Replies: 51 comments 246 replies
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Also, please don't open bug reports or support requests for development builds. At this time, what would be most helpful to us would be to keep all of your feedback here on this post. Thanks for helping test the new features! |
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First attempt to load latest dev build ended up with Config Editor (Safe Mode) due to this line: Commented out |
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Made a config change, hit save and restart, and got this series of errors I've not noted before. Restarted 5 minutes later, got a similar error on a different camera: |
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i noticed when i try to create state classification i got this logs |
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How do you delete classification models? I'm creating quite a few tests; looks like there are a few different locations I need to delete things in (and possibly the DB?) |
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I am running it since a few weeks and it is rock stable.
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@NickM-27 Here is some early NPU feedback FWIW. I changed my 2 Openvino detectors from GPU to NPU. Inference is maybe 1ms higher than GPU. This is on a Arrow Lake 225H running Proxmox with Frigate in a LXC container. 32GB Ram, 4vcpu's. My build is a day old (brand new setup). I have 4 cameras passing 8fps of 1920*1080 h265 CBR 1.5Mb/s Ill be playing around with this build for a while yet so happy to test/break anything you want to know..... Build 0.17.0-1e50d83 ov_1: model: Vainfo: |
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I seem to be getting face recoginition crashes. Only thing in the logs is. |
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NPU Intereference speed example with image: ghcr.io/blakeblackshear/frigate:256817d: Setup:
Detector interference speed:
Detector CPU usage: same at both: around 1,9% The power consumption of this setup is with NPU the same like with iGPU. |
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I've started playing with classification (state) for a iron gate which is in plain sight of one of my camera. The "creation" UI is fine but can't seem to be accessed after initial setup (should be available as Edit in "..." to change Name or add additional states. Where is the actual "state" of the particular object supposed to be found ? |
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Having a search box to filter logs would be very helpful. As would having, on mobile, tapping the top of the screen scroll the log window frame to top instead of the page itself. Right now I don't see a way to jump to top of logs on mobile like there is on desktop Also what are people most commonly doing for genai ? I'm using the recordings setting for review summaries which I know mentions rate limits but I'm hitting Google's extremely quick. I really don't want to pay for a service to use this feature but at the same time I'm not sure I have a good enough system to run ollama. I'll need to look into it |
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There is definately something not right with face after build 88a2f6c. as soon as I move on from that commit faces are comming up as unknown. if i try and reprocess them i get the following. If i roll back to 88a2f6c they reprocess.
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So as a quick update on my usage of classification models: its working fairly well. I'm randomly getting errors when trying to train a new model that its failing to find images, but if I hit try again, it works. Its done in multiple times now. One other issue I'm running into now is one of the states that I thought would be nice to have (position of a manual gate) required repositioning the camera (you could see it before, but it was really tough, even for a human, and I couldn't get a classification model trained on it, I moved the camera a slightly to make it much easier), but now when I'm trying to train the model, its obviously pulling tons of images from before the repositioning. Is there a recommended way to handle camera repositioning? |
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Feedback on the new Review interface In short, love it. The Event/Detail views are super useful but the killer feature for me is the Object Path tracking. I think that's going to help a lot of users understand what's happening under the hood when it comes to object detection and debug configuration issues. |
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I'm testing the tab with the "Classification" of objects and for some reason I can't train the model, when I click on the button, an endless download appears, and various errors appear in the logs from version to version. There is a version where learning takes place without problems (01452e4), but for some reason this functionality does not work on the last two versions.
b"[concat @ 0x55d3557cbd80] Impossible to open '/tmp/cache/preview_frames/preview_Entry-1762930288.004772.webp'\n[in#0 @ 0x55d3557cba40] Error opening input: Invalid data found when processing input\nError opening input file /dev/stdin.\nError opening input files: Invalid data found when processing input\n"
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Is this correct for setting up genai? It doesnt seem to be running? |
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Possibly a daft question - if I want to update the activity_context_prompt per camera, do I just copy / paste the default text into the camera genai section and amend as I wish? |
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Should I train night b&w/infrared snapshots for classification objects or only colored snapshots? |
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Some kind of weird memory leak happened, I noticed a ton of swapping going on, so I checked htop and saw The last error in the logs showed this but nothing about the side camera. scrolling up I did see some errors with audio docker log |
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I am currently testing the developer version [and] I find it super well-made. I am on version 097673b-rpi. I just have one question: I'm trying to set up genai with LM Studio, but it absolutely insists on an API key, yet I can't provide one. Is this normal? Here is my config: YAML environment_vars: genai: base_url: http://10.0.0.102:1234/v1 <-- Line commented out or removedapi_key: tutu Thank you for your work. |
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Dev builds of Frigate never start up on my Jetson when configuring my streams, today I figured out why: Inside the frigate docker: root@600b8b2175f1:~$ /usr/lib/ffmpeg/jetson/bin/ffprobe -v quiet -print_format json -show_format -show_streams <my-rtsp-uri>
{
[.. hangs forever ..]
^C
root@600b8b2175f1:~$ /usr/lib/ffmpeg/jetson/bin/ffprobe -v quiet -print_format json -show_format -show_streams <my-rtsp-uri> -rtsp_transport tcp
{
"streams": [
{
"index": 0,
"codec_name": "h264",
"codec_long_name": "H.264 / AVC / MPEG-4 AVC / MPEG-4 part 10",
"profile": "Main",
"codec_type": "video",
"codec_tag_string": "[0][0][0][0]",
"codec_tag": "0x0000",
"width": 1280,
"height": 720,
"coded_width": 1280,
"coded_height": 720,
"closed_captions": 0,
"film_grain": 0,
"has_b_frames": 0,
"pix_fmt": "yuv420p",
"level": 31,
"color_range": "tv",
"color_space": "bt709",
"color_transfer": "bt709",
"color_primaries": "bt709",
"chroma_location": "left",
"field_order": "progressive",
"refs": 1,
"is_avc": "false",
"nal_length_size": "0",
"r_frame_rate": "349/12",
"avg_frame_rate": "25/1",
"time_base": "1/90000",
"start_pts": 3097,
"start_time": "0.034411",
"bits_per_raw_sample": "8",
"extradata_size": 37,
"disposition": {
"default": 0,
"dub": 0,
"original": 0,
"comment": 0,
"lyrics": 0,
"karaoke": 0,
"forced": 0,
"hearing_impaired": 0,
"visual_impaired": 0,
"clean_effects": 0,
"attached_pic": 0,
"timed_thumbnails": 0,
"captions": 0,
"descriptions": 0,
"metadata": 0,
"dependent": 0,
"still_image": 0
}
}
],
"format": {
"filename": "<my-rtsp-uri>",
"nb_streams": 1,
"nb_programs": 0,
"format_name": "rtsp",
"format_long_name": "RTSP input",
"start_time": "0.034411",
"probe_score": 100,
"tags": {
"title": "RTSP Session"
}
}
}For some reason |
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When I edit an existing camera and add the audio role, the camera is added twice in my config as two separate cameras. |
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Hi - Do we know if the Memryx MX3 accelerator should be working with these early 0.17 builds? If so, I am happy to test and report back |
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Do you have docker builds yet? I'd like to test out 17 on my 265k CPU and test the NPU |
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Frigate 0.17 includes many new features, some of which require additional feedback to ensure a smooth user experience. Frigate 0.17 is still under active development and is not recommended for use in production systems (there may be large / breaking bugs).
As we get closer to a beta cycle we are looking to get additional feedback from users in some specific areas so that we may get a better understanding of how things are working and fix any bugs.
We are currently looking for feedback on the following features, all other feedback will be ignored for the time being. If you test any of the following, please leave a note even if it just says that things are working well.
If you experience any bugs with config migration, or bugs with existing functionality then please give that feedback as well.
The docs are: https://deploy-preview-19787--frigate-docs.netlify.app/
Object Detectors
Nvidia: CUDA Graphs are now utilized to greatly reduce the involvement of the CPU when running inferences. This is done automatically with no config changes required. This should lead to lower minimum inference speeds and dramatically lower maximum inference speeds for Nvidia GPUs. This primarily affects object detection, but will help some other models such as face recognition. Do note that complex models such as YOLO-NAS and Semantic Search will not be supported / accelerated by CUDA Graphs.OpenVINO GPU: More subtle than Nvidia, but optimizations have been made to all OpenVINO inferences that should reduce CPU usage, memory contention (fewer number of memory transfers), and potentially lower memory usage as well.OpenVINO NPU: OpenVINO now supports NPU. Simply setNPUas the device on a supported platform and make sure/dev/accelis mapped into the container. Would be great to see inference speed examples, all model types that GPU supports should be supported by the NPU as well.Apple Silicon: Apple silicon is now supported. This requires setting up a plugin on the host so Frigate can communicate with the GPU/NPU. see the docsClassification Models
Frigate now has end-to-end support, including training, for classification models. These come in two types,
stateclassification (ex: gate open / close) andobjectclassification (ex: dog recognition). You can use the UI to create and start training the model.We are specifically looking to see examples of accuracy (good and bad) with images, any feedback on the setup wizard, bugs, etc.
https://deploy-preview-19787--frigate-docs.netlify.app/category/custom-classification
Review Item Descriptions
Frigate now supports using GenAI to summarize review items. Unlike object descriptions which are searchable, review item descriptions are structured metadata that include suspicious activity categorization. This allows Frigate UI and notifications to show the title / description along with indicators that something may require review based on the GenAI's understanding of the activity.
https://deploy-preview-19787--frigate-docs.netlify.app/configuration/genai/genai_review/
Authentication / Roles
main-user) to one of Frigate's supported roles (admin) see the docsBeta Was this translation helpful? Give feedback.
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