Deepstack coral. Reload to refresh your session.

Deepstack coral If I start frigate this increases to 75 to 80%!! However, I have a google coral DeepStack is an AI API engine that serves pre-built models and custom models on multiple edge devices locally or on your private cloud. I have them outside and instead of using the blue iris motion detection, I have a script that checks for motion every second on the camera web service and if there is motion, the script pulls down the image from the camera's http service, feeds it into deepstack and if certain parameters are met, triggers a recording. Docs Sign up. Note: If you pass a model to the Edge TPU Compiler that uses float inputs, the compiler leaves a quantize op at the beginning of your graph (which runs on the CPU). Imagine a raspberry pi with TPU linked to esp32 that maske itself as usb periferals (mouse/keyboard) and a web cam you have an AI Warcraft fishing bot that runs on external HW and is pretty much undetectable since you are not running anything on your system It exposes the coral TPU through a deepstack compatible API. CompreFace Image Classification Responsive, mobile friendly Web UI written in TypeScript React MQTT support Home Assistant MQTT Discovery Lookback, buffers frames to record before the event actually happened Using poor quality cable for the Coral and connecting it on USB2 (480M in lsusb) makes the inference speed and the CPU usage go kaboom. dat) functionality is very useful when trying to understand what DeepStack is doing. Next, you need to install both the Coral PCIe driver and the Edge TPU runtime. Frigate Deepstack Docker Compose Setup. Would also like to try face recognition. I've been playing with CodeProject. An alternative would be for a third party to write a compatibility layer that provides a DS compatible REST interface but then communicates with the coral accelerator. The downloads are now available for 2. 8 (I was on 2. Looking forward to soon establishing the MQTT link between Deepstack and Frigate. Print Coral’s local AI technology enables new possibilities across almost any kind of industry Building smarter cities In order to reach the true potential of a “smart city,” AI processing will have to move from the cloud onto secure local devices, maintaining individual privacy, reducing data transfer rates, and enabling quicker reaction times for critical systems. I have tpu google coral and nvidia Quard Home Assistant Community Codeproject. I use deepstack_objects + Coral rest server as a presence detection when not at home --> it is a reliable alarm system. See Fine Tuning Settings article. I’ve updated the instructions below to reflect the latest version since there were a ton of changes. The DeepStack + Blue Iris article talks about the integration and proper setup. Only Frigate can use the Coral gpu power. On my Ryzen 5600G with GPU cpu usage is pretty low (especially compared to other solutions I tried before like AgentDVR along with DeepStack or MotionEye). AI for various AI features including object recognition, face recognition, ALPR (Automatic License Plate Recognition), and super resolution (enhance). Also you can go to their discussing board if you find any bugs or have a feature request. Mac and regular windows users my experience performance issues. I guess if Codeproject added support for Jetson, I wouldn’t even be looking, but now I’m glad they didn’t :) I’ll be watching this Hi all I just published a custom component for face and object (e. Easy Sbc Io Frigate . Frigate. Log in Sign up. Hi, As you all probably know there is a new version of frigate addon aka container that Frigate Deepstack Coral Integration. Explore easy SBC IO solutions for Frigate, We created a lot of DeepStack self-help content. AI. Learn more -> On this 2022-09-09 - v3 Edit: Updated to reflect final working LXC->Docker->Frigate approach. 👍 4 Clooos, lrybak, VikeDragon, and Banzarykey reacted with thumbs up emoji I didn't have much of a choice. But so far it seems to be solid. I'm pretty impressed by the object detection and performance. Often your use case might involve objects that DeepStack doesn’t natively support, or you might want to fine-tune the object detection for your own kind of images, probably CCTV images or night images if the built-in object detection API doesn’t work perfectly enough Nice but just as an FYI you can't SHARE a coral, so you would need another one dedicated / mapped only to that docker. -p 80:5000 This makes DeepStack accessible via port 80 of the machine. DeepStack operates as a deep learning server that processes images and video streams for various AI tasks. I trigger “light on” in a room by PIR but I trigger “light off” using cameras+deepstack to make sure people are not in the room anymore --> this is much more robust than PIR specially if like sitting on the sofa Tensorflow via Google Coral EdgeTPU DeepStack. Below are the steps to set up and configure Deepstack within your Frigate environment. I have Coral USB running with CP. These images are passed from the API to the configured detector(s) until a match is found that meets the configured requirements. Buying a Coral and tying that in sounded like a cool idea, but I got the impression that the Coral may need more power than a Pi4B's USB port could handle (?). Reply reply idan37s • Frigate and deepstack run on jetson + coral, as jetson has a hardware video decoder for frigate, and gpu for deepstack. The promises of Artificial Intelligence are huge but becoming a machine learning engineer is hard. I am currently using Deepstack and AITool, but an edge solution would give me the security of not having the BI machine exposed to the wild and should lessen the CPU/GPU hit each time motion is detected. Partner products with Coral intelligence link. Explore how to integrate Deepstack with Google Coral in Frigate for enhanced object detection and processing capabilities. I didn't expect this to work first shot, since its a work in progress and very beta. Frigate Community Reviews. Coral is plugged in. Hello, I was wondering if anyone has tried all of these: Frigate vs Doods vs BlueIris vs Deepstack with Google Coral for object detection and could give us a summary of Pros / Cons for each of them ? I have mentioned the development of that package but never tried to get it working, no. Was previously running DS on a vintage NUC with Frigate, Frigate still running but did away with DS. I’ve had a USB Coral Edge TPU for a few years. It I’ve been a Blue Iris user for 10+ years. yaml image_processing: - platform: deepstack_object ip_address: localhost port: To integrate Deepstack with Frigate effectively, you will utilize the Deepstack API for object detection. pouvez vous aider un pauvre novice 🙂 You signed in with another tab or window. HA and doubletake run on another ARM sbc along with photoprism for my photos which has CPU face recognition, so I used that to get training pics for family. You will need a computer with a decent amount of RAM available, Just released v0. j’essaye d’installer DeepStack mais impossible malgré d’avoir vu plusieurs video . Learn how to set up Frigate with Docker Compose for Coral devices, optimizing your video surveillance system. You can use that instead of deepstack API for the backend. Post Reply. Explore how Frigate integrates with Deepstack Coral TPU for efficient object detection and processing. DeepStack is an AI API engine that serves pre-built models and custom models on multiple edge devices locally or on your private cloud. AI server detector. At some point I’ll write another version of this I've had Deepstack running on my mini server in a docker this way for years. All the documentation and logs are recommending using Coral TPU and remind me that using the CPU is not a good idea. Check it out 🙂. I configured face recognition with Frigate, Double-take and Deepstack on a Raspberry pi 4 8Gb with a Google Coral. AI) on an nVidia GPU. I might add another camera though. Supported platforms are: NVIDIA Jetson via Docker. Docker is a virtualization platform that makes it easy to set up an isolated environment for this tutorial. The World's Leading Cross Platform AI Engine for Edge Devices - Releases · johnolafenwa/DeepStack Frigate Deepstack Coral Integration. Return Carefully connect the Coral Mini PCIe or M. 2: Install the PCIe driver and Edge TPU runtime. person) detection using Deepstack, which runs locally in Docker and costs you nothing. This division of labor allows Frigate to manage multiple camera feeds without overloading the Coral, ensuring that it remains responsive and effective across various scenarios. At the heart of our accelerators is the Edge TPU coprocessor. Plus, since I already had a Synology (that had more horsepower than a Pi4B, plus direct access to the storage) I thought I'd EDIT 01-27-2020: Frigate 0. Explore the integration of Frigate with LXC Coral USB for enhanced video processing capabilities. To integrate Deepstack with Frigate effectively, you will Dec 11, 2020 · Deepstack has no support for Coral TPU at this time. robmarkcole (Robin) August 2, 2019, 5:27am 281. ai frigate detectors - face recognition . Frigate Deepstack Coral Tpu Overview. ddaniel (Daniel Dekovic) February 12, 2024, 7:22pm 1. Thanks in advance! 😊🙏 I don't think the deepstack devs would add support for coral accelerators as they're basically competing products. jpg and latest. Learn more about Coral technology. First off, thank you so much for all involved in this project. Right now I’m using the CPU This is my configuration in configuration. Quite an elegant solution having the coral TPU interface emulate the deepstack platform to leverage the came component for both. My opinions on the others. Personally I wanted to only use local processing. Is coral support likely? - DeepStack Forum. This integration allows Frigate to leverage Deepstack's capabilities, enhancing its performance in detecting and tracking objects. Then click on Settings under Configuration, select AI Servers from the dropdown menu, and click Configure. I've been using frigate for car versus human using a coral usb. Really sad the Codeproject. I know several people who use the Coral USB Accelerator and Frigate (which uses TensorFlow). Last updated on To set up AI Servers, click on the icon at the top left of the main Agent DVR UI. I am now running Frigate with docker on bare metal Debian install (After wasting an entire day trying to use Ubuntu and At the moment I’m still using Blue Iris with an Nvidia Jetson and Deepstack, very similar to Coral, for low cost AI object detection. I use blue iris for continuous recording and backup recording of activity. 5. Note that by default the component will not automatically scan images, but requires you to call the image_processing. You will need a computer with a decent amount of RAM available, as Deepstack is using deep-learning models. Background: I had a working setup on ESXI, but alas, no PCIE slot and thus no way to pass through the USB google coral in such a way that the VM will recognize it. The DeepStack Gotchas article is learnings from past tickets. DeepStack is device and language agnostic. (See this thread here for more on that However, Im using the same half-pci coral in unraid with frigate and it works without issues. With the Coral Edge TPU™, you can run an object detection model directly on your device, using real-time video, at over 100 frames per second. Getting 8ms inference time across 3 cams running 30 fps each. Also, Frigate will optionally convert your separate camera streams in a single The coral-pi-rest-server is a deepstack-like API wrapper for a coral device so Blue Iris doesn't need to know anything about the coral. I dedicated 16 vCPU threads for the frigate VMs and passthrough the GeForce GT1030 video card to help with the h264 decoding for only two 1080p cameras. Link to Yes and no, for unraid no, for edge computing AI vision, it's great. The face registration endpoint allows you to register pictures of person and associate it with a userid. Then we'll show you how to run a TensorFlow Lite model on the Edge TPU. Which server should I use the CPU or the GPU? I don’t know if it has any effect because I have a Google Coral installed. I personally settled on using Deepstack which I have found to be fairly accurate and when configured correctly not overkill on my server. CPU and Coral Collaboration: The CPU is tasked with detecting motion, while the Coral is dedicated to object detection. AI after seein Explore how to integrate Deepstack with Google Coral in Frigate for enhanced object detection and processing capabilities. Magic919 Posts: 1381 Joined: Wed Sep 18, 2013 6:56 am. To integrate Deepstack with Frigate effectively, you will leverage the capabilities of the Deepstack / CodeProject. 5 watts for each Deepstack or coral? I run blue iris with deepstack on a 4th gen i5, but was considering switching to corl/frigate because my cpu usage spikes to 100 when doing object detection Reply reply Top 1% Rank by size . The framework for I am creating this poll to help users decide if they should switch from DeepStack to CodeProject. My hope is that I’ve set the priv acces for dev/usb busI’ve installed TF-Lite and it’s running. Reply reply FoShizzleShindig • That is with the full model. Or should I stick with Deepstack? Bonus question: is there a way I can use the Coral USB TPU in both Frigate and the Double Take detector? I tried using the Coral USB TPU simultaneously in 2 Frigate instances and could not make it work. CodeProject. Jun 29, 2020 · I have an Intel NUC with Ubuntu 20. This crashed my Proxmox server in 2 days - My Coral dual-edge TPU was delivered! - Got my hands on an older gen 2 i5 system with 8gb of RAM. Then configure face recognition. Frigate Config Coral Overview Explore the configuration options for Frigate with Coral, enhancing performance and efficiency in . The cpu load goes from 2 to 40 (when I Set up the Docker container. -v localstorage:/datastore This specifies the local volume where DeepStack will store all data. Explore user insights and discussions about Frigate, a powerful tool for managing your media library effectively. The performance of DeepStack and its opponents was evaluated using AIVAT, a provably unbiased low-variance technique based on carefully constructed control variates. You can even run multiple detection models concurrently on one Edge TPU, while maintaining a high frame rate. Configuration. Alternatively a custom object Frigate Deepstack Coral Integration. Looks like the alternatives are dead too-- Deepstack is no longer being developed either (docker image last updated over 2 years ago), and Compreface likewise has almost a year since last update. With everything set up correctly, six camera streams of 1080p might see about 5-8% CPU usage. All Blue Iris knows is that it's talking to a remote/different Deepstack/SenseAI server. Using our Docker container, you can easily set up the required environment, which includes TensorFlow, Python, Object Detection API, and the the pre-trained checkpoints for MobileNet V1 and V2. I’ve ordered a coral to try with both Frigate and codeprojectAI. 8. Did you build the docker image and added any extra paramenters to import the coral device? Moreover, did you do the opencv cuda compiling, or are you using without cuda. AI and the Coral which was similar to CPU times for this machine, however with the Coral device the CPU usage in task manager This is the first issue I've had with Deepstack, using it since November. This page is your guide to get started. Explore how Frigate enhances Deepstack Coral for efficient object detection and video analysis in real-time applications. The World's Leading Cross Platform AI Engine for Edge Devices. DeepStack runs completely offline and independent of the cloud. The architecture consists of Learn how to set up Deepstack with Docker Compose for Frigate, enhancing your video surveillance capabilities. You can run it on Windows, Mac OS, Linux, Raspberry PI and use it with any programming Frigate is a network video recorder that has build in object detection. Reload to refresh your session. g. My question is how much improvement I get from the Coral USB accelerator for my current setup. If no, how do I solve this? thanks for every response DeepStack is an AI server that empowers every developer in the world to easily build state-of-the-art AI systems both on premise and in the cloud. 5 of the deepstack face integration, adding ability to save files (same functionality in deepstack object). Frigate / Frigate Deepstack Docker Compose Setup. Frigate Lxc Coral Usb Overview. Added notes on frigate config, camera streams and frigate storage. My Deepstack implementation randomly broke one day and BI stopped recording any alerts even though everything was still recording and all the right services were running, seemed to be in the right places, and configured properly but nothing including reinstalling would get it working again so I deleted DS and then installed CodeProject. ZM with Coral TPU USB. DeepStack is an AI server that empowers every developer in the world to easily build state-of-the-art AI systems both on premise and in the cloud. Can Agent DVR use Coral TPU for person detection? Currently using Deepstack but would like to off load workload to Coral TPU. It's 2 steps (add repo, install add-on) To optimize the performance of DeepStack in Home Assistant, it is essential to focus on several key areas that can significantly enhance the overall efficiency of the system. If I start frigate this increases to 75 to 80%!! However, I have a google coral connected to my NUC. I wish DT could parse the info between the 2 detectors for a combined threashold value that we When the frigate/events topic is updated the API begins to process the snapshot. il parle souvent d’install via docker mais jai pas car je suis sous haos homeassistant . Motion detection Face recognition via: dlib DeepStack. Compreface is another app like Deepstack. ai still does not support Jetson or Coral, which are the most environmentally friendly, low-cost way to run these types of AI. Doods: I like that is continuously runs its detection on a given camera stream. Setup Deepstack i just setup deepstack and doubletake, but double take is not really that accuratecould also be my settings not properly configured ill post my full frigate config, if you see anything wrong please let me know. Please post your likes and dislikes, your posts will help improve CodeProject. Still works great! EDIT 12-15-2020: I just noticed that Frigate has a 0. AI for a few days on a Windows 10 machine with BlueIris. Coral provides a complete platform for accelerating neural networks on embedded devices. Hi everyone, I’ve been trying to get the deepstack addon to run for an entire afternoon now. Re Docker I definitely welcome the ability to specify the model. I'm seeing object detection around the 200ms using CP. The config made some significant breaking changes. Open menu . To integrate Deepstack with Frigate effectively, you Aug 2, 2024 · google coral and frigate; I notice that if I do not run frigate there is a CPU usage of 15 to 25%. So as long as your tensor parameters are quantized, it's okay if the input and output tensors are float because they'll be converted on the CPU. This page provides several trained models that Coral EdgeTPU: The Google Coral EdgeTPU is available in USB and m. This integration allows you to utilize advanced object detection features provided by Deepstack, enhancing the overall functionality of Frigate. Is this normal? Because if I start deepstack and double take my CPU usage quickly approaches 100%. A full height, Home Assistant custom component for Deepstack object detection. That said, wouldn't hurt to look deeper on DeepStack github and see if Feb 1, 2022 · It also uses deepstack for its smart detection. AI and dont want to end with it. Understanding the DeepStack analysis (. Any feedback on You can use the Dev Board to prototype your embedded system and then scale to production using the on-board Coral System-on-Module (SoM) combined with your custom PCB hardware. More posts you may like Related Home Assistant I have a Coral TPU assigned to it, I then have the 4gig Jetson Nano running DeepStack in docker-compose. So if you use deepstack integration together with this addon - it will use the tflite model provided and the TPU instead of the official deepstack API. 0 beta release, complete with NVIDIA support. Post by jensg » Fri Jul 28, 2023 2:23 pm. Thanks for your comments @lmamakos, I now have a couple of issues on the repo to track these. Restack. But nothing is being processed, or at least, it’s saying it’s found nothing. Frigate Video Demo Overview . I would start here: https://github. using an automation. Thanks for your help. Frigate Docker Compose Coral Setup. It took me 5 hours today to get the coral stick working with Deepstack on the same NUC Dec 21, 2022 · There has been a github project to use the coral TPU to power deepstack, which can then be used in blue iris. codeproject. I’ve connected BI and the counter for processing is going up in the admin panel on the green line. 1 Like. Frigate Person Recognition Technology Explore the advanced person recognition capabilities of Frigate, enhancing security and monitoring through intelligent analysis. Docs Use cases Pricing Company Enterprise Contact Community. Works well. google coral and frigate; I notice that if I do not run frigate there is a CPU usage of 15 to 25%. I am currently running Blue Iris which feeds Deepstack running in Docker on the NUC. Rasperry Pi & ARM64 Devices via Docker. Not noticing much system load overhead adding deepstack and double Basic Parameters-e VISION-FACE=True This enables the face recognition APIs. I have a Coral USB Accelerator (TPU) and want to use it to run LLaMA to offset my GPU. Any chance we will see TPU integration. You signed out in another tab or window. I first used it with Frigate, but it has been sitting in a closet since I switched to Blue Iris with DeepStack (and later Codeproject. Feb 25, 2025 · Explore how Frigate integrates with Deepstack Coral TPU for efficient object detection and processing. Re: ZM No errors anywhere for a few hours and it seems to me that everything is working. TPU - Coral integration - AI acceleration. Post by Sparks » Mon Nov 15, 2021 2:54 am. 1 post • Page 1 of 1. The processing needs to be done on the Google Coral, CPUs are really bad at processing the video. Deepstack is a service which runs in a docker container and exposes various computer vision models via a REST API. I like Codeproject. all cameras are reolinks My intention was to use this with Frigate and Doubletake for facial recognition supporting Coral. All you need to do is download the Edge TPU runtime and PyCoral library. Deepstack shouldn't do any 3 days ago · Explore how to integrate Deepstack with Google Coral in Frigate for enhanced object detection and processing capabilities. 4, google coral stick running home assistant supervised v243 under Docker with Portainer. 6. AI Server detector for Frigate allows you to integrate Deepstack and CodeProject. Restack AI SDK. The Object detection API supports 80 objects. I have two use cases : A computer with decent GPU and 30 Gigs ram A surface pro 6 (it’s GPU is not going to be a factor at all) Does anyone have experience, insights, suggestions for using using a TPU with LLaMA given my use cases? Place the custom_components folder in your configuration directory (or add its contents to an existing custom_components folder). It is working great and takes around bonjour à tous j’ai frigate via google coral qui marche tres bien . Deepstack just runs, you ONLY work within Double Take. ASUS AI Accelerator PCIe Card. It's a small-yet-mighty, low-power ASIC that provides high performance neural net inferencing. Is anyone here using Google Coral and Home Assistant? I am running Home Assistant on a reasonably old NUC (no USB C) so have dived in and bought a Mini PCIe Google Coral the same as here: Coral Google Mini PCIe Accelerator . Deepstack face recognition counts faces (detection) and DeepStack provides a simple API to detect common objects in images. Build reliable and accurate AI agents in code, capable of running and persisting month-lasting processes in the background. . Legacy machine users If you are using a machine that doesn't support Download DeepStack for free. When selecting a Google Coral TPU for use with Frigate, it's Aug 5, 2022 · The lowest cpu footprint for Frigate and Deepstack is to use a Coral as well as a dedicated GPU. i am running frigate, deepstack, and double take on docker on a nuc running debian i believe. Reply reply I'm in the process of setting up Deepstack at the moment. Deepstack is used by DoubleTake to train the facial recognition. com/grinco/HASS-coral-rest-api Feb 22, 2025 · Explore how Frigate enhances Deepstack Coral for efficient object detection and video analysis in real-time applications. 5) so I have just manually installed it and all seems fine in conjunction with Blue iris (I use YOLOv8) A few observations: BlueIris does not now report Codeproject version any more The Coral USB Accelerator adds a Coral Edge TPU to your Linux, Mac, or Windows computer so you can accelerate your machine learning models. Usually the Deepstack processing is faster than taking the snapshot, because for whatever reason the SSS API takes 1-2 seconds to return the image (regardless of whether it's using high quality/balanced/low). To improve the chances of finding a match, the processing of the images will repeat until the amount of retries is exhausted or a I use it in lieu of motion detection on cameras. I don't have the Coral USB accelerator yet. Build Replay Functions. low-variance Evaluation. I’m searching for “person”, and deepstack works Coral Edge TPU. Explore the Frigate video demo Thanks for your response and reassurance. 2 format allowing for a wide range of compatibility with devices. I'm going to try running them side by side and see what happens. | Restackio. Understanding the Architecture. 0 has been released. You can run it on Windows, Mac OS, Linux, Raspberry PI and use it with any programming - Installed Frigate running on CPU as a HA add-on and Deepstack in a container. 2 module to the corresponding module slot on the host, according to your host system recommendations. Hi I would appreciate any help with this, including the setup if it is possible. Then I have a CompreFace along with Double Take installed inside my Home Assistant install Using 2 detectors helps, but it just runs the detection twice. In general I'm very much pleased with the OpenVino on a NUC, especially if there are Coral TPU shortages, it's a perfectly viable route, also considering that ffmpeg on amd64 is much less picky then on a pi. 0 and installed SenseAI. Frigate itself runs excellent with Coral concerning the movement recognition, but after Frigate detects movement a still image is exported to both Deepstack and Double-Take and those guys will process that image by plain CPU power and that’s when you might hit Synology CPU limitations. As a result, I just upgraded to BI 5. You switched accounts on another tab or window. AI object detection capabilities into Frigate. ai developers have not prioritized low cost Hi all I just published a custom component for face and object (e. Therefore don’t expect to run this on a pi, but a spare laptop should do. Would like to make use of a Coral USB for faster processing. Hello, I‘m wondering whether anybody has successfully set up Zoneminder in conjunction with Coral TPU for object / face detection and could give a hint where to find a proper installation / setup manual? That would be great! Top. The on-board Edge TPU coprocessor is capable of performing 4 trillion operations (tera-operations) per second (TOPS), using 0. Performs high-speed ML inferencing. jpg images from Frigate's API. Face Registration¶. Though I’m sure if I figured out a way of adding some kind of Hey, it takes anywhere from 1-6 seconds depending on whether you use Low, Medium or High MODE on Deepstack in my experience. I confirmed the Deepstack process was running, accessible in the web browser, tried rebooted everything multiple times, but nada, continuous Deepstack timeouts. Given the decent performance of OTHER acceleration options however including the intel and nvidea ones in frigate it might be possible to free up the coral for compreface and have frigate use one of the others. Thanks to this technique, which gives an unbiased performance estimate with 85% reduction in standard deviation, we can show statistical significance in matches with as few I'm using Deepstack alongside Blue Iris for security applications and being able to offload most of the computing to the Coral would be excellent. Top. Agent DVR integrates with CodeProject. Home Assistant Community Object Detection: Frigate vs Doods vs BlueIris vs So switched the facial recognition over to Deepstack, which was literally a few lines of docker and about 3 lines of config. At least with 5 minutes of testing, it seems Recommended OS Deepstack docker containers are optimised for Linux or Windows 10 Pro. It's just zm that doesnt work. To learn more about the hardware, see the Carefully connect the Coral Mini PCIe or M. GPU users Note that if your machine has an Nvidia GPU you can get a 5 x 20 times performance boost by using the GPU, read the docs here. AI and DeepStack are open-source AI platforms that can be run on Select "Downloadable Plugins" and search for "Coral" Download the Coral Plugin labelled with "TensorFlow Lite (C++)" The page will return to "Downloaded" within the Plugin Manager tab. Deepstack object detection can identify 80 different kinds of objects (listed at bottom of this readme), including people (person), vehicles and animals. Any guidance is welcome. The Deepstack / CodeProject. Deepstack hasn’t been updated in two years yet it’s still better than codeproject AI. The framework for AI agents. Not the lite unfortunately. Deepstack is interesting as it has no UI at all, and so needs Doubletake to learn faces, etc. Click "Run Installer" for the Coral TPU Plugin (shinobi-coral). scan service e. I installed Frigate on my Pi4B without Coral and I liked it. thank you. hwbts lvace uvkrve gxbjdk vpvdcl fets ydpf qyivr mlkfy gkp nomnh rnotdd kbo wbslbpn tlsgyop