System Update

For details, refer to the Flashing OS Image，The TFCard&eMMC image (Debian 12) is recommended.

The following instructions are based on this image. If using a custom-built image, pay attention to operational details.

System Boot

Pre-Boot Preparation

1. 5V USB power supply

2. mini HDMI cable and display

3. USB serial tool (e.g., SLogic Combo8 (optional, for debugging/login))

Normal Boot

1. Login Interface

   • Connect a display via mini HDMI and power on. The core board’s blue LED and Hat baseboard’s white LED should light up, indicating normal power supply.

   • If the eMMC contains the default Raspberry Pi slave image, flash a new standalone image to the TF card and insert it into the M4N-Hat.

   • Press and hold the BOOT0 button, then press RST. After ~20 seconds, the LightDM login screen will appear, indicating a successful boot.

2. Xfce4 Desktop

   • Connect a mouse/keyboard to the onboard USB-A port for input.

   • Default credentials: Username: root, Password: root.

Advanced: Serial & SSH Login

The onboard Type-C USB port serves as the default debug UART (115200 8n1).

Use a serial tool to view kernel logs or log in directly via terminal.

For SSH access, expand network connectivity via USB Ethernet/WiFi dongles.

Note: The system only has the root superuser, and SSH password login is disabled by default for security. For temporary access, refer to here。

LLM

DeepSeek-R1 & QWen3

Left: DeepSeek-R1 1.5B
Right: QWen3 0.6B

Deployment guide: here

VLM

internVL3

Demo video:

DepthAnything v2

1. Download the axcl npu python library

2. Install: pip install axengine-x.y.z-py3-none-any.whl.

3. Run:

   source ../venv-llm/bin/activate
   python python/infer.py --img examples/demo02.jpg --model depth_anything_v2_vits_ax650.axmodel
   

Interactive Image Segmentation & Inpainting

A QT-based GUI for real-time segmentation (point/box selection) and inpainting.

Open Source Official GitHub Repo: SAM-ONNX-AX650-CPP
Download prebuilt binaries or compile from source.

Example: Removing a player from a photo:

Live Demo (Screenshots):

RAW	SAM	Inpaint

Interactive Text-to-Image Search (CLIP)

A QT-based GUI using OpenAI’s CLIP (Contrastive Language–Image Pre-training) for zero-shot image retrieval via text input (supports Chinese/English).

Open Source Official GitHub Repo: CLIP-ONNX-AX650-CPP

DEMO VIDEO

1. Install QT:

   apt update
   apt install cmake qt6-base-dev
   

2. Download prebuilt files (executable, models, test images/text):

   • Baidu Pan

3. Extract CLIP.zip to /root/Desktop/:

   root@m4nhat-7190c7:~/Desktop/CLIP# tree -L 1
   .
   ├── CLIPQT
   ├── cn_vocab.txt
   ├── coco_1000
   ├── libonnxruntime.so
   ├── libonnxruntime.so.1.16.0
   ├── onnx_models
   ├── run_en.sh
   ├── run_zh.sh
   └── vocab.txt
   

4. Run in Desktop's terminal:

   ./run_zh.sh  # For Chinese  
   ./run_en.sh  # For English  
   

Screenshots: