-da1d157d1512) as the 1st open source data labeling annotation and visualization project.
If Xtreme1 is part of your development process / project / publication, please cite us ❤️ :
```bash
@misc{Xtreme1,
title = {Xtreme1 - The Next GEN Platform For Multisensory Training Data},
year = {2023},
note = {Software available from https://github.com/xtreme1-io/xtreme1/},
url={https://xtreme1.io/},
author = {LF AI & Data Foundation},
}
```