jetson orin 重新安裝

$ sudo apt-get update

$ sudo apt-get upgrade

$ sudo apt install python3-pip

$  sudo apt-get install curl

$ sudo pip3 install -U jetson-stats

$ sudo jtop

info 中 CUDA, cuDNN 出現 MISSING, 需安裝 nvidia-jetpack

$ sudo apt-get install nvidia-jetpack

出現錯誤

E: Unable to locate package nvidia-jetpack

$ sudo vi /etc/apt/sources.list.d/nvidia-l4t-apt-source.list 

deb https://repo.download.nvidia.com/jetson/common r36.3 main

deb https://repo.download.nvidia.com/jetson/t234 r36.3 main

$ sudo apt-get update

$ sudo apt-get install nvidia-jetpack

安裝 chromium

$ sudo apt-get install chromium-browser

$ snap download snapd --revision=24724

$ sudo snap ack snapd_24724.assert

$ sudo snap install snapd_24724.snap

$ sudo snap refresh --hold snapd

$ chromium-browser

安裝 Deepstream https://docs.nvidia.com/metropolis/deepstream/7.0/dev-guide/text/DS_Installation.html

$ pkg-config --modversion glib-2.0

2.72.4

$ sudo apt install meson ninja-build

$ git clone https://github.com/GNOME/glib.git

$ cd glib

$ git checkout <glib-version-branch>

# e.g. 2.76.6

$ meson build --prefix=/usr

$ ninja -C build/

$ cd build/

$ ninja install

$ pkg-config --modversion glib-2.0

$ sudo apt install \

libssl3 \

libssl-dev \

libgstreamer1.0-0 \

gstreamer1.0-tools \

gstreamer1.0-plugins-good \

gstreamer1.0-plugins-bad \

gstreamer1.0-plugins-ugly \

gstreamer1.0-libav \

libgstreamer-plugins-base1.0-dev \

libgstrtspserver-1.0-0 \

libjansson4 \

libyaml-cpp-dev

$ git clone https://github.com/confluentinc/librdkafka.git

$ cd librdkafka

$ git checkout tags/v2.2.0

$ ./configure --enable-ssl

$ make

$ sudo make install

$ sudo mkdir -p /opt/nvidia/deepstream/deepstream/lib

$ sudo cp /usr/local/lib/librdkafka* /opt/nvidia/deepstream/deepstream/lib

$ sudo ldconfig

$ wget --content-disposition 'https://api.ngc.nvidia.com/v2/resources/org/nvidia/deepstream/7.0/files?redirect=true&path=deepstream_sdk_v7.0.0_jetson.tbz2' --output-document 'deepstream_sdk_v7.0.0_jetson.tbz2'

$ sudo tar -xvf deepstream_sdk_v7.0.0_jetson.tbz2 -C /

$ cd /opt/nvidia/deepstream/deepstream-7.0

$ sudo ./install.sh

$ sudo ldconfig

nvidia jetson orin 安裝 vino

$ sudo apt-get update

$ sudo apt-get upgrade

$ sudo apt-get install vino

$ 

$ mkdir -p ~/.config/autostart

$ cp /usr/share/applications/vino-server.desktop ~/.config/autostart/.

$ 

$ cd /usr/lib/systemd/user/graphical-session.target.wants

$ sudo ln -s ../vino-server.service ./.

$ 

$ gsettings set org.gnome.Vino prompt-enabled false

$ gsettings set org.gnome.Vino require-encryption false

$ 

$ gsettings set org.gnome.Vino authentication-methods "['vnc']"

$ gsettings set org.gnome.Vino vnc-password $(echo -n 'thepassword'|base64)

更改 Docker Root Dir

參考 https://ithelp.ithome.com.tw/articles/10235112

參考 https://medium.com/@calvineotieno010/change-docker-default-root-data-directory-a1d9271056f4

$ docker info

$ vi /etc/docker/daemon.json

{

  "data-root": "/path/to/new/docker_data"

}

$ sudo systemctl stop docker

$ sudo systemctl stop docker.socket

$ sudo rsync -avh /var/lib/docker/* /path/to/new/docker_data

$ sudo systemctl start docker

$ sudo systemctl start docker.socket

$ docker info

Jetpack 6.0 更新 CUDA 12.2 至 12.6

本篇參考 安裝 Flux & ComfyUI 將其中的一些細節敘述清楚

參考 https://www.jetson-ai-lab.com/tutorial_comfyui_flux.html

參考 https://docs.nvidia.com/metropolis/deepstream/dev-guide/text/DS_Installation.html#id10

$ sudo jtop

CUDA: 12.2.140

cuDNN: 8.9.4.25

TensorRT: 8.6.2.3

因為需要從 cuda-12.2 更新到 cuda-12.6

而在更新的過程中，會移除 Deepstream-7.0

所以需要自己安裝 Deepstream-7.1

記錄下目前的版本資料

$ dpkg -l>dekg_jp6.0.txt

$ wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-aarch64.sh

$ chmod +x Miniconda3-latest-Linux-aarch64.sh

$ ./Miniconda3-latest-Linux-aarch64.sh

$ conda update conda

$ conda create -n comfyui python=3.10

$ conda init bash

$ cat .bashrc

$ conda activate comfyui

$ conda info --envs

$ conda deactivate

$ conda activate comfyui

$ conda list

$ wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/arm64/cuda-keyring_1.1-1_all.deb

$ sudo dpkg -i cuda-keyring_1.1-1_all.deb

$ sudo apt-get update

$ sudo apt-get -y install cuda-toolkit-12-6 cuda-compat-12-6

$ update-alternatives --list cuda

$ update-alternatives --display cuda

$ sudo update-alternatives --config cuda

cuda-12.6

$ apt list -a cudnn

$ sudo apt-get install cudnn=9.10.2-1

$ apt list -a python3-libnvinfer

$ sudo apt-get install python3-libnvinfer=10.7.0.23+cuda12.6

The following packages will be REMOVED:

  deepstream-7.0 libnvparsers-dev nvidia-tensorrt-dev

$ sudo apt-get install python3-libnvinfer-dev=10.7.0.23-1+cuda12.6

$ sudo jtop

CUDA: 12.6.85

cuDNN: 9.10.2

TensorRT: 10.7.0.23

$ wget --content-disposition 'https://api.ngc.nvidia.com/v2/resources/org/nvidia/deepstream/7.1/files?redirect=true&path=deepstream-7.1_7.1.0-1_arm64.deb' -O deepstream-7.1_7.1.0-1_arm64.deb

$ sudo apt-get install ./deepstream-7.1_7.1.0-1_arm64.deb

$ export BNB_CUDA_VERSION=126

$ export LD_LIBRARY_PATH=/usr/local/cuda-12.6/lib64:$LD_LIBRARY_PATH

$ git clone https://github.com/timdettmers/bitsandbytes.git

$ cd bitsandbytes

$ pip uninstall numpy

$ pip install "numpy<2.0"

$ mkdir -p build

$ cd build

$ cmake .. -DCOMPUTE_BACKEND=cuda -DCUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda-12.6

$ make -j$(nproc)

$ cd ..

$ python setup.py install

$ pip install http://jetson.webredirect.org/jp6/cu124/+f/5fe/ee5f5d1a75229/torch-2.3.0-cp310-cp310-linux_aarch64.whl

$ pip install http://jetson.webredirect.org/jp6/cu124/+f/988/cb71323efff87/torchvision-0.18.0a0+6043bc2-cp310-cp310-linux_aarch64.whl

$ pip install http://jetson.webredirect.org/jp6/cu124/+f/0aa/a066463c02b4a/torchaudio-2.3.0+952ea74-cp310-cp310-linux_aarch64.whl

$ python3

>>> import bitsandbytes as bnb

>>> print(bnb.__version__)

$ git clone https://github.com/comfyanonymous/ComfyUI.git

$ cd ComfyUI

$ pip install -r requirements.txt

$ cd custom_nodes

$ git clone https://github.com/ltdrdata/ComfyUI-Manager.git

$ cd ..

$ mkdir workflows

$ cd workflows

$ wget https://www.jetson-ai-lab.com/assets/workflow_agx_orin_4steps.json

$ cd ..

到 https://huggingface.co/black-forest-labs/FLUX.1-schnell/tree/main

下載 flux1-schnell.safetensors 放到 models/unet

下載 ae.safetensors 放到 models/vae/FLUX1

到 https://huggingface.co/stabilityai/stable-diffusion-3-medium/tree/main/text_encoders

下載 clip_l.safetensors 和 t5xxl_fp8_e4m3fn.safetensors 放到 models/clip

$ python main.py --port=8080

在 http://127.0.0.1:8080/ 網頁，按 Queue Prompt, 等待...

Load workflow_agx_orin_4steps.json 時，需修改 "Load VAE" 的 vae_name 到 FLUX1/ae.safetensors

記錄下目前的版本資料

$ dpkg -l>dpkg_jp6.0_comfyui.txt

若需要將 cuda-12.6 還回 cuda-12.2

參考記錄下來的版本資料 dpkg_jp6.0.txt dpkg_jp6.0_comfyui.txt

參考 https://repo.download.nvidia.com/jetson 下載 package

移除不必要的 package

$ sudo apt-get remove --purge package

安裝 package 時，常出現相依性錯誤，所以有時要變更安裝順序

甚至最後重新安裝一遍，確保全部安裝

$ cd jetpack_6.0

$ ./download.sh

$ ./rollback.sh

$ ./install.sh

參考 https://catalog.ngc.nvidia.com/orgs/nvidia/containers/l4t-cuda/tags

$ xhost +

$ docker run -it --rm --net=host --runtime nvidia\

  -e DISPLAY=$DISPLAY \

  -v /tmp/.X11-unix/:/tmp/.X11-unix \

  nvcr.io/nvidia/l4t-cuda:11.4.19-runtime

$ docker run -it --rm --net=host --runtime nvidia\

  -e DISPLAY=$DISPLAY \

  -v /tmp/.X11-unix/:/tmp/.X11-unix \

  nvcr.io/nvidia/l4t-cuda:12.2.12-runtime

$ docker run -it --rm --net=host --runtime nvidia\

  -e DISPLAY=$DISPLAY \

  -v /tmp/.X11-unix/:/tmp/.X11-unix \

  nvcr.io/nvidia/l4t-cuda:12.6.11-runtime

docker: Error response from daemon: failed to create task for container: 

failed to create shim task: OCI runtime create failed: 

failed to create NVIDIA Container Runtime: failed to construct OCI spec modifier: 

requirements not met: unsatisfied condition: cuda>=12.6 (cuda=12.2): unknown.

因為 Jetpack 6.0 自帶 CUDA 12.2

使用的 docker image 不能比 CUDA 12.2 高 

$ docker run -it --rm --net=host --runtime nvidia\

  -e DISPLAY=$DISPLAY \

  -v /tmp/.X11-unix/:/tmp/.X11-unix \

  -w /opt/nvidia/deepstream/deepstream-7.0 \

  nvcr.io/nvidia/deepstream-l4t:7.0-samples-multiarch

因為 Jetpack 6.0 自帶 CUDA 12.2

使用的 docker image 不能比 CUDA 12.2 高 

所以也無法使用 Deepstream 7.1

$ docker run -it --rm --net=host --runtime nvidia\

  -e DISPLAY=$DISPLAY \

  -v /tmp/.X11-unix/:/tmp/.X11-unix \

  -w /opt/nvidia/deepstream/deepstream-7.1 \

  nvcr.io/nvidia/deepstream-l4t:7.1-samples-multiarch

安裝 Flux & ComfyUI

參考 https://www.jetson-ai-lab.com/tutorial_comfyui_flux.html

$ sudo jtop

CUDA: 12.2.140

cuDNN: 8.9.4.25

TensorRT: 8.6.2.3

因為需要從 cuda-12.2 更新到 cuda-12.6

而在更新的過程中，會移除 Deepstream-7.0

所以需要自己安裝 Deepstream-7.1

記錄下目前的版本資料

$ dpkg -l>dekg_jp6.0.txt

$ wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-aarch64.sh

$ chmod +x Miniconda3-latest-Linux-aarch64.sh

$ ./Miniconda3-latest-Linux-aarch64.sh

$ conda update conda

$ conda create -n comfyui python=3.10

$ conda init bash

$ cat .bashrc

$ conda activate comfyui

$ conda info --envs

$ conda deactivate

$ conda activate comfyui

$ conda list

$ wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/arm64/cuda-keyring_1.1-1_all.deb

$ sudo dpkg -i cuda-keyring_1.1-1_all.deb

$ sudo apt-get update

$ sudo apt-get -y install cuda-toolkit-12-6 cuda-compat-12-6

$ update-alternatives --list cuda

$ update-alternatives --display cuda

$ sudo update-alternatives --config cuda

cuda-12.6

$ sudo apt-get install cudnn=9.5.1-1

$ sudo apt-get install python3-libnvinfer=9.5.1-1

The following packages will be REMOVED:

  deepstream-7.0 libnvparsers-dev nvidia-tensorrt-dev

$ sudo apt-get install python3-libnvinfer-dev=10.6.0.26-1+cuda12.6

$ sudo jtop

CUDA: 12.6.77

cuDNN: 9.5.1

TensorRT: 10.6.0.26

$ wget --content-disposition 'https://api.ngc.nvidia.com/v2/resources/org/nvidia/deepstream/7.1/files?redirect=true&path=deepstream-7.1_7.1.0-1_arm64.deb' -O deepstream-7.1_7.1.0-1_arm64.deb

$ sudo apt-get install ./deepstream-7.1_7.1.0-1_arm64.deb

$ export BNB_CUDA_VERSION=126

$ export LD_LIBRARY_PATH=/usr/local/cuda-12.6/lib64:$LD_LIBRARY_PATH

$ git clone https://github.com/timdettmers/bitsandbytes.git

$ cd bitsandbytes

$ pip uninstall numpy

$ pip install "numpy<2.0"

$ mkdir -p build

$ cd build

$ cmake .. -DCOMPUTE_BACKEND=cuda -DCUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda-12.6

$ make -j$(nproc)

$ cd ..

$ python setup.py install

$ pip install http://jetson.webredirect.org/jp6/cu124/+f/5fe/ee5f5d1a75229/torch-2.3.0-cp310-cp310-linux_aarch64.whl

$ pip install http://jetson.webredirect.org/jp6/cu124/+f/988/cb71323efff87/torchvision-0.18.0a0+6043bc2-cp310-cp310-linux_aarch64.whl

$ pip install http://jetson.webredirect.org/jp6/cu124/+f/0aa/a066463c02b4a/torchaudio-2.3.0+952ea74-cp310-cp310-linux_aarch64.whl

$ python3

>>> import bitsandbytes as bnb

>>> print(bnb.__version__)

$ git clone https://github.com/comfyanonymous/ComfyUI.git

$ cd ComfyUI

$ pip install -r requirements.txt

$ cd custom_nodes

$ git clone https://github.com/ltdrdata/ComfyUI-Manager.git

$ cd ..

$ mkdir workflows

$ cd workflows

$ wget https://www.jetson-ai-lab.com/assets/workflow_agx_orin_4steps.json

$ cd ..

到 https://huggingface.co/black-forest-labs/FLUX.1-schnell/tree/main

下載 flux1-schnell.safetensors 放到 models/unet

下載 ae.safetensors 放到 models/vae/FLUX1

到 https://huggingface.co/stabilityai/stable-diffusion-3-medium/tree/main/text_encoders

下載 clip_l.safetensors 和 t5xxl_fp8_e4m3fn.safetensors 放到 models/clip

$ python main.py --port=8080

http://127.0.0.1:8080/

Load workflow_agx_orin_4steps.json 時，需修改 "Load VAE" 的 vae_name 到 FLUX1/ae.safetensors

記錄下目前的版本資料

$ dpkg -l>dekg_jp6.0_cuda-12.6.txt

若需要將 cuda-12.6 還回 cuda-12.2

$ cd jetpack_6.0

$ ./download.sh

$ ./install.sh

參考記錄下來的版本資料 dekg_jp6.0.txt dekg_jp6.0_cuda-12.6.txt

移除不必要的 package

$ sudo apt-get remove --purge package

參考 https://catalog.ngc.nvidia.com/orgs/nvidia/containers/l4t-cuda/tags

$ xhost +

$ docker run -it --rm --net=host --runtime nvidia\

  -e DISPLAY=$DISPLAY \

  -v /tmp/.X11-unix/:/tmp/.X11-unix \

  nvcr.io/nvidia/l4t-cuda:11.4.19-runtime

$ docker run -it --rm --net=host --runtime nvidia\

  -e DISPLAY=$DISPLAY \

  -v /tmp/.X11-unix/:/tmp/.X11-unix \

  nvcr.io/nvidia/l4t-cuda:12.2.12-runtime

$ docker run -it --rm --net=host --runtime nvidia\

  -e DISPLAY=$DISPLAY \

  -v /tmp/.X11-unix/:/tmp/.X11-unix \

  nvcr.io/nvidia/l4t-cuda:12.6.11-runtime

docker: Error response from daemon: failed to create task for container: 

failed to create shim task: OCI runtime create failed: 

failed to create NVIDIA Container Runtime: failed to construct OCI spec modifier: 

requirements not met: unsatisfied condition: cuda>=12.6 (cuda=12.2): unknown.

$ docker run -it --rm --net=host --runtime nvidia\

  -e DISPLAY=$DISPLAY \

  -v /tmp/.X11-unix/:/tmp/.X11-unix \

  -w /opt/nvidia/deepstream/deepstream-7.0 \

  nvcr.io/nvidia/deepstream-l4t:7.0-samples-multiarch

docker run -it --rm --net=host --runtime nvidia\

  -e DISPLAY=$DISPLAY \

  -v /tmp/.X11-unix/:/tmp/.X11-unix \

  -w /opt/nvidia/deepstream/deepstream-7.1 \

  nvcr.io/nvidia/deepstream-l4t:7.1-samples-multiarch

球型攝影機 onvif

參考 https://github.com/FalkTannhaeuser/python-onvif-zeep

參考 https://www.onvif.org/onvif/ver20/util/operationIndex.html

$ python -m venv --system-site-packages /mnt/Data/envs/onvif

$ source /mnt/Data/envs/onvif/bin/activate

$ pip install --upgrade onvif_zeep

$ git clone https://github.com/FalkTannhaeuser/python-onvif-zeep.git

$ onvif-cli devicemgmt GetHostname --user 'admin' --password 'sh22463458' --host '192.168.113.203' --port 80

查詢 ProfileToken

$ onvif-cli media GetProfiles --user 'admin' --password 'sh22463458' --host '192.168.113.203' --port 80 | grep -o "'token': '[^']*'" | awk -F': ' 'END {print $2}'

'MediaProfile00002'

$ onvif-cli ptz GotoPreset "{'ProfileToken':'MediaProfile00002', 'PresetToken':'9'}" --user 'admin' --password 'sh22463458' --host '192.168.113.203' --port 80

$ onvif-cli ptz GetPresets "{'ProfileToken':'MediaProfile00002'}" --user 'admin' --password 'sh22463458' --host '192.168.113.203' --port 80

$ onvif-cli ptz AbsoluteMove "{'ProfileToken':'MediaProfile00002', 'Position':{'PanTilt':{'x': -0.05, 'y': 0.6}, 'Zoom':0.5}}" --user 'admin' --password 'sh22463458' --host '192.168.113.203' --port 80

相對位置移動, 0:不移動 正:上,右,放大 負:下,左,縮小

左上

$ onvif-cli ptz RelativeMove "{'ProfileToken':'MediaProfile00002', 'Translation':{'PanTilt':{'x': 0.105, 'y': 0.22}, 'Zoom':0.3}}" --user 'admin' --password 'sh22463458' --host '192.168.113.203' --port 80

右下

$ onvif-cli ptz RelativeMove "{'ProfileToken':'MediaProfile00002', 'Translation':{'PanTilt':{'x': -0.115, 'y': -0.201}, 'Zoom':0.3}}" --user 'admin' --password 'sh22463458' --host '192.168.113.203' --port 80

左上

$ onvif-cli ptz RelativeMove "{'ProfileToken':'MediaProfile00002', 'Translation':{'PanTilt':{'x': 0.105, 'y': 0.21}, 'Zoom':0.15}}" --user 'admin' --password 'sh22463458' --host '192.168.113.203' --port 80

右下

$ onvif-cli ptz RelativeMove "{'ProfileToken':'MediaProfile00002', 'Translation':{'PanTilt':{'x': -0.105, 'y': -0.21}, 'Zoom':0.15}}" --user 'admin' --password 'sh22463458' --host '192.168.113.203' --port 80

open webui 使用網頁搜尋

https://developers.google.com/custom-search/v1/introduction?hl=zh-tw

點選 程式化搜尋引擎 (免費版) 使用者：取得金鑰

https://programmablesearchengine.google.com/controlpanel/all

點選 新增

輸入 搜尋引擎名稱

在 Paid Element API 金鑰 欄位，輸入之前取得的 金鑰

取得 搜尋引擎 ID

進入 open webui, 點選左下角使用者，選擇 設定

點選 管理員設定/網頁搜尋

開啟 啟用網頁搜尋

網頁搜尋引擎: google_pse

開啟 Full Context Mode

輸入 Google PSE API 金鑰

輸入 Google PSE 引擎 ID

網頁搜尋引擎: duckduckgo

可以直接使用

在 open webui 的傳送訊息欄位下方，可以點選 網頁搜尋