Frigate person recognition reddit I'm running Frigate on an NUC i5 and like 10-15 more containers without Coral and I really can't complain. Indeed no event was created, even though it seems that I have a camera mounted above a path and it doesn't really detect a person. I have the Frigate Home Assistant Integration configured which exposes person detection (binary_sensor) and person count (sensor) — both work well. You can have Frigate as a Docker container or as Home Assistant add-on. When I go into HA under "Down Main Person Motion" binary sensor, I get a rapid-fire of 9 "person detection" events in about 15 seconds - they all fire and clear after 1-2 seconds. Frigate is superior for object detection and effortlessly integrates with HA. A sensor is being generated, recognizing my face. 293K subscribers in the homeassistant community. HA and doubletake run on another ARM sbc along with You're not using minimum score or threshold either that I can see. Frigate is using OpenCV and Tensorflow to perform realtime object detection for your IP cameras locally. Frigate’s documentation specifically doesn’t recommend using a VM if you intend to use Coral TPU because it’s so hit or miss getting Working great so far, training takes no time at all on jetson. 8 # threshold for face recognition confidence match_timeout: 60 # time (in seconds) to wait before recognizing the same person again reidentification_interval: 60 # time (in seconds) to wait before re-identifying a person There's an addon called Double Take that seamlessly integrates mqtt, Frigate and face recognition engine. When the container starts it subscribes to Frigate’s MQTT events topic and looks for events that contain a person. 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 animals. I moved from in-camera detection (HikVision) to Frigate and it eliminated 95% of false positives from things like birds, trees etc. Although a passive IR detector can detect a person that is moving, once they settle down the IR sensor will no longer "see" them because it is triggered by a change in temperature; the person does continues to radiate IR energy when they're not moving but it is not changing. My frigate is often 70-71% certain it recognises a person walking around in my birdhouse. Frigate can't yet handle retention based on available disk space. The unofficial but officially recognized Reddit community discussing the latest LinusTechTips, In Frigate itself I counted 18 events in the span of 10 minutes ranging from ~45 seconds to 3 minutes - nothing out of the ordinary. Powered by I made Frigate run on my Synology 920, running both MQTT and Frigate in Docker and three camera's connected through RTSP. It is cool though. After adding the new cameras, the "Person" camera is "Idle" and the "Person Occupancy Detected" isn't updating. If your object is smaller, it'll be harder to compare. For frigate the person detection stays set even if there is no motion, hence the reason for using frigate for lights. It does object detection. 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 Viseron is a self-hosted NVR deployed via Docker, which utilizes machine learning to detect objects and start recordings. She is black and white and I think the pattern somehow is causing the mis-cat-egorization. Orange box = Object detected, green box = Trying to detect what the object is - I’m guessing you’re seeing green boxes around people? Can you paste your config file into something like pastebin (removing any passwords!)? I’m wondering whether you’ve changed the default behaviour by accident (by default Frigate only detects people) objects: track: - person filters: person: # Optional: minimum decimal percentage for tracked object's computed score to be considered a true positive (default: shown below) threshold: 0. One in particular 90% of the time is detected as a person. Frigate in this method is doing the work of detecting if person is present, then it's just coordinating those camera images with the facial detectors to find a face and output the results. snapshot: 0 # process frigate images from frigate/+/person So if someone walks into an area it triggers, then if that person stays motionless it clears. Will even tell me the colors of someone's pants and shirt. It is called Frigate and I’m going to demonstrate you how to setup it and how you can integrate it with Home Assistant. It actually doesn't rely on motion at all, we have renamed this in the next major update (currently in beta) to be presence sensor so it is more clear. In my case, I chose compreface and it used barely any resources. It’s a quick ON or OFF. You can then trigger automations based on recognized faces and such. I really love Frigate combined with it's Home Assistant capabilities. it's got a nice clean field to work with to find a person so go back to the documentation and look at minimum score and threshold Plugged the model designation into my frigate. On the two outside cameras in areas where a person would be detected it like 71 or 73% probability. If you don't use Frigate, but had a motion sensor and a live updating jpg image from Home Assistant or another source, you could pass this URL to `/recognize` endpoint and increase the amount of So I've used Deepstack (now CodeProject. With that said you can run double-take along side frigate for facial recognition. Its not in the event either. Home Assistant is open source home automation that puts local control and privacy first. However, I'm also looking for a generic motion detector binary_sensor that triggers on motion, despite an object being discovered or not. If it's moving, a higher percentage of the pixels will be blurry, if that makes sense. latest: 5 # number of times double take will request a frigate snapshot. This camera is like $1200 US. attempts: # number of times double take will request a frigate latest. Is there a way to improve person recognition other than increasing the threshold? There are filters that could be used, like a min_area filter for person. It recognizes it and has a box around it but it won't record it or notify me. Maybe I mischaracterized my setup, it’s Frigate running in Docker on Ubuntu, and the Ubuntu is on bare metal. yaml and edited my minimum and threshold for objects. . 😸 Using the frigate hass integration you can use the "person motion sensor". I have found that a passive IR temperature sensor can be used to Would a next level of detection be object actions? Such as person standing, person walking, person running. I'm kinda in the industry and have one such Hanwha camera on my desk for person detection right now. I'm looking for some tips to improve person detection I always thought I had everything set up for the best, until last night I realized I wasn't detected by frigate. I also have issues with my cats. The ease of adding face detection is because of the addon double take which works together very seamlessly with frigate. It also reads messages sent by Frigate to MQTT when a detection occurs, grabs the snapshot, sends it to Deepstack and pushes to result back to Frigate as custom recognition (Face or whatever). I see one is Doesn't really apply to Frigate, though. Never more than that. Frigate absolutely nailing the object detection and confusing the hell out of me my dog gets identified as a person when the camera sees him head on. I am also not sure if many here are following the development of the Immich photo & video self Basically a friendly web UI for you to feed data and train Deepstack for your face recognition or other custom models. It needs an image of at least Frigate doesn't do facial recognition. Maybe a generic 4-legged object? I added a bunch of cameras, but also left some old ones in place. When a Frigate event is received the API begins to process the snapshot. # object labels that are allowed for facial recognition. Or car stopping, car stopped, car begins moving, car moving. I am hoping to create an automation that MQTT Frigate Person: This subscribes to the wildcard MQTT topic frigate/+/person to monitor for person events on all of your cameras. I use blue iris when I want to look at footage. Also, for just $5/mo, you can add Frigate+ service, where you train it on images from your actual camera feeds to be able to detect objects/people/etc (again feeding into HASS). 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. Everything can run inside HA supervised as add-ons. Also, a generic animal object would be great as I've got dogs, cats, possums, coyotes, raccoons and other assorted critters. 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. But with full respect to the Frigate contributors, the objects that it can recognize or note really useful. 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. In general though, the best way to get When double take had enough pixels to work with, it works well and updates the frigate event with the name of the person detected. Zone name in frigate is all upper case, but during troubleshooting I've noticed the payload had the name from frigate via mqtt in all low. I tried resetting Frigate, HA and the Frigate Integration but it won't update. I cant seem to find an option in frigate to set a confidence treshold. It was now detecting people with a 95 to 99% probability. Pixels are the key however. @blakeblackshear @NickM-27 I am not sure if Frigate has had any consideration into implementing facial recognition into the NVR itself or not. I would add a min_score of . For me this works for security purposes. Fortunately frigate does sometimes detect my cat even when it frames per second, so even if in one frame it doesnt recognize a human shape or thinks the shape could possibly be a bird, within less than a second it will be correctly I believe many people successfully run it with good results using a Google Frigate is excellent, within the bounds of what it does. Frigate and deepstack run on jetson + coral, as jetson has a hardware video decoder for frigate, and gpu for deepstack. I still have a github issue opened on it. jpg for facial recognition. jpg and latest. I'm not an expert here but at the bare minimum coax isn't future proof. ON: It looks for anything >0 which means a person was detected. Any idea what could be causing this? Here is a sample of the camera config: Imagine no more as there is one. Double-Take was developed alongside Frigate to watch for person detection. So, all of my automations and integrations are done through Frigate. It works with deepstack, compreface, facebox, I am using Frigate on my HA alongside Deepstack/Compreface and DoubleTake. If you do some digging on Linus Tech Tips videos, he has a video that kind of glances over the whys and hows. 75 and a threshold of . Unfortunately, you have to have the detection notifications inside MQTT from Frigate for Double-Take to watch for facial recognition. ai) before with Blue Iris for object recognition. I started working on this when I got tired of my Arlo cameras always giving false positives or not recording at all. I did not double check it as it took me few days of fighting after upgrade and I need some recovery time before I look at frigate again Double Take is a proxy between Frigate and any of the facial detection projects listed above. 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). I tried BlueIris a few months ago and if i remember right it needed waaaay more resources than Frigate. Frigate uses 300x300 models to compare with. 7 # Optional: mask to prevent this object type from being detected in certain areas (default: no mask) # Checks based on the bottom center of the bounding box /r/StableDiffusion is back open after the protest of Reddit killing open API access, which will bankrupt app developers, hamper moderation, and exclude blind users from the site. 8 That camera has a limited area that it needs to monitor there's not a lot of sort of crap around it for lack of a better term at the moment. Restarted frigate and immediately noticed that my detections were much more accurate. labels: - person - mike. It automatically pulls events, looks for a person, looks for recognize: min_face_size: 1000 # minimum face size to be recognized (pixels) recognition_threshold: 0. jpg images from Frigate’s. If i would be able to set that confidence treshold to 75% it would save me a Blue iris is a superior nvr. Yes but they're not really in the price range for home use. It'll obviously depend on your cameras' resolution though. The recording and detection switches also operate as expected. kczb xbih eanfrdx obfhynt qgygsl txf kzmnhq fkcl zufje anwudzajb