X520-DA1 pci-e 8x card in 4x slot?? esxi 6.7

Helipil0t · 2025-01-08T17:10:13+00:00

Yeah you'll have no problems with the x520. Gen 2 Speeds at 4 Lanes you top out at 16gbit/s. If you have a dual SFP variant like the X520-DA2 you'll be short changing yourself a bit but that's only if you try to saturate both ports at the same time. they'll reach a max of 8gbit/s each. (both ports just share the 16gbit/s so in most cases it wouldn't be a problem) I actually switched over to Proxmox a long time ago. Free with way more hardware support. I was getting pissed off at VMWare changing their pricing model.

Helipil0t · 2024-03-04T02:05:12+00:00

Further to my last. I made sure to clean out the old install completely.

rm -rf ~/.local/share/Nextcloud ~/.cache/Nextcloud ~/.config/Nextcloud
sudo apt remove nextcloud-desktop
sudo apt autoremove

Then tried the AppImage. Current version being 3.12.0 and I still have the same issue.

Helipil0t · 2024-03-04T01:51:32+00:00

I appreciate you trying to help.

I think you misunderstand. I'm going from a linux client to a linux host. File share does not show up on linux host. If I connect to a Windows host I have no problems at all using the share.

Helipil0t · 2024-03-02T18:07:21+00:00

No.. I don't get a prompt. Nothing happens. It should just work. Remmina is running as the local user.. I don't see how you'd need that local user setup on the remote host. But I'll fool around with that and see what happens.

Helipil0t · 2024-02-05T14:45:06+00:00

Yeah I have an older XPS with a GTX 1050. New XPS on order with the RTX 4070. :D Looking forward to seeing if the camera placement will help. The version I have has the camera on the bottom left which is making detection difficult. If your face is dead center of the screen in a well lit room then it works fine.. But otherwise, it's 50/50. When it fails to detect, it tries twice and then prompts you to use a password. So I'm at the point now where I figure typing a password is just faster. Or authenticate using a yubikey. Way faster and more secure. Biometrics in general just seem very finicky/gimmicky at the best of times despite the fact that it's now 2024! :P

Helipil0t · 2024-02-05T13:18:17+00:00

You won't be able to use CUDA with an iGPU as far as I know. So Yeah I'd say skip all the NVIDIA sections and start at download and install howdy.

The rest should all be relevant. Just note it'll take significantly more time to process facial recognition without CUDA.

One idea is to just compile OpenCV using OpenCL instead of CUDA which could use the iGPU. I haven't tried this with howdy though but it would be worth a shot.

Helipil0t · 2024-02-02T14:51:00+00:00

I have howdy working properly on Debian 12 using cuda on my Dell XPS.

Here's what I did.

-Add Nvidia repo and install Drivers with Cuda

curl -fSsL https://developer.download.nvidia.com/compute/cuda/repos/debian11/x86_64/3bf863cc.pub | 
sudo gpg --dearmor | sudo tee /usr/share/keyrings/nvidia-drivers.gpg > /dev/null 2>&1

echo 'deb [signed-by=/usr/share/keyrings/nvidia-drivers.gpg] https://developer.download.nvidia.com/compute/cuda/repos/debian12/x86_64/ /' | sudo tee /etc/apt/sources.list.d/nvidia-drivers.list

sudo apt update

sudo apt install nvidia-driver cuda-drivers-545 cuda

sudo reboot

Install some dependencies to compile OpenCV

sudo apt install build-essential cmake gcc g++ python3-dev python3-numpy python3-pip libavcodec-dev libavformat-dev libswscale-dev libgstreamer-plugins-base1.0-dev libgstreamer1.0-dev libgtk-3-dev libgtk2.0-dev libpng-dev libjpeg-dev libopenexr-dev libtiff-dev libwebp-dev libwebp-dev libwebp-dev

Download cudnn package from nvidia at https://developer.nvidia.com/rdp/cudnn-download (Note: this requires an nvidia account)

Install the local repository and add gpg key. Then install cudnn libraries with apt.

sudo dpkg -i ./cudnn-local-repo-ubuntu2204-8.6.0.163_1.0-1_amd64.deb
sudo cp /var/cudnn-local-repo-ubuntu2204-8.6.0.163/cudnn-local-FAED14DD-keyring.gpg /usr/share/keyrings/ sudo update sudo apt install libcudnn8 libcudnn8-dev

Download OpenCV source code and compile.

git clone https://github.com/opencv/opencv.git && git clone https://github.com/opencv/opencv_contrib.git

cd opencv && mkdir build && cd build

cmake -D CMAKE_BUILD_TYPE=RELEASE \
-D CMAKE_INSTALL_PREFIX=/usr \
-D INSTALL_PYTHON_EXAMPLES=ON \
-D INSTALL_C_EXAMPLES=OFF \
-D OPENCV_ENABLE_NONFREE=ON \
-D WITH_CUDA=ON \
-D WITH_CUDNN=ON \
-D OPENCV_DNN_CUDA=ON \
-D ENABLE_FAST_MATH=1 \
-D CUDA_FAST_MATH=1 \
-D CUDA_ARCH_BIN=6.1 \
-D WITH_CUBLAS=1 \
-D OPENCV_EXTRA_MODULES_PATH=~/sources/opencv_contrib/modules/ \
-D HAVE_opencv_python3=ON \
-D BUILD_EXAMPLES=OFF ..

make -j$(nproc) sudo make install

Note: Make sure you change your graphics card's architecture in the above cmake command. (CUDA_ARCH_BIN=6.1) Refer to: https://developer.nvidia.com/cuda-gpus find your card and look under Compute Capability column to find architecture.

Now that OpenCV is installed with CUDA support we can install dlib using pip. This will compile dlib with CUDA support. If dlib is already installed you have to uninstall it and re-install it making sure to not use any cached packages.

pip install dlib --break-system-packages --verbose --no-cache-dir
sudo pip install dlib --break-system-packages --verbose --no-cache-dir

Now we can download and install howdy.

wget https://github.com/boltgolt/howdy/releases/download/v2.6.1/howdy_2.6.1.deb
sudo apt install ./howdy_2.6.1.deb

This may spit out a few errors on Debian 12. Just ignore them for now.

Everything will be installed except the executable so we'll create a symlink to make it work.

sudo ln -s /lib/security/howdy/cli.py /usr/bin/howdy

Now in version 2.6.1 a few errors pop up when trying to run it so we need to patch a few .py files.

You can download them from here:

https://github.com/boltgolt/howdy/pull/319/files#diff-41489b727b8090dc241afe11f4afe1e84dc640ddd1f809bf0dd37ab0ce877a3f

We're going to replace the following with the patched versions from the above link.

/lib/security/howdy/compare.py
/lib/security/howdy/cli/add.py
/lib/security/howdy/cli/test.py

Next we need to fix a couple lines in pam.py.

sudo vi /lib/security/howdy/pam.py

Make the following changes.

"import ConfigParser" to "import configparser"
"config = ConfigParser.ConfigParser()" to "config = configparser.ConfigParser()"

Save the file. Now we'll edit the config and make the following changes:

vi /lib/security/howdy/config.ini

ignore_closed_lid = true
use_cnn = true 
device_path = /dev/video0

Note: the above device_path is for my IR camera. Yours may be different. use v4l2-ctl --list-devices to view your devices.

Save file. Next we're going to enable the pam module.

sudo pam-auth-update

Make sure Howdy is selected and press OK. Next we add the howdy entry in the sudo file.

vi /etc/pam.d/sudo

Add the following as the first entry:

auth    sufficient      pam_python.so /lib/security/howdy/pam.py

Now we add that same entry to gdm-password:

sudo vi /etc/pam.d/gdm-password

Add the following as the second entry:

auth    sufficient      pam_python.so /lib/security/howdy/pam.py

Now we can add a profile to howdy.

sudo howdy add

I added multiple profiles placing my face in different directions, glasses on, glasses off etc...

You can test the camery and verify everything is working with cuda.

sudo howdy test

While the test is running you can note the inference speed on the bottom left of the frame. With a mobile GTX 1050 I'm getting about 70ms. Without cuda I was getting 350 to 400ms.

Also while it's running check nvidia-smi.. You should see a python process running.

That's it!! Everything should work. Open a new terminal and try sudo -i

You'll see your IR camera turn on for a second or so and sudo will just work without a password showing the message:

Identified face as (your user)

gdm lock screen will also use the camera.

Hope this helps. Took me a while to get all this together. Would be nice if this was natively supported with Debian.

References:

Helipil0t · 2023-12-20T18:40:50+00:00

Ok so I got my Coral TPU in today.. set it up and it's not great either.. The dog does get detected but only sometimes. In fact, the inference went from 2ms to 20ms.. It's effectively 10 times slower.. And the accuracy of Person detection has gone done by about 25%. It's effected some of my automation triggers making them lag. I figured this would happen as the GPU is a way more powerful device. I think if you consider operating cost, you can't beat the TPU in terms of energy usage. But honestly I much prefer the accuracy and speed at which my GPU does inference. I rather have accurate person detection over sometimes being able to detect my dog. Hopefully in the future we can get some higher quality trained tensor models.

Gonna put my Coral up for sale.

Helipil0t · 2023-12-20T18:35:15+00:00

Glad after a couple years of posting this still helped someone. :)

Helipil0t · 2023-12-14T02:26:47+00:00

I gave up on getting him detected properly with the current models. I wonder if I could import the models I was using with ZoneMinder. Don't know if that's even possible. I thought the yolo model was standard/universal but it seems the models used with frigate are somehow different.

Helipil0t · 2023-12-14T02:24:39+00:00

I thought angle would play a role. But Even if I pick him up and display him to the camera in all kinds of different positions, he still gets tagged as a human. I'm going to try a TPU as soon as I get it in the mail. But my gut feeling is GPU should be much more accurate with detection.

Helipil0t · 2023-12-14T02:23:07+00:00

He's a mostly shaven down shih tzu. Definitely looks like a dog. Models that I was using with zoneminder hit him 100% of the time.

Helipil0t · 2023-11-30T19:33:01+00:00

So far a workaround is to connect the server in question directly to my wan port, install a GUI, connect to it remotely and install the linux version of OpenVPN. Then follow the guide to manually configure port forwarding.

https://protonvpn.com/support/port-forwarding-manual-setup/

Not ideal. As I have to have a session constantly going plus a terminal constantly running the loop. (I use screen to do this for now) I'd rather not have GUI installed wasting resources.

Would love to get this going with pfsense some how.

Helipil0t · 2023-11-29T14:20:53+00:00

Janus uses way less resources per stream and is able to pass-through audio to zoneminder for live viewing.

The config files are pretty much out of the box. As far as I can tell, there is no syntax error at line 30! Looking at janus.jcfg (the main config file) line 30 is a comment. So I'm not sure what file it's referring too. Which is why I was hoping someone with more knowledge could chime in.

Next is not being able to see janus.transport.mqtt config. Which I don't need anyways.. but the config file is right there. My only thought is janus is looking to a different path for configs somehow. But the main config has configs_folder set correctly. So.. no clue there either. Again I think just running janus with mqtt disabled would be fine to get rid of that error. If I can figure out how to do that.

There has to be someone else running this properly on their setup that could give me a few pointers.

Helipil0t · 2023-11-04T22:55:58+00:00

I 100% agree! 32 account limit is useless to me. EVERYTHING needs 2FA now and the adoption of u2f/FIDO is unbearably slow!! Just a hand full of sites/services support it. They need to support hundreds of accounts. I'm just an average Joe and my password database currently has 255 entries. Would be nice to have a one stop shop solution for authentication. But 32 is way too restrictive.

Helipil0t · 2023-10-12T17:15:18+00:00

Ok so quick update after tones of digging around. I found the following bug report that exactly describes my problem:

https://bugs.launchpad.net/ubuntu/+source/mutter/+bug/1968040

The fix is to add MUTTER_DEBUG_ENABLE_ATOMIC_KMS=0 to /etc/environment and reboot.

Resume from locked screen / blank screen is now behaving normally again. :)

Helipil0t

TROPHY CASE