BasicAI launched the world's first open-source platform for multisensory training data.
Xtreme1 provides deep insight into data annotation, data curation, and ontology management to solve 2D image and 3D point cloud dataset ML challenges. The built-in AI-assisted tools take your annotation efforts to the next level of efficiency for your 2D/3D Object Detection, 3D Instance Segmentation, and LiDAR-Camera Fusion projects.
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Join the Xtreme1 community on Slack to share your suggestions, advice, and questions with us.
Image Bounding-box Annotation - YOLOR | Image Segmentation Annotation - RITM |
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1️⃣ Supports data labeling for images, 3D LiDAR and 2D/3D Sensor Fusion datasets
2️⃣ Built-in pre-labeling and interactive models support 2D/3D object detection, segmentation and classification
3️⃣ Configurable Ontology Center for general classes (with hierarchies) and attributes for use in your model training
4️⃣ Data management and quality monitoring
5️⃣ Find labeling errors and fix them
6️⃣ Model results visualization to help you evaluate your model
3D Point Cloud Cuboid Annotation - OpenPCDet | 2D & 3D Fusion Object Tracking Annotation - AB3DMOT |
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Get early access to Xtreme1 online version without any installation 🚀
Any OS can install the Xtreme1 platform with Docker Compose (installing Docker Desktop on Mac, Windows, and Linux devices). On the Linux server, you can install Docker Engine with Docker Compose Plugin.
Component | Recommended configuration |
---|---|
CPU | AMD64 or ARM64 |
RAM | 2GB or higher |
Hard Drive | 10GB+ free disk space (depends on data size) |
For Mac, Windows, and Linux with desktop:
Software | Version |
---|---|
Docker Desktop | 4.1 or newer |
For Linux server:
Software | Version |
---|---|
Docker Engine | 20.10 or newer |
Docker Compose Plugin | 2.0 or newer |
Right row models only can be running on Linux server with NVIDIA Driver and NVIDIA Container Toolkit.
Component | Recommended configuration |
---|---|
GPU | Nvidia Tesla T4 or other similar Nvidia GPU |
GPU RAM | 6G or higher |
RAM | 4G or higher |
Click the latest release on the right of repository home, select asset whose name likes xtreme1-<version>.zip
, and double click the downloaded package to unzip it. Or use the following command to download the package and unzip it, you should replace the version number to the lastest.
wget https://github.com/basicai/xtreme1/releases/download/v0.5.2/xtreme1-v0.5.2.zip
unzip -d xtreme1-v0.5.2 xtreme1-v0.5.2.zip
Enter into the release package directory, and execute the following command to start all services. It need a few minutes to init database and prepare a test dataset, if everything shows ok in console, you can open address http://localhost:8190
in your browser (Google Chrome is recommended) to try out Xtreme1. You can replace localhost
to ip address if you want to access from another computer.
docker compose up
⚠️ Some Docker images, such asMySQL
, do not support ARM architecture, if your computer is using ARM CPU, such as Apple M1, you can add Docker Compose override filedocker-compose.override.yml
, which contains the following content. It will force usingamd64
image to run onARM64
platform through QEMU emulation, but the performance will be affected.
services:
mysql:
platform: linux/amd64
# Start in foreground.
docker compose up
# Or add -d option to run in background.
docker compose up -d
# When up finished, you can start or stop all or specific service.
docker compose start
docker compose stop
# Stop all services and delete all containers, but data volumes will be kept.
docker compose down
# Delete volumes together, you will lose all your data in mysql, redis and minio, be careful!
docker compose down -v
Docker compose will pull all service images from Docker Hub, including basic services mysql
, redis
, minio
, and application services backend
, frontend
. You can find the username, password, hot binding port to access MySQL, Redis and MinIO in docker-compose.yml
, for example you can access MinIO console at http://localhost:8194
. We use Docker volume to save data, so you won't lose any data between container recreating.
# You need to explicitly specify model profile to enable model services.
docker compose --profile model up
Make sure you have installed NVIDIA Driver and NVIDIA Container Toolkit. But you do not need to install the CUDA Toolkit, as it already contained in the model image.
We are using Docker BuildKit to accelerate the building speed, such as cache Maven and NPM packages between builds. By default BuildKit is not enabled in Docker Desktop, you can enable it as following. For more details, you can check the official document Build images with BuildKit.
# Set environment variable to enable BuildKit just for once.
DOCKER_BUILDKIT=1 docker build .
DOCKER_BUILDKIT=1 docker compose up
# Or edit Docker daemon.json to enable BuildKit by default, the content can be something like '{ "features": { "buildkit": true } }'.
vi /etc/docker/daemon.json
# You can clear builder cache if you encounter some package version related problem.
docker builder prune
git clone https://github.com/basicai/xtreme1.git
cd xtreme1
The docker-compose.yml
default will pull application images from Docker Hub, if you want to build images from source code, you can comment service's image line and uncomment build line.
services:
backend:
# image: basicai/xtreme1-backend
build: ./backend
frontend:
# image: basicai/xtreme1-frontend
build: ./frontend
Then when you run docker compose up
, it will first build backend
and frontend
image and start services. Be sure to run docker compose build
when code changed, as up command will only build image when it not exist.
You should not commit your change to
docker-compose.yml
, to avoid this, you can copydocker-compose.yml
to a new filedocker-compose.develop.yml
, and modify this file as your development need, as this file is already added into.gitignore
. And you need to specify this specific file when running Docker Compose command, such asdocker compose -f docker-compose.develop.yml build
.
To get more development guides, you can read the README in each application service's directory.
This software is licensed under the Apache 2.0 LICENSE © BasicAI.
If Xtreme1 is part of your development process / project / publication, please cite us ❤️ :
@misc{BasicAI,
title = {Xtreme1 - The Next GEN Platform For Multisensory Training Data},
year = {2022},
note = {Software available from https://github.com/basicai/xtreme1/},
url={https://basic.ai/},
author = {BasicAI},
}