The BEST Self-Hosted CCTV Solution With AI Object Detection?
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- เผยแพร่เมื่อ 5 ส.ค. 2024
- Frigate is an open-source, free, AI accelerated object-based detection CCTV solution! Not only does it enable you to keep your recordings private, it also allows you to focus on exactly the things you want to record. In this video I detail the features of Frigate, how to configure and deploy it in Docker, as well as how to passthrough a Google Coral TPU to your VM on Proxmox.
Recommended Cameras:
Unifi G3 Flex: amzn.to/3QZAIDj
Loryta: amzn.to/3qKf3o7
Amcrest: amzn.to/44ziJ9Q
Coral AI:
amzn.to/47sDjuV
Docker-Compose: github.com/JamesTurland/JimsG...
Proxmox GPU Passthrough: pve.proxmox.com/wiki/PCI_Pass...
Find me on:
Discord: / discord
Twitter: / jimsgarage_
Reddit: / jims-garage
GitHub: github.com/JamesTurland/JimsG...
00:00 - Introduction to Frigate
02:35 - Frigate Features Walkthrough
07:00 - Coral TPU Passthrough to Proxmox
10:18 - Coral TPU Driver Install
12:20 - Docker Config Review
15:50 - Frigate Config File Review
21:20 - Frigate Deployment Via Docker
22:10 - Testing Frigate Dashboard & Walkthrough
24:12 - Frigate Home Assistant Overview
25:20 - Outro - วิทยาศาสตร์และเทคโนโลยี
Hi Jim. Thank you for referring me to this video in your response to my comment on your UniFi Controller on Docker video! (Shout-out to Lawrence Systems for referring to your video in his recent UniFi video) I find your videos very useful and informative. I thoroughly enjoy how you go in-depth with explaining the compose .yaml file. I would also like to thank you for bringing up the Coral TPU. I never realized such a thing existed. You have earned my Like and Subscription, and I hope you earn more from others, as well
I really appreciate your feedback, thank you. Important to note that since the video an integrated GPU is now supported, thus the TPU isn't strictly required.
@@Jims-Garage Good to know. I will likely be saving my iGPU resources for a display in case I need to do some troubleshooting. With the TPU being so small and relatively inexpensive, as well as being another thing to experiment with, I will likely go with the TPU route
thank for the demo and info, have a great day
Thanks, you too!
This would be a far better solution than my current setup, of hours of highly suspicious birds and rustling leaves.
Totally agree, precisely why I set this up. Works very well.
Definitely something that is on my list to do
Highly recommend it if you're in the market for CCTV
Just a note: if you don't want e.g.: the iGPU to be exclusive to frigate (to use for decoding/transcoding) use a docker LXC instead of a full VM. I have a miniITX system that has the iGPU used by both proxmox (for graphical console access) and frigate on a docker that is in a LXC.
Also to add: not all m.2 e-key pcie wifi slots support two devices, so some might only see a single device.
Thanks for your post. Yes, needs to support bifurcation for two devices.
Great video. Thanks!
You're welcome 😁
If you use a computer with an intel cpu, you can also use the openvino model, and vaapi for acceleration. That model seems to be better for detecting people, and does not need a coral, and isn't as cpu heavy as using just cpu.
Correct, it's great that this has been added. To clarify though, an intel CPU with iGPU.
Thanks for the great video Jim, I've followed your lead a got a M.2 dual chip version as well, what PCIe adapter did you use please?
Can you link it? Want to make sure
Is the MQTT server only necessary for using Frigate with Home Assistant? Is it needed otherwise? I was going to run it directly, without HA integration. Great video, btw!
Yes, mqtt is for home automation (via home assistant usually). You don't need it to run standalone.
Hello, I habe got a question.
Would it be possible to run all the software including proxmox & Frigate on a RP4 while having the about the same performance? This is intended to get a mobile AI system. Would there be any bottlenecks? We would run the system on a SSD instead of using SD cards of course.
Thanks for the nice video.
I appreciate any comments on this.
Hey, good question, I haven't ever done it, but... Proxmox has a small performance impact of around a few percent, so not much. Docker is also very lightweight, but you could run binaries. The most important thing would be to use a coral USB, there's no way the Pi's CPU could do AI detection. With a coral AI it would likely be very capable for CCTV.
Not sure if you have settled on a RPi4 but I would seriously consider an RPi5 instead since it has native m.2 compatability now with a pi hat. It would make the system very viable without any workarounds messing with performance in anyway. Would still need a coral. But it will be a much more viable system for longer and will survive many updates.
the detect feed should be low res and low fps. 5 fps and ~640x480 are enough for detection, and is way less load on the TPU and CPU
the detect and the record stream URLs can be different
Hello very great video. Hello !
I have my home assistant on a rasberry 4. I have now bought myself a Google Coral Edge TPU USB Accelerator. How do I install it in the raspberry? Is it just to insert it into usb and run or do I have to make some settings? Or do I have to make some setting in frigate.yaml ?
Hi, thanks! First off, how are you running services on your Pi? Is it through Docker? Secondly, you'll need to deploy Frigate, configure it to use the Coral TPU, and then install the Home Assistant Frigate integration. This sounds like a lot, but it's pretty straightforward. The instructions in the video should work for a Pi.
@@Jims-Garage Hello ! Thanks for quick reply. I don't drive docks. What do you mean with you'll need to deploy Frigate, configure it to use the Coral TPU ? Where do i fing a good video for that ?
Hi Jim, all your project are really cool, i got some problems with frigate, in the future I'll buy coral hw, but for the moment i just want to see the web ui with a camera, to take a look at the interface, when i start the container i can open the web ui, but it still load, and five me only the top bar with nothing else, anyone know why? I don't use exactly your same config.
Check the logs, likely a camera connection issue.
Can I run Frigate in a more rudimentary way? I am currently using MotionEye but it isn't being maintained very well any more and I imagine it's going to fall further behind as time goes on. Currently run it in a VM on XCP-NG and Coral doesn't really work well as a passthru. I am only really interested in viewing it and recording when basic motion occurs, don't need the AI aspects so much.
You can install bare metal if you want. I have run it in Proxmox with coral passthrough for a couple of years now
@@Jims-Garage Yeah ideally I would but I'm fully VM-based in my homelab so prefer to keep it virtual if I can. I'm going to see if I can set it up in a "basic" way for now. Basically just going to down my Motioneye container and try Frigate instead - fingers crossed! If it works real well I'll see if there's more I can do or need to do with the AI detection (my homelab is short on rackspace).
@@knightlautrec4311 I'm not entirely sure what you're asking. What do you mean by rudimentary?
@@Jims-Garage Sorry, as in JUST basic motion detection, not AI-powered (which requires Coral or a lot of CPU power).
What other selfhosted app that we can deploy to make use of this google coral?
None that I use, but there are some machine learning ones that do. I believe immich will in the future.
Jim, thanks for the video. What do you use the udm for ?
I don't, I sold it. I use Sophos XG instead, and have the controller as a docker container.
@@Jims-Garage thanks you need to show us your setup.
Can this also be used to match faces ? Can you train it on people ?
No, unfortunately it's just shapes.
So you can use this with any modern cctv setup?
It should work with most IP cameras.
Thanks for the tutorial and helping me decide that this is NOT for me. I don’t have the time to be figuring out this system. No wonder it is free
Fair enough. It's really powerful once you first configure it, but not for everyone.
Hi Jim, great video. What about Blue Iris, despite the fact that it is not open source?
Cheers
I've heard it's good, but I went with frigate due to price, home assistant integration, and open source nature.
Is there an app for iOS or android?
Yes, Home Assisstant is available on iOS. Otherwise, access frigate through the web browser.
@@Jims-Garage can you easily access home assistant from outside your network?
@@lewistaylor6695 yes, simply port forward (although there are some security steps you should follow like having a reverse proxy with SSL, I have videos)
i can get p5 with 8GB so that holds promis
great video. I have an Intel NUC. curious if the PCIe chip will fit in the Intel NUC or perhaps go wit the USB Coral. Thank you!
Best to check the max size m.2 it will take Vs the m.2 coral tpu. Otherwise you could do a m.2 key adapter to a full PCIe slot. Failing that, USB coral.
As you're running an Intel NUC you'd probably be better off just using the openvino plugin for inference
@@OliverHamilton good point, they've recently added support.
Jewel chip?
Dual, perhaps my pronunciation 😂
Unify? Store in Cloud? Well, now I know you do not go to the top of my list…
Modern cameras do have the detection included, so external AI/process/software are not necessary anymore.
Not sure I follow you. I use unifi cameras with frigate and store footage encrypted in the cloud. What is bad about that? I have complete control of all hardware and storage. The coral tpu means you can buy cheap cameras, lots of them, and have AI on them all. It's far more cost effective.
UDM-Pro = Bad naming for enterprise, grossly under-powered and very limited abbilities. That being said, what you are doing on Frigate is supported on UniFi Protect.
For security, running VM's is for enthusiasts and those who enjoy complexity and dreams of compact shite. Run hardware and be done with it.
The big one not mentioned, Frigate is very much Google entangled, no thanks.
It's very expensive for what it is.
In what way is frigate entangled with google?
The license is MIT, which is fully open source and forkable. There are over 150 contributers, so if a company would close it, the community would very much keep it open.
The image processing is done via Tensorflow and OpenCV. Yes, Tensorflow was originally developed by Google, but is also open source with the apache license. So again, F-up and the community will fork it. OpenCV was originally sponsored by Intel for that matter, but it leads an open source on its own.
Tensorflow works best with a Coral TPU, yes. A very specific piece of hardware for Tensorflow specific calculations, but it is equally able to use a GPU at a slightly higher power per calculation. It's not entwined in that way either. It runs fully locally if you want to. So no google involvement there either.
Android is very much google, but android alternatives like GrapheneOS and Cyanogen are very much not despite the framework being android. And there are a multitude of project available where the community has forked and re-opened a project. So in that regard, who cares who originally developed something. If the project is big enough, it will remain open.
You say "just run hardware". But that is just basically it. You trade time for money. And granted UniFi appears to be one of the very few localized hardware solutions. But what does UniFi use on the background for image recognition? There is a high probability that it's Tensorflow :) But talking entanglement? You trade one company for another. At least frigate is open source.
@@patrickd9551 thanks, I agree with all of this.
I totally understand that dedicated hardware is the ideal choice, however, udmp is not that hardware. No object detection, no external storage, and not even a redundant drive (or certainly when I had one).
UDM = Great product, don't blame the tool just because you don't have the knowledge how to use it properly.
@@angelln25
LOL, thanks for the laugh ya muppet.