From 23327adedaae45df56e63eeb0942e05da2c67031 Mon Sep 17 00:00:00 2001 From: Jagger Wang Date: Thu, 30 May 2024 11:58:55 +0800 Subject: [PATCH] Update README --- README.md | 19 ++++++++++--------- 1 file changed, 10 insertions(+), 9 deletions(-) diff --git a/README.md b/README.md index c82475fb..caa41cbe 100644 --- a/README.md +++ b/README.md @@ -9,7 +9,8 @@ [![Use Cloud for Free](https://basicai-asset.s3.amazonaws.com/docs/Open-source/Operation/App_Button.png)](https://app.basic.ai) -# Intro +# 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, 2D/3D Semantic/Instance Segmentation, and LiDAR-Camera Fusion like never before. @@ -20,7 +21,7 @@ The README document only includes content related to installation, building, and Find us on [Twitter](https://twitter.com/Xtreme1io) | [Medium](https://medium.com/multisensory-data-training) | [Issues](https://github.com/xtreme1-io/xtreme1/issues) -# Key features +# 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) :-------------------------:|:-------------------------: @@ -40,7 +41,7 @@ Image Annotation (B-box, Segmentation) - [YOLOR](https://github.com/WongKinYiu/y :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) +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) :-------------------------:|:-------------------------: ![](/docs/images/2d_v.gif) | @@ -78,7 +79,7 @@ The built-in models only can be running on Linux server with [NVIDIA Driver](htt ## Install with Docker -### Download package +### Download Package Download the latest release package and unzip it. @@ -87,7 +88,7 @@ wget https://github.com/xtreme1-io/xtreme1/releases/download/v0.9.1/xtreme1-v0.9 unzip -d xtreme1-v0.9.1 xtreme1-v0.9.1.zip ``` -### Start services +### Start Services Enter into the release package directory, and execute the following command to start all services. It needs a few minutes to initialize database and prepare a test dataset. @@ -120,7 +121,7 @@ docker compose down docker compose down -v ``` -### Install built-in models +### Start Built-in Models You need to explicitly specify a model profile to enable model services. @@ -145,7 +146,7 @@ Make sure you have installed [NVIDIA Driver](https://docs.nvidia.com/datacenter/ If you use **Docker Desktop** + **WSL2.0**, please find this [issue #144](https://github.com/xtreme1-io/xtreme1/issues/144) for your reference. -### Running docker images on ARM architecture machines +### Run on ARM CPU Please note that certain Docker images, including `MySQL`, may not be compatible with the ARM architecture. In case your computer is based on an ARM CPU (e.g. Apple M1), you can create a Docker Compose override file called docker-compose.override.yml and include the following content. While this method uses QEMU emulation to enforce the use of the ARM64 image on the ARM64 platform, it may impact performance. @@ -175,14 +176,14 @@ vi /etc/docker/daemon.json docker builder prune ``` -### Clone repository +### Clone Repository ```bash git clone https://github.com/basicai/xtreme1.git cd xtreme1 ``` -### Build images and run services +### Build Images and Run Services The `docker-compose.yml` default will pull application images from Docker Hub, if you want to build images from source code, you can comment on the service's image line and un-comment build line.