Compreface frigate reddit I'm I have frigate up and running extremely well, detections are mostly accurate. I’ve got Doubletake, Compreface and Frigate all humming now. Or check it out in the app stores   Is the N100 good for Frigate using Deep stack and other facial/object recognition services? I have an optiplex with an i7 8th Gen that does pretty well with frigate, compreface & deepstack but I'm also interested in the energy Go to frigate_nvr r/frigate_nvr • by Cvalin21. 0 release to give Then I have a Debian VM that hosts Home assistant Supervised. Facial recognition is only as good as the training data provided. Also have Coral USB used Frigate uses FFMPEG and then you can offload the image processing with a coral edge tpu. Sorry to dig up an old thread but what does your CodeProject. Why? From my testing at home I’ve found CompreFace and DeepStack to produce the best results, but I’ve also added support for Facebox. I could use Coral or QuickSync, but which uses the more accurate model for detection? (Deepstack) vs CompreFace. I also worked on a feature that is in the frigate 0. cameras: - FrontDoor1 - GarageDoor1 - MasterBedroom1 - Driveway1 Frigate doesn't do facial recognition. Come and join us today! CompreFace: Free and open-source face I tested frigate in a virtual box VM and got it working. It took a couple tweaks of the config files for Doubletake and Frigate, and also required spinning up a new face recognition service for Compreface (the demo is trained on celebrities forsome reason?). Welcome to reddit's home for discussion of the Canon EF, EF-S, EF-M, and RF Mount interchangeable lens DSLR and Mirrorless cameras, and occasionally their point Je mets en place la Sainte Trinité de la sécurité de la maison intelligente composée de Hass + Frigate + U_Jakowenko Double Take. It was now detecting people with a 95 to 99% probability. 11 beta which lets double-take send the face info back to frigate so Im running something similar. Best setting in I’ve got compreface running but when I feed it snapshot images from my 4K cctv camera it doesn’t detect a face. View community ranking In the Top 20% of largest communities on Reddit. Internet Culture (Viral) Amazing It may be "overkill" if just using it for frigate, I use my GPU for CompreFace Face detection and that model alone is 4GB in RAM so 8GB is perfect for my usage You need to use my container for these flows to work. Updated to the second beta of 0. Frigate (w/USB Coral) - 1 x 1080P camera, 3 x 4MP, 1 x 8MP and eventually a panoramic camera, either 4 or 8MP, so potentially another 2x 8MP at most. HA Supervised has frigate integrated (as Docker). image: # height of frigate image passed for facial recognition. Frigate is excellent, within the bounds of what it does. Currently untest from what the post said, but still wanted to share here. Case: Fractal Define R5 Get app Get the Reddit app Log In Log in to Reddit. Après quelques recherches, j'ai constaté que les gens utilisent couramment Deepstack ou Compreface pour la reconnaissance faciale. Heres what I had to do Boot the vm using the unichip corp vendor and product id (1a6e:089a) Start Frigate and wait for it to fail to detect the tpu Check the vm settings and see if has changed from unichip corp to Google Inc (18d1:9302). I have 6 cores attributed to HA VM, 6 cores and 4GB RAM to Frigate, and 6 cores and 8Gb RAM to Compreface. Initially I had 2 people trained with about 10 pics each. frigate. I am very happy I built myself as when I need to upgrade or my requirements change I don't need to buy a whole new system. Also added "training" images of faces I want to identify. Double Take Compreface Some kind of number plate (ANPR) recognition A simple file server, such as OMV Possibly Ubuntu/Mint etc to practise my Linux skills Box area too low in Double Take and Frigate . My goal is to make it so that when a certain face is recognized (and other security factors are considered, I know photos can fool it) the door will unlock. The face recognition in CodeProject. The http request node should contain the IP and port to the /recognize endpoint from my container. I hope you'll find this useful! Currently setup with Frigate and Coral PCIe on an old Lenovo USFF but had been watching for the 2. Not an overkill like yours but a ryzen 4500 + 32g + rtx2060 + google coral. Video Files are stored on dedicated drives (spinning metal, not in the VM space as its on a SSD). This to me is sort of important for a security standpoint. If you don’t use Frigate, then you can still utilize the Double Take API and pass any image One of the guys over at compreface on github has built compreface with coral tpu support. I hope you'll find this useful! I do I've built the logic that connects Frigate face detection to Compreface and ProjectAI myself using Nodered and MQTT (triggered by frigate/events and the JSON event structure). I get 4 times more recognitions with deepstack than with compreface. It does object detection. When both automations begin doing what I want, I’ll merge both into one. Reply reply SeraphTM Hi all, I have my coral and frigate setup - whilst it does a pretty good job with ID'ing things it does have issues with certain things. It seems to work pretty good but I realized many of the recognitions are getting rejected even though Double Take is a proxy between Frigate and any of the facial detection projects listed above. I got it working and training with frigate. I'm trying to find out, how the Coral Edge TPU model or Frigate is trained, or how I can train it with from camera's snapshots. Now I want to add DoubleTake triggers into HA but it doesn't look like I can use the separate install that I have on the VM, is the only way to get the triggers to use the DoubleTake addon? I've installed the docker container and then you have to create a config file and place in one of the empty directories that the frigate container makes I've got it setup with deepstack and compreface for facial recognition and I'll use it in conjunction with home assistant VM to send alerts to certain things((on to do list still as I perfect this) CompreFace Image Classification Responsive, mobile friendly Web UI written in TypeScript React I respond to all comments here on Reddit, the Home Assistant forum thread or GitHub issues. 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 Installed compreface in a docker container and set it up to get a key to put in doubletake config. Anyone have recommendations on getting consistently larger box area's for Double Take/Compreface to recognize faces? Should I find a way to not allow 'latest' for facial recognition? Or just use 'snapshot' or 'mqtt'? Reddit's most popular camera brand-specific subreddit! We are an unofficial I currently run 20 docker containers (HA, Frigate, DoubleTake, Compreface, Zig2M, zwave2m, etc. Is there anyone still using double take and if so can you please post a double take config? and CompreFace was trained. 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. If I enlarge the persons face it does detect it, is there a way to change the config to recognise a face in a larger image? FYI the camera already has person detection hence I don’t need to use frigate. Restarted frigate and immediately noticed that my detections were much more accurate. yaml and edited my minimum and threshold for objects. These images are passed from the API to the configured detector(s) until a match is found that meets the configured requirements. 2 coral to come back in stock) - it's working well so far. Now. I have them both installed as add-ons in HAOS, but i'm not getting anything into For me, nothing has been better than conpreface arcface-r100 running on my Nvidia GPU. I have frigate/double take/compreface setup. I'd recommend you to use compreface instead of deepstack, as its not maintained. Frigate + Double Take + Compreface Support Recently set up and testing out doing facial recognition on a Reolink doorbell that I have. Accuracy was pretty good, but more importantly there were no false positives. The http request in the NR flow is to my container's API. The unofficial but officially recognized Reddit community discussing the latest LinusTechTips, TechQuickie and other LinusMediaGroup content. When a Frigate event is received the API begins to process the snapshot. I'm using only computer (HP tiny with i5 6th generation CPU) resources. 13 and frigate card broke 😭 have tried rebooting reloading and deleting and free downloading the frigate card integration. I'm trying to create an automation that the trigger is when I arrive at my home and double-take recognizes my face is above 85% certainty on my doorbell camera and the action is CompreFace Image Classification Responsive, mobile friendly Web UI written in TypeScript React I respond to all comments here on Reddit, the Home Assistant forum thread or GitHub issues. thanks u/Bruceflix and u/rusochester - Doubletake is working great and was super easy to set up. Get the Reddit app Scan this QR code to download the app now. I’m running proxmox on it, I have hassio on one vm and other vm running frigate with the coral and face recognition (double take + compreface) with the gpu. When the container starts it subscribes to Frigate's MQTT events topic and looks for events that contain a person. Frigate Fans: OpenCV, a frigate library, is holding a Fundraiser is Struggling & Time's Double-Take is pulling events from Frigate and passing them to CompreFace, which is matching them (or not) correctly, and they are mostly correctly identified in Double-Take. The container then takes the information from that Frigate event and starts to poll images from Frigate to pass to CompreFace/Facebox. It has been working okay, but the stream never worked, it was only still images updated every second and only at the low resolution. output stream in a way to feed into plex / jellyfin audio to play in gui when viewing face detection(I saw doubletake and compreface) Saw the tracks from a deer in my backyard and even though I have dog enabled I didn't catch it when I definitely should have due to the area he was To start messing around with face recognition I installed double take and compreface in dockers on it's own VM. You have made it possible to have something of awesome quality FREE and allow others to be apart to help build something so grand. It works with deepstack, compreface, facebox, and rekognition. Frigate is able to use a much lower resolution because detection something large like a person doesn’t require many pixels. I'd start by setting up I'm new to Frigate NVR. Case: Fractal Define R5 MotherBoard: Asus B550 mATX CPU: Ryzen 5700G RAM: Currently at 32GB of 3600 mgtps RAM and can expand that with 2 more sticks to 64GB which I will likely do at some point. Get the Reddit app Scan this QR code to download the app now I plan on using double take for facial recognition with Frigate NVR. Those of you who uses Double-Take and CompreFace. 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. My setup is an HP EliteDesk 800 G4 DM Core i5-8500T 2. Thanks!. 1 - SSD 480 GB - 32GB, with Proxmox installed, HA in VM and Double Take as addon, Frigate in LXC container, and Compreface in LXC container. You may find it useful if you’re looking to detect specific people. AI, CompreFace, Deepstack and others. Or check it out in the app stores     TOPICS. However: I'm struggling to find in the documentation if it's possible to add the integration without having HACS, as my HA container does not have any access to add-ons or the HACS. I had this issue while trying to passthrough to my home-assistant vm running Frigate. I have been examining the logbook, and it seems that it takes a while for Frigate to notice that someone has walked into the frame. frigate and coral incorrect identifications. IrascibleBadger I have Frigate and Doubletake running on my Unifi doorbell. With that said you can run double-take along side frigate for facial recognition. We ask that you please take a minute to read It primarily interfaces with frigate so when someone comes to your door it will detect them and let you know if it is a known person or not. Double-take automation . I moved from in-camera detection (HikVision) to Frigate and it eliminated 95% of false positives from things like birds, trees etc. When the frigate/events topic is updated the API begins to process the snapshot. I have frigate working, deepstack working, compreface working and doubletake working. What I'm looking for if possible. Hello everyone. We are Reddit's primary hub for all things modding, from troubleshooting for beginners to creation of mods by experts. AI was not very reliable. If you haven't seen the Frigate+ docs, check them out: https://docs. I run Frigate on an Intel NUC i5 with a coral accelerator. Hey guys. The USB Hub (for Power Meter readings) and Coral M2 (for Frigate) are passed through from Truenas to the VM/HA. delay: 0. Hello! I have Frigate configured and working fine (it’s working fine also with compreface and double take), I receive notifications through telegram, and I have two automations (one for snapshots and other for clips) notifying me through telegram when someone enters my surveilled space. jpg and latest. Also you have doubletake which is by yakowlenko, not maintained as well (it's dead). I have frigate set up on another machine and accessible on the network (waiting for an M. Now moving to hardware and thought it would be pretty easy since I have known good configs View community ranking In the Top 1% of largest communities on Reddit. I use only one camera, tapo C200. AWESOME JOB TO ALL CONTRIBUTORS!!! Just wanted to take the time and say great job to all the contributors to Frigate NVR. AI detector setting look like in Compreface recognizes faces with very low quality, and gives false positives. Best setting in double-take for CompreFace. I have a reolink camera that I have been using though Frigate with the Frigate card in HA for the past few months. video/plus/ Edited to add: Confirmed that it works. Facial recognition takes a ton of pixels however. There's no reason to use opencv_face_required: true with compreface, compreface already has a face check built in. The previous days I've managed to setup Frigate on my Proxmox with shared iGPU (Raptor Lake CPU) as LXC with the Coral Coral USB Edge TPU, and having for now a 1 Hikvision 4MP camera. This is pure frigate, without homeassistant integration, which is the go-to recommendation as it integrates in to its phone app. mqtt: true # add a delay expressed in seconds between each detection loop. I know Frigate seems to start recording after an event and slightly before, which I'm guessing is a buffer happening. This combination you have now it's doomed already. Hey all, I recently got double-take set up with frigate and compreface. So the next step for me is setting up facial recognition since Frigate doesn't natively do this. However, Frigate NVR has been detecting as it should, but, it would seem that the I installed Frigate NVR (security video cameras that use AI to detect people and cats) and you can hand off detection (images/footage) to another AI model trained to recognize your face (or really anything you want). I have seen there are different programs to accomplish this task like CodeProject. I run Unraid OS in a NAS that I built myself. Expand user menu Open settings menu. Currently, I am using Double-Take in Home Assistant to orchestrate face recognition using Compreface as the face I've been using Frigate + CompreFace + Node-Red to achieve this, but my Node-Red flow became pretty complicated and hard to maintain, so I decided to move my logic to a local API, which I containerized. 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 compreface is much more accurate than deepstack. I've got compreface running on my frigate server, and used the Homeassistant integration for Doubletake. This subreddit has gone Restricted and reference-only as part of a mass protest against Reddit's recent API changes, which break third-party apps and moderation tools I containerized an API which subscribes to Frigates MQTT topic and then takes images from the API and passes them to compreface or facebox for facial recognition. I run CompreFace on a very old Mac with little to no issues. One example, compreface always gives a result for everyone, even if I only have my family in Process Frigate images with DeepStack, Facebox, CompreFace, and AWS Rekognition Double Take Unified UI and API for processing and training images for facial recognition. Hello. To improve the chances of finding a match, the processing of the images will repeat until the amount of retries is exhausted or a Plugged the model designation into my frigate. Double take isn't accurate or is, it's just an interface between frigate and face recognition software. I'll list my choices and rationale below. But I'm currently trying to add facial recognition via double-take and compreface. One capability I'd like to add is to be able to easily browse through unknown faces and potentially train for them (with names). These images are I got Frigate running on Unraid and have it connected to Home Assistant which is in a VM on my Unraid. I currently run 20 docker containers (HA, Frigate, DoubleTake, Compreface, Zig2M, zwave2m, etc. Using a Frigate+ model with Frigate will detect face as a "sub label" of person. jpg images from Frigate's API. ) and it is great. height: 500 # only process images from specific cameras. installed doubletake in a docker container Pointed doubletake config to Frigate, my MQTT server (home asssistant addon), and # process frigate images from frigate/+/person/snapshot topics. Log In / Sign Up; Wanted to know if it was possible to use CompreFace for object detection and if so, how do I do this in the config file? Thanks in advance. On the two outside cameras in areas where a person would be detected it like 71 or 73% probability. Which would be more accurate? I have a Google Coral and I7 7700 Intel with the Intel 630 Gpu. kau wugn mfelio qwgknl mgpjj qgtch qaknuj gjctbl lesa wnvd