nvidia-patch
deepstack_licenceplate_model
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nvidia-patch | deepstack_licenceplate_model | |
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309 | 1 | |
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- | GNU General Public License v3.0 only |
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nvidia-patch
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Do I need to have a beefy PC to transcode 4k? Or can I just buy my brother an Nvidia shield pro and setup a cheap server on my end?
This can be patched out. https://github.com/keylase/nvidia-patch
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Transcoding 4K HDR tone mapping
NVIDIA Corporation GA106 [GeForce RTX 3060] and I applied the patch here https://github.com/keylase/nvidia-patch
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Linux 6.6 to Protect Against Illicit Behavior of Nvidia Proprietary Driver
> CUDA, and pretty much all optimization(hacks) done to run games better
And arbitrary limitations implemented at the driver level to force you to purchase their enterprise GPUs, see https://github.com/keylase/nvidia-patch#nvenc-and-nvfbc-patc...
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GPU Guide (For AI Use-Cases)
Nvidia has no motivation to make a consumer card with lots of VRAM, that's basically the only (relevant) separator between the GeForce family and the Quadro lineup.
There are restrictions on NVENC streams with consumer cards, but that has been a solved problem for a while [0].
If they were to make a consumer card with more VRAM, it would immediately undercut their own Quadro/Tesla lineup, which cost substantially more. I don't see a reason for them to do it.
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Can't hardware transcode mor than 5 at a time even after all the required changes
I have never had to do the session limit bump thing from the last link. I have a 3090 as well and simply did the initial unlock, which worked fine. I would reinstall fresh drivers from Nvidia, making sure you install the newest one that is supported by the unlock tool (536.40 as of this post, the GitHub for the patch has links to the drivers - https://github.com/keylase/nvidia-patch/tree/master/win)
- Can you flash any consumer version Nvidia card to remove the streaming limits?
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Can my GPU transcode?
Aren't these Quadro versions. The patch here. https://github.com/keylase/nvidia-patch supports Quadro versions of you click on the win clickable.
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Let's have a talk - Guide to Choosing the Best Plex Server for You
Second, the GPU. The GPU is probably as important as the CPU, and in some cases more important, and when we talk about GPUs we will primarily talk about Nvidia GPUs as they are officialy supported by the Plex team. NVIDIA GPUs are important for Plex hardware transcoding due to their dedicated video encoding/decoding units, superior performance, wide codec support, improved video quality, reduced CPU load, power efficiency. They offer a powerful hardware acceleration solution that can greatly enhance the transcoding capabilities of a Plex server. It's also important to note that Nvidia GPUs require a patch to unlock the number of HW transcoding streams. Dedicated GPUs are large pieces of hardware and have their place in desktop PCs. However, they can also be used with mini-PCs by using an external GPU enclosure.
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What does this Max. 3 concurrent stream cap mean anway?
As there's no NVENC patch available (yet) for the Beta driver branch - referring to this one: https://github.com/keylase/nvidia-patch - which can lift the limits of HW transcoding, I was now wondering a little, as I can see 5 (hw) streams on Plex, which actually shouldn't/cannot be the case no?
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Is there somewhere that lists Nvidia GPUs.
I haven’t done this yet but there is a patch on GitHub that removes the limitation for consumer GPUs. Makes lower end cards more attractive for this type of work
deepstack_licenceplate_model
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What is the benefit of GPU?
To train a custom model I went here How to Deepstack Custom Models. I used the free Google Cloud option. And if you go here Deepstack License Plate someone has a trained custom license plate module you could try without training. To handle all the communication between Blue Iris and Deepstack (To Include MQTT / Home Assistant / Telegram etc) I use this wonderful open source tool called Node Deepstack AI which lets you use both the included Deepstack models and custom models because the dev is awesome and implemented that for me. Let me know if you have any questions.
What are some alternatives?
vgpu_unlock - Unlock vGPU functionality for consumer grade GPUs.
unmanic - Unmanic - Library Optimiser
nvlax - Future-proof NvENC & NvFBC patcher (Linux/Windows)
Sunshine - Self-hosted game stream host for Moonlight.
wlroots - A modular Wayland compositor library
Proxmox-Nvidia-LXC- - how to create an Proxmox LXC in 6.2-1
sunshine - Host for Moonlight Streaming Client
jellyfin-media-player - Jellyfin Desktop Client based on Plex Media Player
get-priv-data - Retrieve NvFBC Private Data (UUID) from a Steam installation
FidelityFX-FSR - FidelityFX Super Resolution
obs-nvfbc