Skip to main content
SDK Version: 2.3.3

DXNN - DEEPX NPU SDK

DX-AllSuite (DEEPX All Suite) is an all-in-one software platform designed to streamline the entire process of compiling, optimizing, and deploying AI inference applications on DEEPX NPUs. It ensures optimal compatibility and powerful hardware performance through a complete toolchain that covers everything from model creation to real-world "Physical AI" deployment.

Full Architecture Overview​

DXNN SDK Full Architecture Overview

Figure. DXNN SDK Full Architecture Overview.

Key Features​

  • High Efficiency: Equipped with the proprietary DX-COM compiler that extracts 100% of NPU performance. It utilizes advanced quantization (Intelligent Quantization with INT8) to minimize accuracy loss while maximizing inference speed.
  • Seamless Integration: Build intelligent video analytics pipelines that bridge the entire pre-processing, inference, and post-processing workflow. Using DX-Stream (GStreamer-based custom plugins), you can deploy complex vision tasks without extensive code modifications.
  • Flexible Ecosystem: Fully supports Python and C++ APIs and offers a ModelZoo with over 270 optimized models. As a leader in the Open-Source Physical AI Alliance, we provide seamless workflows for popular frameworks.

Getting Started​

DX-AllSuite provides two environments depending on your intended use. Choose the environment that fits your needs to get started.

AI Model Compile Environment (Host PC)​

This environment is used for converting and optimizing trained AI models into DEEPX NPU-specific binaries.

  • Arch: x86_64
  • OS: Ubuntu 24.04 / 22.04 / 20.04 (LTS), Fedora, Redhat, CentOS
  • Hardware: x86_64 Host PC
  • Software: Python 3.8~3.12, CUDA (Optional for simulation)
  • Key Tasks: AI model (.onnx) compilation, Quantization, .dxnn generation
  • Action: DX-Compiler Local Installation Guide Link

AI Model Runtime Environment (Target Device)​

This environment is for performing inference and running applications on devices physically equipped with DEEPX NPUs.

  • Arch: x86_64, aarch64
  • OS: Ubuntu 24.04 / 22.04 / 20.04 / 18.04 (LTS), Debian 13 / 12
  • Hardware: Host PC / Target Board (DEEPX NPU is required)
  • Software: Python 3.8+
  • Key Tasks: .dxnn model execution, real-time data inference, resource management
  • Action: DX-Runtime Installation Guide Link
Activation Required

A system reboot is mandatory after installation to properly load the NPU Driver into the kernel.

sudo reboot

Supported Models​

DX-AllSuite supports a vast array of industry-standard AI architectures, optimized for peak performance on our NPU.

  • Image Classification: AlexNet, ResNet/ResNeXt/WideResNet, MobileNet, EfficientNet (Lite/V2), ViT/DeiT/BEiT, MobileViT, FastViT, CasViT, RegNet, ShuffleNet, VGG, and more.
  • Object Detection: YOLO families (YOLOv3–YOLOv11, YOLOX, YOLO26), SSD, EfficientDet, NanoDet, DamoYOLO.
  • Segmentation: DeepLabV3/DeepLabV3+, SegFormer, BiSeNet, UNet, YOLACT, and YOLO-based segmentation variants (YOLOv5/YOLOv8/YOLO26).
  • Advanced Vision Tasks: Face analysis (Detection, Recognition, Landmarks, Attributes), Human/Hand Pose Estimation, Low-Light Enhancement, Image Denoising, Super Resolution, Depth Estimation, Oriented Object Detection (OBB), Zero-Shot Instance Segmentation, and Person Attributes.
Pro Tip

Instead of compiling models yourself, you can download ready-to-use binaries from the DEEPX ModelZoo, which features over 270 optimized models.

Documentation Navigation​

If you are a first-time user, we recommend following the documentation in this order.

Support​

The DEEPX Technical Support Team is here to help you build smooth AI solutions.

Last updated: