Frigate person recognition reddit The solution is to feed frigate a low res stream for object detection, and set the resolution on the cropped snapshots used by compreface as high as possible. But with full respect to the Frigate contributors, the objects that it can recognize or note really useful. Frigate can also do object detection really well and can offload the object detection to a Google Coral TPU. When the frigate/events topic is updated the API begins to process the snapshot. Haven't seen any recent posts re Face Recognition and would appreciate any initial Ive had some okay success with BlueIris and deepstack for recognition. A USB Coral ($59. Restarted frigate and immediately noticed that my detections were much more accurate. Get access to custom models designed specifically for Frigate with Frigate+. The Github page for the Blueprint says that it can be done. Facial recognition takes a ton of pixels however. And I have enabled webrtc as far as I know, Frigate documents are like rabbit hole! 🤣 Do I need to use special card? Like Alex WebRTC card. Any motion captured will have a high res clip recorded by frigate I have a lot of Unifi cameras, only a few of which I have installed. Frigate uses 300x300 models to compare with. Still identifies my large cat as a boat on one specific cam, but I guess thats the angle and Frigate includes the object labels listed below from the Google Coral test data. On the other hand, Reolink, with a similar monetization model, for some reason has a local person detection as an entity in Home Assistant and it works perfectly. Needs some API where people can send public messages /upload video of that car tied to the plate. Badly put together automation for a first try but it’ll be so good. A Coral will free up the cpu cores which means it has more time for decoding. Most CPU's and GPU's have decoders, but passing them to Frigate will depend on the decoder and how you are running Frigate (hopefully docker). Works well. These images Frigate isnt facial recognition. 99) can handle about 10 cameras. Browse privately. But now I have installed 3 cameras and moving to frigate. I have a lifesize statue of a cat on my back porch and, until I excluded an area around it, Frigate was constantly telling me it detected a cat even though the statue didn't move. You can then feed your image into a third party face recognition solution like Double Take, which then feeds back the detected name into Frigate as a sub label. User images and facial recognition data are being sent to the cloud without user consent, and live camera feeds can purportedly be accessed without any authentication. be used with Frigate with an appropriate width/height config or only object detection models? Is it possible to use two models concurrently, e. 13). 8. Is not directly supported/accelerated by Coral, but there are implementations using GPU accelerations. Frigate can save a snapshot image to /media/frigate/clips for each object that is detected named as <camera>-<id>. Please note: car is listed twice because truck has been renamed to car by default. When the container starts it subscribes to Frigate’s MQTT events topic and looks for events that contain a person. I’ve updated the instructions below to reflect the latest version since there were a ton of changes. It is called Frigate and I’m going to demonstrate you how to setup it and how you can integrate it with Home Assistant. For users with Frigate+ enabled, snapshots are accessible in the UI in the Frigate+ pane to allow for quick submission to the Frigate+ service. Many thanks We would like to show you a description here but the site won’t allow us. Frigate can't yet handle retention based on available disk space. Imagine no more as there is one. Question, has anyone had success using Frigate detection to automate a light? I have an outdoor floodlight connected to a smart switch and wanted to use a frigate based camera feed and person occupancy to set things off. The web UI is awesome. I am using high fps on front facing cameras because frigate uses snapshots from that stream and everything is blurry e. I meant detecting 'cars' in my cameras. video/plus/ No, just one coral for frigate. For my use cases a 1920x1080 often is enough but if you want to get into person recognition from a distance I’d look into 4K camera’s. 7 mask: 0,0,1000,0,1000,200,0,200 Also as an aside, you've set max_frames which is HIGHLY discouraged as it forcefully breaks frigate stationary object tracking and leads to undesired Thanks for chipping in u/nickm_27. I've almost got more person object masks then Originally my plan was to follow Everything Smart Home's videos on setting up Frigate, then Deepstack then Double Take. However, birds set it off. Try and experience A lightweight nextcloud alternative r/selfhosted • • Imagine no more as there is one. Because I don't, I use the Frigate live view card (from Frigate integration), and set the provider to "go2rtc". Park. Has anyone had any luck with any integration relating to number plate recognition. If you want to build something yourself, grab an AI accelerator like the Google Coral USB or M. Firewalla is dedicated to making accessible cybersecurity solutions that are simple, affordable, and powerful. Double-Take will take events from frigate and do faces, I just set it up over the weekend and am training faces, since its new, and Im not a great programme rI havent figured out any great automations yet, but Im well on my way. Reolink + frigate (nvr) + deep stack (object retention / license plate) + double take (facial recognition). Yours is a ton more efficient. This month, with the release of the GPT-4 Vision API, I was able to take my experimentation to the next level to allow a higher level of contextual understanding. mqtt: host: xxxxxxx port: xxxx user: xxxxxx password: xxxxxx # topics for mqtt topics: frigate: frigate/events homeassistant: homeassistant matches: double-take/matches cameras: double-take/cameras # global detect settings (default: shown below) detect: match: # save match images save: true # include base64 encoded string in api results and Frigate - motion/object detection only, Coral accelerated. Nick, thank you for such detailed information. 0 has been released. A single Coral outperforms most CPUs. Any of these turn on the outside light. No facial recognition stuff, I dont believe in that and wouldnt want someone being able to enter my house by holding up a picture of me. Just object/person detection, but DoubleTake provides a nice, friendly interface layer between frigate and a few different face recognition tools. Thanks! I'm currently using frigate. Jul 23, 2024 · recognize: # minimum face size to be recognized (pixels) min_face_size: 1000 # threshold for face recognition confidence recognition_threshold: 0. But I can't even count how many times a tree has been detected as a person, or a cat as a bicycle. We would like to show you a description here but the site won’t allow us. Technically you can run double-take without frigate, but passing along camera configs is a lot easier with frigate. Doorbell/Peephole camera detects movement > images are sent to Amazon Rekognition for person detection (loop of 4 until person is recognized, one per second or so) Doorbell is pressed I don't want Deep stack/Frigate running just for this, much less on a slow mini PC or a Pi All runs smooth and fast for automated and rather powerful person detection on 5 cameras 24/7, running on a 10-years old macbook-pro for an all-in-one security system with home assistant on top. So, all of my automations and integrations are done through Frigate. What is really important for me is the object detection. It needs an image of at least 250x250px to reliably recognize a face. Frigate is superior for object detection and effortlessly integrates with HA. And double take will only search frigate detected person snapshots for faces. One Coral USB accelerator can do real time object recognition on 6 to 7 cameras at once, so it's pretty powerful. I also have a couple of cameras, and I also have Frigate for person recognition. jpg for facial recognition snapshot: 5 Frigate, downloader integration, google generative ai integration. (Person/car/dog). I'd recommend you to use compreface instead of deepstack, as its not maintained. I'm running Frigate on an NUC i5 and like 10-15 more containers without Coral and I really can't complain. But a moving person at a distance would be easier for Frigate to detect than a non-moving person at a distance. They are also accessible via the api. Is this the correct usage or does it need to save the area numbers within GUI as well? This is what I have for my camera under its Objects portion of the yaml code: ``` objects: track: person bear dog cat filters: person: Frigate on the other hand was designed specifically to do object detection on CCTV feeds and setting it up was pretty simple (you do have to manually write a config file unlike Shinobi but pretty much everything you need to know for that is explained in the docs and it's really easy). These images # frigate settings (default: shown below) frigate: url: # if double take should send matches back to frigate as a sub label # NOTE: requires frigate 0. In my case, I chose compreface and it used barely any resources. Yes, the video is quite laggy. My frigate is often 70-71% certain it recognises a person walking around in my birdhouse. USPS delivered a package and I can see the truck approach right in front of my house. Deepstream - object detection, face recognition. Effectively it is using Frigate to do the person detection using a Coral, once it identifies a person we take 3 snapshots of the camera spaced 1 second apart and save them as 3 individual files. As you can imagine, having a GPU does help with facial recognition though. 2 Accelerator B/M (G650-04686-01) does it mean that the facial recognition will have more accurate results? Frigate is excellent, within the bounds of what it does. For object recognition, whether it's Deepstack or Code Project AI, the real determining factor is which object models you are using. Etc. It was now detecting people with a 95 to 99% probability. If i would be able to set that confidence treshold to 75% it would save me a lot of weong tags without need for another model. Reply reply. Plugged the model designation into my frigate. As we’ll be using gpu offloading we’ll install Frigate in a seperate docker instead of running it as the HAOS add-on. I'm using frigate with Deepstack and Double Take and it works great. You will need one for each of your cameras and this one starts up if no one's home. It only detects 'human' once the car has stopped and the person gets out. Mar 17, 2021 · Double Take is a proxy between Frigate and any of the facial detection projects listed above. I've used wyze, the Samsung cam, and blink in the past. When the container starts it subscribes to Frigate's MQTT events topic and looks for events that contain a person. When double take had enough pixels to work with, it works well and updates the frigate event with the name of the person detected. Everything can run inside HA supervised as add-ons. You can get double take itself up and running in like 10 minutes. I've found the snapshot. family members) or a stranger. I worry that a lot of people read the Frigate documentation and come away thinking that Reolink cameras requ I am trying to use the Double Take facial recognition with the Frigate Notifications (SgtBatten/HA_blueprints), but not able to get it working. The dev just put up brand new docs for the v8 release - best tip is to start with the super simple config file and build up from there. Frigate doesn't do individual face recognition, but rather object recognition (cat, person, fish etc. Apr 23, 2025 · The integration of frigate person recognition allows for more precise tracking and monitoring of individuals, making it an invaluable tool for security and surveillance applications. If your object is smaller, it'll be harder to compare. A sensor is being generated, recognizing my face. The motion eye is very clever. So you would then configure Scrypted to pull the RTSP stream from Frigate rather than directly from the camera. 2 and roll your own around the Frigate NVR. You can use a minimum of 10 images, but they recommend 100 images per camera. Reply reply Plugged the model designation into my frigate. With everything set up correctly, six camera streams of 1080p might see about 5-8% CPU usage. This aids in secondary processing such as facial and license plate recognition for person and car objects. I believe UI only says Pet/Person as well (Only based off my unifi doorbell), so if you wanted more granular AI recognition, Frigate. For cars, the snapshot with the largest visible license plate will be selected. I get only working where it says person detected, but not michael is detected for example i also use compreface with frigate and double take and a google coral I use both reolink cameras for security and frigate for person detection automations (lights). I was planning to use the new device also for 4K transcoding for PLEX, so I've found that the new Intel N100 works wonders for this purpose. I tried BlueIris a few months ago and if i remember right it needed waaaay more resources than Frigate. But don't really know how the cameras might be used in conjunction with alarms? Edit: I have frigate. The Coral only does the recognition, not the decoding. Pixels are the key however. My aim is to keep a log of plate numbers and use this to call out new ones. Our smart firewalls enable you to shield your business, manage kids' and employees' online activity, safely access the Internet while traveling, securely work from home, and more. The config made some significant breaking changes. I'm already building home automations on top of frigate & nodered (using mqtt) and it works flawlessly! Kudos to frigate for such a great project! Now wanting to expand to automations based on Face Recognition and wondering what's the best path to take. Never more than that. jpg images from Frigate's API. Here is an automation I am using: automation: - alias: Turn on the outside lights when a person is detected at night trigger: platform: numeric_state entity_id: sensor. Double take isn't accurate or is, it's just an interface between frigate and face recognition software. I was able to setup Frigate but when I went to install Deepstack, their github does not look like it has been updated in 2 years. jpg images from Frigate’s API. probably because it's on CPU right now wihle I wait for Coral cards to be available. Brave is on a mission to fix the web by giving users a safer, faster and more private browsing experience, while supporting content creators through a new attention-based rewards ecosystem. This is yaml for one of my cameras. You'll need something like Deepstack for face recognition. A rest sensor is set up for each camera. The camera is facing the door which is fully glassed window door so contrast wise no the best. I was thinking that I would be using that unit also for processing and the NAS connected via USB 3. Frigate does object detection only. Is Deepstack still being maintained. I have this stack running on unRaid with a Home Assistant and the detection is incredible. You can then trigger automations based on recognized faces and such. but the system does not detect 'car'. But for anyone wondering how accurate frigate is in general, and in particular for people/cars, yesterday I had some landscapers do some work around my house, with my 4 cameras running all day it triggered over 800 detections for people and cars. If you haven't seen the Frigate+ docs, check them out: https://docs. You will be able to fine tune your model with the images you have uploaded and annotated up to 12 times with your annual subscription. I moved from in-camera detection (HikVision) to Frigate and it eliminated 95% of false positives from things like birds, trees etc. An automation for each camera fires on motion detection in Frigate. Is there a way to "ungroup" facial recognition groups in QuMagie so that I can correct the wrong tags without changing the ones that are correct? It's almost like I need an "unlink" these people option. The people that walking in pass the door therefore they re not walking that fast. ). Using a Frigate+ model with Frigate will detect face as a "sub label" of person. I am also not sure if many here are following the deve Do you have a working automation for notifications? I tried the blueprints but I can't get it to work where it says the name which match the face like. Off the shelf you have the Google Nest cameras which will do face recognition well. Now with frigate after playing quite sometimes. backyard_person_score above: 20 condition: condition: or conditions: - condition: time after: '22:00:00' - condition: sun before: sunrise action: - service: scene You are wrong. I made Frigate run on my Synology 920, running both MQTT and Frigate in Docker and three camera's connected through RTSP. You can have Frigate as a Docker container or as Home Assistant add-on. It runs very well on a Raspberry Pi - see the docs - and with the additional of a USB Google Coral adapter (if you can get your hands on one) it will run all the object / person detection with absolutely no issues. I use blue iris when I want to look at footage. Have the object detection publish to MQTT then setup BI to record based on MQTT. The model you are using is the normal frigate model which does not have licence plate recognition. However, you should be utilizing the dedicated decoder from your CPU/GPU to decode the streams. After trying out the new facial recognition feature, seeing it only works on the expensive AI cameras, and doesn't work that well at all (captures a small percentage of faces), I'm considering dumping Protect for something better. Looking at the feature list, iSpy seems to be much more powerful in this regard and even offers face recognition. This is using the default prompt which can be hugely improved to suit my camera. I really love Frigate combined with it's Home Assistant capabilities. You'd need to use an add-on solution to do specific face recognition, but also be aware that camera placement can make this tough - cameras at roof height are unlikely to get enough detail (especially at night) for reliable, specific face We would like to show you a description here but the site won’t allow us. If you want facial recognition you can try deepstack and double take to process images after Frigate has detected a person. In my setup frigate night person recognition is poor (I'm use frigate 0. As you see in one of the attached images, in one with a guy and a dog, the dog is being recognized as a person 😄 Is there a way to improve person recognition other than increasing the threshold? Dec 29, 2022 · I am using Frigate on my HA alongside Deepstack/Compreface and DoubleTake. Frigate is an open source NVR built around real-time AI object detection. " Replace {{label}} in title and message of the notification with a persons name if double-take face match is detected. The payload is a call to DOODS2 referencing the debug feed of that camera in Frigate. I've minimized it through playing with the settings but as accuracy increases, the amount of missed events goes up with it. If you need more cameras, Frigate supports multiple Corals. It just happened again today. Just to try Frigate I set one camera, just recording clips on person detection on a Pi4 and the CPU use went up to about 80% most of the time. latest: 5 # number of times double take will request a frigate snapshot. Can’t give you the finer details but it’s possible this way. In summary, Frigate's video pipeline is a well-structured process that efficiently combines motion detection and object recognition to provide a comprehensive Posted by u/MrAnachronist - 1 vote and 3 comments the detection detects objects, not number plates and recognition works at low resolution and low frame rate, typically one uses one of the substreams - but depends on perf. If it detects my phone entering the home zone AND a person walking up to my door within a minute or so, it unlocks the door (and notifies me of that). Mine is still doing its thing for over 10 years. mqtt: host: *** port: *** user: Does Frigate have plate recognition on its roadmap? License plate is already supported for frigate+ models (which are slated to come out with 0. Hi 👋! After switching from Nest to Frigate and HA, I tried to replicate the package delivery notification functionality of the older camera system. Much like Vampires can't be seen in mirrors, Cats can't be detected by image recognition due to their phase shifting ability. So my question is: should I use DeepStack or CompreFace? My setup is one 1080p camera, 6th gen i7, and GTX 960m. I have a decent camera with frigate which will create a snap shot including the plate which is usually very clear. A decoder will help with the video intake. @blakeblackshear @NickM-27 I am not sure if Frigate has had any consideration into implementing facial recognition into the NVR itself or not. I do all this without a coral but I have a really nice server. See the full configuration reference for an example of expanding the list of tracked objects We would like to show you a description here but the site won’t allow us. 5 threshold: 0. 8 # time (in seconds) to wait before recognizing the same person again match_timeout: 60 # time (in seconds) to wait before re-identifying a person reidentification_interval: 60 # scale factor for the I think doods and frigate use the same tensor flow models for object recognition? Frigate does add some logic for motion, but I wouldnt expect it to be miles better than doods. If it's moving, a higher percentage of the pixels will be blurry, if that makes sense. You would also probably benefit from using a decoder. On the two outside cameras in areas where a person would be detected it like 71 or 73% probability. It forces the related rest sensor to update, so the call is made to DOODS2, scanning a single frame from that camera. But there again, the statue was fairly close to the I've been testing Frigate+Doubletake for facial recognition on people. There is a workaround where you fire off an automation in the Tapo app that triggers another TP-Link device, like a plug, which in turns triggers a notification. I’ll to. I am hoping to create an automation that checks if it’s me at the front door camera. Frigate is an NVR (network video recorder) that uses AI, specically tensorflow lite models, to track objects (people, cars, dogs, cats, etc) and alert you in a myriad of customizable ways when something "interesting" happens (person comes up to your door, for example). After some research, I've found that people commonly use either DeepStack or CompreFace for face recognition. Frigate is able to use a much lower resolution because detection something large like a person doesn’t require many pixels. Frigate+ has a face label so faces can be tracked and more accurately sent to face recognition services instead of guessing that a person is facing the camera, but there have been no plans discussed for Frigate+ / Frigate to host / maintain facial recognition itself. jpg and latest. # object labels that are allowed for facial recognition. When a Frigate event is received the API begins to process the snapshot. jpg for facial recognition. Frigate also uses MQTT to talk to HomeAssistant so it can trigger Double Take is a proxy between Frigate and any of the facial detection projects listed above. If I buy a Coral AI Google Mini PCIe M. Now if you are just detecting 'car' as an example get a camera with one high resolution main stream (to take pictures) and one substream that meets the recognition guidelines. I’d always recommend Axis ip camera’s, although expensive, in my experience they are very reliable and last long. Blue iris is a superior nvr. jpg image from Frigate produces better results and you can also crop it in real time with query parameters as long as that Frigate event is still in progress. Moore says some of the issues have since been patched but cannot verify that cloud data is being properly deleted. Now I'm using Frigate (docker) working with HA to do object detection and automation (Text-to-speech that car is coming down driveway, etc). It'll obviously depend on your cameras' resolution though. Reply reply SeraphTM Facial recognition is used to determine if a face is a known person it is trained on (e. These images are passed from the API to the configured detector(s) until a match is found that meets the configured requirements. I just can t seem to get this right, the picture background is sharp but the person moving is really blurry. yml file. Frigate is using OpenCV and Tensorflow to perform realtime object detection for your IP cameras locally. That being said, here's one of the automations I use for the Frigate object detection and BI recording, just to get you started alias: Frigate Person Trigger BI Record BP - Zones description: Use Frigate person detector to trigger camera recording in BlueIris trigger: - platform: state entity_id: - binary_sensor. The main attractions is it's object / person detection but this can be easily disabled in the config. So if home zone value is zero. Dogs have been detected as persons, and the percentage is not that different (person is always around 84% while the dogs as persons 81/82%). So, what's good about BI, is that it could recognize a "bird" vs a "pet". When I create an object mask in Frigate (Add to Person) I copy it and place it in my frigate. My plan was to use: Triggered by person detection Verify the person is me (use additional security features like: Car is home, Cell Phone is home, etc…) The issue I am running with Aug 30, 2023 · Indeed no event was created, even though it seems that for an instant it realizes that I was a "person" Because it did not score high enough. labels: - person - mike. These object types are frequently confused. I still have a github issue opened on it. 0 beta release, complete with NVIDIA support. I need to install my Google Coral TPU since it eats my i5-11600 up like crazy when processing objects. The training data is, I believe, based largely on generic images rather than CCTV images, so it's not so precise at differentiating between the subtleties of Now, Frigate did add some new features, like requiring motion to happen before recognizing a person to help with false positives, but I still found the higher quality models to be near bulletproof in recognition, and I chose to go that route and am still very happy with DOODS. In my setup, I would just setup an automation in homeassistant. frigate docs include some hints to make ffmpeg work with some non standard camera's, could be worth a try: Frigate saves from the stream with the record role in 10 second segments. I cant seem to find an option in frigate to set a confidence treshold. Je cherche à commencer à jouer avec la reconnaissance faciale et je me demandais si double-take est ce que je devrais… Aug 30, 2023 · Indeed no event was created, even though it seems that for an instant it realizes that I was a "person" Frigate config file. Search privately. jpg for facial recognition latest: 5 # number of times double take will request a frigate snapshot. With a better PC (I used a mini Ryzen 4500, no need at all going so “high” spec), I run 4 cameras, recording 24/7 with audio and recording clips on person detection, and it works great. Deepstack shouldn't do any recognition until after person detection from the Coral. If Frigate can call a url you can do it that way also but IDK if frigate can as I never played with that part. snapshot: 0 # process frigate images from frigate/+/person We would like to show you a description here but the site won’t allow us. You need to pay the subscription and train a model using your images to get licence plate objects, same with packages. Double-take and Frigate - Frigate passes the scanned faces to a locally installed copy of double-take and compares against the training pictures you've fed it. I have an O/C sensor on my front and a motion sensor outside the front door. Since all my cameras now have their on-board AI, I use the pet and person triggers for events. I use frigate in combination with my phone. You probably want some sort of separate NVR so that you have a 24/7 recording as you never know when that will be useful. yaml and edited my minimum and threshold for objects. Or use a tensor processing unit($25 to $50) and a software like frigate to throw frames at the tpu and recognize people, plates, objects. At some point I’ll write another version of this that incorporates the May 22, 2024 · Hello, Thought I would share my node-red config if anyone is looking to setup the Google Generative AI with Frigate and notifications to Google home and phones. You can also view thd Frigate camera but the framerate is low so better to just go to the source. # NEED TO REMOVE THE MASKS objects: track: - person mask: 0,0,1000,0,1000,200,0,200 filters: person: min_area: 5000 max_area: 100000 min_score: 0. I'm setting up the holy trinity of smart home security consisting of HASS + Frigate + u/Jakowenko's Double Take. back_lawn_person_occupancy Now I need frigate in my car with a roadcam. 0+ update_sub_labels: false # stop the processing loop if a match is found # if set to false all image attempts will be processed before determining the best match stop_on_match: true # ignore I have never used Frigate, but the main difference that i can see is that Viseron has support for different kinds of detectors, and some better hardware acceleration (CUDA, Jetson Nano etc) Also has built in Face recognition and some other computer vision implementations Apr 6, 2023 · I am really struggling with false detections, I have fine tuned min area sizes, confidence level percentages etc, but sadly there is no combination that works without a load of false positives (mainly at night), which I think is fair in saying is one of the main reasons many of us turned to Frigate. 11 which is not the latest version) night motion sensing is a bit better. 11+ option to include names in frigate events labels: - person stop_on_match: false attempts: # number of times double take will request a frigate latest. everything "works" but I definitely having issues with frigate unable to keep up with the camera feed. Still works great! EDIT 12-15-2020: I just noticed that Frigate has a 0. Let's say you have Frigate configured so that your doorbell camera would retain the last 2 days of continuous recording. I certainly defer to your greater experience on this topic. Unfortunately, the default model was not trained on relevant camera images including images of people from the top down. We then send those 3 files to Google AI From my understanding the object recognition models used by Frigate are Alpha/Beta and they work OK. 11. frigate. I can definitely recommend reolink for use as a security camera, the AI person detection has been just about perfect for me, and the on camera AI chip is almost instantaneous. g. I was into running the object recognition on a live stream using a python script and tensorflow. person is the only tracked object by default. I really just wanted the community to know that there are reliable Reolink options out there that can work with a very simple configuration. g blurred face, person. From there install the addon in ha and you can turn detection on / off for the cams you setup. yeah it doesnt do too well with pets/animals. update_sub_labels: true # frigate 0. Feb 12, 2024 · I don’t think this would do face recognition, the frigate codeproject ai detector uses /v1/vision/detection but the api to do face recognition in code project ai is /v1/vision/face/recognize 22 votes, 16 comments. Works either after the object detection output by Frigate, or on its own. I’m running HA as a VM on Proxmox, on a Ryzen 5 mini PC, I use Frigate with 3 rtsp cameras, recording 24/7 with audio, triggering events on person recognition with no hardware acceleration and the CPU hardly ever goes beyond 20%, usually much lower. I think that in the future as Frigate develops further it could become much more suitable to how I like to have my cameras interface with me, but at present I would So I've used Deepstack (now CodeProject. jpg. These images are There's an addon called Double Take that seamlessly integrates mqtt, Frigate and face recognition engine. ai) before with Blue Iris for object recognition. The best privacy online. ALPR is separate but can be done with code project ai once frigate (or whatever) detects a license plate Admittedly I am running Frigate on a Debian 11 machine which is not my usual OS so perhaps my difficulties with getting Frigate to run could be due to my not being a Linux person. Reply reply WWGHIAFTC The lowest cpu footprint for Frigate and Deepstack is to use a Coral as well as a dedicated GPU. All processing is performed locally on your own hardware, and your camera feeds never leave your home. Dec 13, 2020 · EDIT 01-27-2020: Frigate 0. That allows you to have a smaller image when passing it to CompreFace/Facebox which will produce quicker responses. Can you elaborate on what and how you are running frigate? Imo the motion/object detection with zones and masks and all that would be the hardest part which is what frigate with a coral works best at. When using Frigate+ models, Frigate will choose the snapshot of a person object that has the largest visible face. Also you have doubletake which is by yakowlenko, not maintained as well (it's dead). I don't have an nvr set up outside of that, just have my cameras back up a low res stream 24/7 via ftp to be all inclusive. , the built-on COCO model plus another? If all really want to do is to detect both people as with the COCO model and squirrels ;-) as with the MobileNet V2 (iNat birds), what is the simplest way to go With Frigate+, you get a model fine tuned to your cameras for improved accuracy in your specific conditions. attempts: # number of times double take will request a frigate latest. These options determine which recording segments are kept for continuous recording (but can also affect tracked objects). It would be cool to be able to set alarms based on Frigate person detection and time of day. My plan (may it gives you idea) is to run home automation scenes with face and object recognition - laptop + me in sun patio -> close shutters, my wife with a book turn on this I have a similar setup. Looking for recommendations. Frigate is spot on with every single car type with the exception of USPS. 2 to the device for storing the recordings The Coral will greatly increase your image recognition capabilities. Posted by u/Cvalin21 - No votes and 21 comments I'd be interested in how you might use that. Jul 22, 2024 · This article decribes setting up Frigate with Double Take and Compreface for facial recognition. It ran for a few days but the pattern (person) recognition of Frigate takes too high load on the CPU to leave room for other Docker instances like Home Assistant and Plex so I decided against it. rwp dtuqbk uxahfick bwhhda aevzr toep iijlhg aaduf uzts thnytz