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dependabot[bot]andGitHub 34593dc204 Bump axios from 1.13.6 to 1.18.0 in /web
Bumps [axios](https://github.com/axios/axios) from 1.13.6 to 1.18.0.
- [Release notes](https://github.com/axios/axios/releases)
- [Changelog](https://github.com/axios/axios/blob/v1.x/CHANGELOG.md)
- [Commits](https://github.com/axios/axios/compare/v1.13.6...v1.18.0)

---
updated-dependencies:
- dependency-name: axios
  dependency-version: 1.18.0
  dependency-type: direct:production
...

Signed-off-by: dependabot[bot] <support@github.com>
2026-07-22 02:22:55 +00:00
45 changed files with 203 additions and 1090 deletions
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@@ -82,7 +82,6 @@ frontdoor
fstype
fullchain
fullscreen
gatekeep
genai
generativeai
genpts
@@ -10,11 +10,8 @@ body:
Before submitting, read the [beta documentation][docs].
By posting here you agree to follow our [AI policy][ai-policy]. Posts that appear to be written by an AI on your behalf may be closed without a response.
[docs]: https://docs-dev.frigate.video/
[discussions]: https://github.com/blakeblackshear/frigate/discussions
[ai-policy]: https://github.com/blakeblackshear/frigate/blob/dev/AI_POLICY.md
- type: textarea
id: description
attributes:
@@ -8,12 +8,9 @@ body:
Before submitting your support request, please [search the discussions][discussions], read the [official Frigate documentation][docs], and read the [Frigate FAQ][faq] pinned at the Discussion page to see if your question has already been answered by the community.
By posting here you agree to follow our [AI policy][ai-policy]. Posts that appear to be written by an AI on your behalf may be closed without a response.
[discussions]: https://www.github.com/blakeblackshear/frigate/discussions
[docs]: https://docs.frigate.video
[faq]: https://github.com/blakeblackshear/frigate/discussions/12724
[ai-policy]: https://github.com/blakeblackshear/frigate/blob/dev/AI_POLICY.md
- type: textarea
id: description
attributes:
@@ -8,12 +8,9 @@ body:
Before submitting your support request, please [search the discussions][discussions], read the [official Frigate documentation][docs], and read the [Frigate FAQ][faq] pinned at the Discussion page to see if your question has already been answered by the community.
By posting here you agree to follow our [AI policy][ai-policy]. Posts that appear to be written by an AI on your behalf may be closed without a response.
[discussions]: https://www.github.com/blakeblackshear/frigate/discussions
[docs]: https://docs.frigate.video
[faq]: https://github.com/blakeblackshear/frigate/discussions/12724
[ai-policy]: https://github.com/blakeblackshear/frigate/blob/dev/AI_POLICY.md
- type: textarea
id: description
attributes:
@@ -8,12 +8,9 @@ body:
Before submitting your support request, please [search the discussions][discussions], read the [official Frigate documentation][docs], and read the [Frigate FAQ][faq] pinned at the Discussion page to see if your question has already been answered by the community.
By posting here you agree to follow our [AI policy][ai-policy]. Posts that appear to be written by an AI on your behalf may be closed without a response.
[discussions]: https://www.github.com/blakeblackshear/frigate/discussions
[docs]: https://docs.frigate.video
[faq]: https://github.com/blakeblackshear/frigate/discussions/12724
[ai-policy]: https://github.com/blakeblackshear/frigate/blob/dev/AI_POLICY.md
- type: textarea
id: description
attributes:
@@ -8,12 +8,9 @@ body:
Before submitting your support request, please [search the discussions][discussions], read the [official Frigate documentation][docs], and read the [Frigate FAQ][faq] pinned at the Discussion page to see if your question has already been answered by the community.
By posting here you agree to follow our [AI policy][ai-policy]. Posts that appear to be written by an AI on your behalf may be closed without a response.
[discussions]: https://www.github.com/blakeblackshear/frigate/discussions
[docs]: https://docs.frigate.video
[faq]: https://github.com/blakeblackshear/frigate/discussions/12724
[ai-policy]: https://github.com/blakeblackshear/frigate/blob/dev/AI_POLICY.md
- type: textarea
id: description
attributes:
@@ -8,12 +8,9 @@ body:
Before submitting your support request, please [search the discussions][discussions], read the [official Frigate documentation][docs], and read the [Frigate FAQ][faq] pinned at the Discussion page to see if your question has already been answered by the community.
By posting here you agree to follow our [AI policy][ai-policy]. Posts that appear to be written by an AI on your behalf may be closed without a response.
[discussions]: https://www.github.com/blakeblackshear/frigate/discussions
[docs]: https://docs.frigate.video
[faq]: https://github.com/blakeblackshear/frigate/discussions/12724
[ai-policy]: https://github.com/blakeblackshear/frigate/blob/dev/AI_POLICY.md
- type: textarea
id: description
attributes:
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@@ -10,12 +10,9 @@ body:
**If you are looking for support, start a new discussion and use a support category.**
By posting here you agree to follow our [AI policy][ai-policy]. Posts that appear to be written by an AI on your behalf may be closed without a response.
[discussions]: https://www.github.com/blakeblackshear/frigate/discussions
[docs]: https://docs.frigate.video
[faq]: https://github.com/blakeblackshear/frigate/discussions/12724
[ai-policy]: https://github.com/blakeblackshear/frigate/blob/dev/AI_POLICY.md
- type: textarea
id: description
attributes:
@@ -12,14 +12,11 @@ body:
**If you are unsure if your issue is actually a bug or not, please submit a support request first.**
By posting here you agree to follow our [AI policy][ai-policy]. Posts that appear to be written by an AI on your behalf may be closed without a response.
[discussions]: https://www.github.com/blakeblackshear/frigate/discussions
[prs]: https://www.github.com/blakeblackshear/frigate/pulls
[docs]: https://docs.frigate.video
[faq]: https://github.com/blakeblackshear/frigate/discussions/12724
[ai]: https://docs.frigate.video
[ai-policy]: https://github.com/blakeblackshear/frigate/blob/dev/AI_POLICY.md
- type: checkboxes
attributes:
label: Checklist
@@ -7,13 +7,6 @@ assignees: ''
---
<!--
By posting here you agree to follow our AI policy:
https://github.com/blakeblackshear/frigate/blob/dev/AI_POLICY.md
Requests that appear to be written by an AI on your behalf may be closed without a response.
-->
**Describe what you are trying to accomplish and why in non technical terms**
I want to be able to ... so that I can ...
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@@ -1,4 +1,4 @@
_Please read the [contributing guidelines](https://github.com/blakeblackshear/frigate/blob/dev/CONTRIBUTING.md) and the [AI policy](https://github.com/blakeblackshear/frigate/blob/dev/AI_POLICY.md) before submitting a PR. Every PR must be read and submitted by a person, and PRs that appear to be unreviewed AI output will be closed without review._
_Please read the [contributing guidelines](https://github.com/blakeblackshear/frigate/blob/dev/CONTRIBUTING.md) before submitting a PR._
## Proposed change
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@@ -1,126 +0,0 @@
# Frigate AI Policy
## TL;DR
- **Use AI tools if they help you.** We do too. This is about what you post, not which tools you use to write it.
- **A person has to read it and send it.** Don't wire a bot or an agent up to post on your behalf.
- **Write your posts yourself.** Your own words, the template filled in, and you answering maintainers rather than your assistant.
- **Don't paste an AI's guess at the cause as though it were a diagnosis.** Tell us what you actually observed.
- **Read your code before you submit it.** Disclose that AI was used, and be ready to explain every line.
- **If we misjudge something you wrote, just say so.** We'll take you at your word.
The rest of this document explains each of these, and why.
## Scope
AI tools are a reality of modern development and we're not opposed to their use. You are responsible for anything you submit, however it was produced, and we are responsible for anything we merge and release. We hold a high bar for both.
This policy applies everywhere this project is discussed: issues, discussions, pull requests, code reviews, and commit comments.
## Why this exists
Frigate is built and supported by a small group of maintainers and a community of volunteers who read every post and review every pull request. Nobody here is paid to do it, and time spent reading a post is time not spent fixing bugs or building features.
We're not opposed to AI tools. We use them too. But content generated by an AI and submitted without review costs a real person real time, and usually gives them less to work with than a few honest sentences would have. That is the problem this policy addresses.
## A person has to be in the loop
Every issue, discussion, comment, and pull request here must be read and submitted by a person. Using an AI tool to help you write is fine. Wiring one up to post on your behalf is not.
Specifically, do not:
- Connect a bot or agent to GitHub that opens issues, discussions, or pull requests without you reading them first
- Post output from a tool you have not read
- Use tooling to file bulk or drive-by contributions across the repository
We will close anything we believe was posted without a person reading it, and we may mark it as spam. Posts that skip the templates are the most common sign of this.
## Issues, discussions, and comments
We do not mind if you use AI tools to help you write. Do not have tools post unreviewed content on your behalf. We may hide any comment we believe to be unreviewed AI output.
Keep posts to what is needed to communicate your point. A long, confidently written, AI-padded post is harder to help with than a short direct one, not easier, and it is usually obvious.
**Describe your actual problem in your own words.** Tell us what you did, what you expected, and what actually happened. That is the information we need, and only you have it.
**Do not paste an AI's guess at the cause as though it were a diagnosis.** It is frequently wrong in ways that send everyone down the wrong path, and it buries the details that would have led to the real answer. We would rather see what you observed than what a model inferred.
**Fill in the template completely.** The templates ask for logs, config, version, and hardware because those are the things needed to help you. An AI cannot supply them for you, and a post missing them cannot be acted on.
**Answer maintainers yourself.** If we ask you a question, we are asking _you_, not your AI assistant. These are the spaces where we build trust and understanding with the community, and that only works if we're talking to each other. Using AI to fix your grammar or clarity is fine, but the substance has to be yours.
This applies to pull request descriptions and review replies as much as it does to bug reports and discussions.
### Quoting AI output
If you want to include something an AI told you, it must be:
- In a quote block, using `>`
- Disclosed as AI output, saying which tool it came from
- Accompanied by your own comment explaining why you think it is relevant
Keep the excerpt short. Do not paste long transcripts.
### Non-native English speakers
AI is genuinely useful for participating in a project that operates in English, and we would rather hear from you through a translation tool than not hear from you at all. Using AI to improve the grammar or clarity of something you wrote yourself is fine.
If you are translating your posts, make sure the translation says what you meant. Including your original text in a `<details>` block helps us verify the translation if something reads oddly, and keeps the thread readable.
## Code contributions
We need to understand your relationship with the code you're submitting. The more AI was involved, the more important it is that you've genuinely reviewed, tested, and understood what it produced.
Because of the long-term maintenance burden every merged change creates, we require a human in the loop who understands the work the AI produced. Pull requests that appear to be unreviewed AI output will be closed without review.
### Requirements when AI is used
If AI is used to generate any portion of the code, contributors must adhere to the following requirements:
1. **Explicitly disclose the manner in which AI was employed.** The PR template asks for this. Be honest, this won't automatically disqualify your PR. We'd rather have an honest disclosure than find out later. Trust matters more than method.
2. **Perform a comprehensive manual review prior to submitting the pull request.** Don't submit code you haven't read carefully and tested locally.
3. **Be prepared to explain every line of code you submitted when asked about it by a maintainer.** If you can't explain why something works the way it does, you're not ready to submit it.
4. **Check for an existing pull request addressing the same change.** If one exists, comment there and work with its author instead of opening a duplicate.
5. **It is strictly prohibited to use AI to write your posts for you** (bug reports, feature requests, pull request descriptions, GitHub discussions, responding to humans, etc.). We need to hear from _you_, not your AI assistant. These are the spaces where we build trust and understanding with contributors, and that only works if we're talking to each other.
### Established contributors
Contributors with a long history of thoughtful, quality contributions to Frigate have earned trust through that track record. The level of scrutiny we apply to AI usage naturally reflects that trust. This isn't a formal exemption, it's just how trust works. If you've been around, we know how you think and how you work. If you're new, we're still getting to know you, and clear disclosure helps build that relationship.
### What this means in practice
We're not trying to gatekeep how you write code. Use whatever tools make you productive. But there's a difference between using AI as a tool to implement something you understand and handing a feature request to an AI and submitting whatever comes back. The former is fine. The latter creates maintenance risk for the project.
Some honest context: when we review a PR, we're not just evaluating whether the code works today. We're evaluating whether we can maintain it, debug it, and extend it long-term, often without the original author's involvement. Code that the author doesn't deeply understand is code that nobody understands, and that's a liability.
One more thing worth saying directly: most maintainers already have access to the same AI tools you do. A PR that's entirely AI-generated, where the author can't explain the design, debug issues independently, or engage substantively in design discussions, doesn't offer something we couldn't produce ourselves. What makes a contribution genuinely valuable is the human judgment and domain understanding behind it, as well as the engagement during review that shapes it into something we can confidently take on long-term.
## Our use of AI
The Frigate documentation site has an "Ask AI" search that answers questions from the docs, and we may use AI tooling to help with triage and project management. Like any automated tooling, it is not always right.
If an AI tool leaves a comment on your contribution, treat it the way you would any other comment. If you think it is wrong, say so, and a brief explanation is enough. Maintainers always have the final say.
## Enforcement
Contributions and posts that do not follow this policy will be closed. Depending on the situation, maintainers may also:
- Hide or delete comments that appear to be unreviewed AI output
- Mark automated content as spam
- Close an issue, discussion, or pull request without further review
- Lock a conversation
- Temporarily or permanently block an account from participating in the project
Repeated violations may result in being blocked from contributing to Frigate.
### When we get it wrong
There is no reliable way to detect this, and we're not going to pretend otherwise. Whether something reads as unreviewed AI output is a judgment call, usually made quickly, by a volunteer with limited time and no way to know for certain. These calls are subjective and we won't always get them right.
If it happens to you, just say so. A short reply telling us you wrote it yourself is enough, and we'll take you at your word and pick the conversation back up. We would much rather occasionally reopen something we misjudged than treat everyone who posts here as a suspect.
We'd ask for some understanding in return. These calls get made quickly because the volume is real, and time spent second-guessing them is time not spent helping the person in the next thread.
## Attribution
Portions of this policy are adapted from the [Open Home Foundation AI Policy](https://developers.home-assistant.io/docs/ai_policy/).
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@@ -2,8 +2,6 @@
Thank you for your interest in contributing to Frigate. This document covers the expectations and guidelines for contributions. Please read it before submitting a pull request.
All participation in this project, including pull requests, issues, and discussions, is covered by our [AI policy](AI_POLICY.md).
## Before you start
### Bugfixes
@@ -23,16 +21,28 @@ Before writing code for a new feature:
## AI usage policy
AI tools are a reality of modern development and we're not opposed to their use. But we need to understand your relationship with the code you're submitting, and we need to hear from you rather than from your AI assistant.
AI tools are a reality of modern development and we're not opposed to their use. But we need to understand your relationship with the code you're submitting. The more AI was involved, the more important it is that you've genuinely reviewed, tested, and understood what it produced.
**Read the [AI policy](AI_POLICY.md) before you open a pull request.** It is short, and it applies to everything you post here. The parts that most often catch people out:
### Requirements when AI is used
- A person has to be in the loop. Don't wire a bot or agent up to open pull requests, issues, or discussions on your behalf.
- Disclose how AI was used. The PR template asks for this. Be honest, it won't automatically disqualify your PR.
- Review and test everything you submit, and be prepared to explain every line when asked.
- Don't use AI to write your PR description or your replies to maintainers.
If AI is used to generate any portion of the code, contributors must adhere to the following requirements:
Pull requests that appear to be unreviewed AI output will be closed without review.
1. **Explicitly disclose the manner in which AI was employed.** The PR template asks for this. Be honest — this won't automatically disqualify your PR. We'd rather have an honest disclosure than find out later. Trust matters more than method.
2. **Perform a comprehensive manual review prior to submitting the pull request.** Don't submit code you haven't read carefully and tested locally.
3. **Be prepared to explain every line of code they submitted when asked about it by a maintainer.** If you can't explain why something works the way it does, you're not ready to submit it.
4. **It is strictly prohibited to use AI to write your posts for you** (bug reports, feature requests, pull request descriptions, GitHub discussions, responding to humans, etc.). We need to hear from _you_, not your AI assistant. These are the spaces where we build trust and understanding with contributors, and that only works if we're talking to each other.
### Established contributors
Contributors with a long history of thoughtful, quality contributions to Frigate have earned trust through that track record. The level of scrutiny we apply to AI usage naturally reflects that trust. This isn't a formal exemption — it's just how trust works. If you've been around, we know how you think and how you work. If you're new, we're still getting to know you, and clear disclosure helps build that relationship.
### What this means in practice
We're not trying to gatekeep how you write code. Use whatever tools make you productive. But there's a difference between using AI as a tool to implement something you understand and handing a feature request to an AI and submitting whatever comes back. The former is fine. The latter creates maintenance risk for the project.
Some honest context: when we review a PR, we're not just evaluating whether the code works today. We're evaluating whether we can maintain it, debug it, and extend it long-term — often without the original author's involvement. Code that the author doesn't deeply understand is code that nobody understands, and that's a liability.
One more thing worth saying directly: most maintainers already have access to the same AI tools you do. A PR that's entirely AI-generated — where the author can't explain the design, debug issues independently, or engage substantively in design discussions — doesn't offer something we couldn't produce ourselves. What makes a contribution genuinely valuable is the human judgment and domain understanding behind it, as well as the engagement during review that shapes it into something we can confidently take on long-term.
## Pull request guidelines
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@@ -11,8 +11,6 @@ It is not recommended to copy this full configuration file. Only specify values
:::
Sections marked `# NOTE: Can be overridden at the camera level` can be set globally and then adjusted per camera. See [Global and Camera-Level Configuration](../config_overrides.md) for how that works.
```yaml
mqtt:
# Optional: Enable mqtt server (default: shown below)
@@ -173,14 +171,13 @@ model:
# Valid values are rgb, bgr, or yuv. (default: shown below)
input_pixel_format: rgb
# Required: Object detection model input tensor format
# Valid values are nhwc, nchw, hwnc, or hwcn (default: shown below)
# Valid values are nhwc or nchw (default: shown below)
input_tensor: nhwc
# Optional: Data type of the model input tensor
# Valid values are float, float_denorm, or int (default: shown below)
input_dtype: int
# Required: Object detection model architecture, used by detectors that support more
# than one model type (openvino, onnx, rknn, memryx, axengine, synaptics, and others)
# Valid values are ssd, yolox, yolonas, yolo-generic, rfdetr, dfine (default: shown below)
# Required: Object detection model type, currently only used with the OpenVINO detector
# Valid values are ssd, yolox, yolonas (default: shown below)
model_type: ssd
# Required: Label name modifications. These are merged into the standard labelmap.
labelmap:
@@ -471,8 +468,8 @@ review:
detections: False
# Optional: Activity Context Prompt to give context to the GenAI what activity is and is not suspicious.
# It is important to be direct and detailed. See documentation for the default prompt structure.
activity_context_prompt: |
Define what is and is not suspicious
activity_context_prompt: """Define what is and is not suspicious
"""
# Optional: Image source for GenAI (default: preview)
# Options: "preview" (uses cached preview frames at ~180p) or "recordings" (extracts frames from recordings at 480p)
# Using "recordings" provides better image quality but uses more tokens per image.
@@ -816,8 +813,7 @@ classification:
cameras:
camera_name:
# Required: Crop of image frame on this camera to run classification on
# [x1, y1, x2, y2] as decimals between 0 and 1, relative to the detect resolution
crop: [0.0, 0.25, 0.3, 0.85]
crop: [0, 180, 220, 400]
# Optional: If classification should be run when motion is detected in the crop (default: shown below)
motion: False
# Optional: Interval to run classification on in seconds (default: shown below)
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@@ -335,7 +335,7 @@ For example:
```
services:
frigate:
image: ghcr.io/blakeblackshear/frigate:stable
image: blakeblackshear/frigate:latest
environment:
- FRIGATE_BASE_PATH=/frigate
```
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@@ -165,7 +165,7 @@ If available, recommended settings are:
#### Setup via the Add Camera Wizard
The [Add Camera Wizard](cameras.md#adding-a-camera-with-the-add-camera-wizard) is the recommended way to add a standard Reolink camera. Before starting, make sure [HTTP is enabled](https://support.reolink.com/articles/360003452893-How-to-Access-Reolink-Cameras-NVRs-Home-Hub-Locally-via-Web-Browsers/) in the camera's advanced network settings. The wizard uses the camera's HTTP API to determine its resolution and choose the recommended stream type from the table above.
The Add Camera Wizard is the recommended way to add a standard Reolink camera. Before starting, make sure [HTTP is enabled](https://support.reolink.com/articles/360003452893-How-to-Access-Reolink-Cameras-NVRs-Home-Hub-Locally-via-Web-Browsers/) in the camera's advanced network settings. The wizard uses the camera's HTTP API to determine its resolution and choose the recommended stream type from the table above.
1. Click **Add Camera** in <NavPath path="Settings > Global configuration > Camera management" />.
2. Choose **Manual selection** as the stream detection method and select **Reolink** as the camera brand.
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@@ -7,49 +7,6 @@ import ConfigTabs from "@site/src/components/ConfigTabs";
import TabItem from "@theme/TabItem";
import NavPath from "@site/src/components/NavPath";
## Adding a camera with the Add Camera Wizard
The Add Camera Wizard is the recommended way to add a camera. Click **Add Camera** in <NavPath path="Settings > Global configuration > Camera management" />. The wizard connects to your camera, tests each stream, and writes the camera's configuration for you, including the [go2rtc](go2rtc.md) restream and the live view stream mapping, so a standard setup needs no hand-written YAML.
### Step 1: Name and connection
Enter a name for the camera along with its host or IP address and credentials, then choose how the wizard should find the camera's streams:
- **Probe camera** queries the camera over ONVIF (the ONVIF port is usually 80 or 8080) and asks it for its stream URLs. Some cameras use a separate ONVIF/service account rather than the device admin user, and some require **Use digest authentication** to be enabled.
- **Manual selection** builds a stream URL from a template for the camera brand you pick (Dahua/Amcrest/EmpireTech, Hikvision/Uniview/Annke, Ubiquiti, Reolink, Axis, TP-Link, or Foscam). Choose **Other** to enter a custom RTSP URL directly. Non-RTSP stream types must be [configured manually](#setting-up-camera-inputs).
The name you enter is lowercased and spaces become underscores. If the result still isn't a valid config key, the wizard generates a safe name and stores what you typed as `friendly_name`.
### Step 2: Probe or snapshot
In probe mode, the wizard reports what the camera returned (manufacturer, model, firmware, profile count, and whether PTZ, presets, and [autotracking](autotracking.md) are supported) along with the RTSP URLs it discovered. Test each candidate to see its resolution, frame rate, and codecs together with a snapshot, then select the one you want to use.
In manual mode, the wizard tests the templated URL and shows the same metadata and snapshot.
If no RTSP URLs are found, the credentials may be wrong or the camera may not support ONVIF. Go back and use manual selection instead.
### Step 3: Stream configuration
Assign [roles](#setting-up-camera-inputs) to the stream, and use **Add Another Stream** to add the camera's other streams, for example a substream for `detect` alongside the main stream for `record`. At least one stream must have the `detect` role before you can continue.
**Reduce connections to camera** routes that input through the go2rtc restream so Frigate and the live view share a single connection to the camera instead of each opening their own. See [restream](restream.md) for more detail.
### Step 4: Validation and testing
Connect each stream to get a live preview, an estimated bandwidth figure, and a list of validation results. The wizard checks for the most common misconfigurations, including:
- A detect resolution that is too high (increased resource usage) or too low for reliable detection, or one it could not probe at all
- A stream marked `record` whose audio codec is not AAC, or that has no audio at all
- A stream marked `audio` that carries no audio stream
- Using a restreamed input for the `record` role
- Brand-specific issues, such as an RTSP stream on a Reolink camera that should use http-flv, or a Dahua/Hikvision substream selected for `detect`
**Use stream compatibility mode** passes the stream through go2rtc's ffmpeg module. Enable it if a stream fails to load after several attempts. Note that this also prevents [two way talk](/configuration/live#two-way-talk) from being detected for that stream.
**Save New Camera** writes the configuration and starts the camera right away. No restart is required.
Other features, including [hardware acceleration](hardware_acceleration_video.md), [two way talk](/configuration/live#two-way-talk), and audio transcoding, is configured after the camera has been added. For camera model specific quirks, see the [camera specific](camera_specific.md) docs.
## Setting Up Camera Inputs
Several inputs can be configured for each camera and the role of each input can be mixed and matched based on your needs. This allows you to use a lower resolution stream for object detection, but create recordings from a higher resolution stream, or vice versa.
@@ -112,7 +69,7 @@ Additional cameras are simply added under the camera configuration section.
<ConfigTabs>
<TabItem value="ui">
Navigate to <NavPath path="Settings > Global configuration > Camera management" /> and use the [Add Camera Wizard](#adding-a-camera-with-the-add-camera-wizard) to configure each additional camera.
Navigate to <NavPath path="Settings > Global configuration > Camera management" /> and use the add camera button to configure each additional camera.
</TabItem>
<TabItem value="yaml">
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@@ -20,7 +20,7 @@ Settings are organized into two scopes:
- **Global configuration**: values under <NavPath path="Settings > Global configuration" /> apply to every camera by default. This is where you set the baseline behavior for object detection, recording, snapshots, motion, and so on.
- **Camera configuration**: values under <NavPath path="Settings > Camera configuration" /> apply to a single camera. Use the camera selector button at the top of these pages to choose which camera you are editing.
When a camera-level section is left untouched, the camera simply inherits the global values. Changing a value on a camera page **overrides** the global value for that camera only: the global setting and every other camera are unaffected. This mirrors how the YAML works, where a value set under `cameras.<name>` takes precedence over the same value set at the top level. See [Global and Camera-Level Configuration](./config_overrides.md) for the full details, including how lists and maps are handled and which settings must be enabled globally first.
When a camera-level section is left untouched, the camera simply inherits the global values. Changing a value on a camera page **overrides** the global value for that camera only: the global setting and every other camera are unaffected. This mirrors how the YAML works, where a value set under `cameras.<name>` takes precedence over the same value set at the top level.
To undo an override and go back to inheriting from the parent scope, use the reset button at the bottom of the section:
@@ -130,8 +130,7 @@ go2rtc:
```yaml
genai:
my_provider:
api_key: "{FRIGATE_GENAI_API_KEY}"
api_key: "{FRIGATE_GENAI_API_KEY}"
```
## Common configuration examples
-244
View File
@@ -1,244 +0,0 @@
---
id: config_overrides
title: Global and Camera-Level Configuration
---
import ConfigTabs from "@site/src/components/ConfigTabs";
import TabItem from "@theme/TabItem";
import NavPath from "@site/src/components/NavPath";
Most of Frigate's configuration can be set once for all cameras and then adjusted for individual cameras. The global value acts as the default for every camera, and any camera can override it.
This page explains how that inheritance works. For a tour of the Settings UI itself, see [Frigate Configuration](./config.md).
## The basics
Set a value globally and every camera uses it. Set the same value on a camera and that camera uses its own value instead.
<ConfigTabs>
<TabItem value="ui">
1. Navigate to <NavPath path="Settings > Global configuration > Object detection" /> and set **Detect FPS** to `5`. Every camera now detects at 5 fps.
2. Navigate to <NavPath path="Settings > Camera configuration > Object detection" />, select the `driveway` camera, and set **Detect FPS** to `10`.
The `driveway` camera now detects at 10 fps. Every other camera still uses the global value of 5.
</TabItem>
<TabItem value="yaml">
```yaml
detect:
fps: 5 # every camera detects at 5 fps
cameras:
front_door:
ffmpeg: ...
driveway:
ffmpeg: ...
detect:
fps: 10 # except this one
```
`front_door` inherits `fps: 5`, and `driveway` uses `10`.
</TabItem>
</ConfigTabs>
## Overrides apply per value, not per section
Overriding one value in a section does not detach the rest of that section. Everything you don't set on the camera still comes from the global configuration.
<ConfigTabs>
<TabItem value="ui">
If you set a camera's **Motion threshold** but leave **Contour area** alone, only the threshold is overridden. The contour area continues to follow <NavPath path="Settings > Global configuration > Motion detection" />, and changing it there still affects that camera.
Open a section to see which values are overridden: the section header indicates how many fields differ from the global configuration.
</TabItem>
<TabItem value="yaml">
```yaml
motion:
threshold: 30
contour_area: 10
cameras:
driveway:
motion:
threshold: 40
```
The `driveway` camera ends up with `threshold: 40` and `contour_area: 10`. Only the value you wrote was overridden.
</TabItem>
</ConfigTabs>
## Returning a camera to the global value
<ConfigTabs>
<TabItem value="ui">
A camera section that has its own values shows an **Overridden** badge. To remove the override and go back to inheriting, use the **Reset to Global** button at the bottom of the section.
</TabItem>
<TabItem value="yaml">
Frigate treats a camera value as an override because it is written in the config file, not because it differs from the global value. Repeating the global value under a camera still creates an override:
```yaml
snapshots:
enabled: true
cameras:
driveway:
snapshots:
enabled: true # this is an override, even though it matches
```
If you later change the global `snapshots.enabled` to `false`, `driveway` keeps saving snapshots, because it has its own value. To make a camera follow the global value again, delete the key from the camera rather than setting it to match.
</TabItem>
</ConfigTabs>
## Lists replace, maps merge
This is the distinction that surprises people most.
**Lists are replaced entirely.** A camera's list does not add to the global list, it takes its place.
<ConfigTabs>
<TabItem value="ui">
The camera page shows the objects the camera is currently tracking, starting from the global list. Changing that selection under <NavPath path="Settings > Camera configuration > Objects" /> replaces the list for that camera, so make sure every object you want tracked is selected, not just the ones you are adding.
</TabItem>
<TabItem value="yaml">
```yaml
objects:
track:
- person
- car
cameras:
backyard:
objects:
track:
- dog # backyard tracks ONLY dog, not person or car
```
To track `dog` in addition to the global objects, list all of them on the camera.
</TabItem>
</ConfigTabs>
An empty list is a valid override, and is the normal way to opt a camera out of something:
```yaml
review:
alerts:
labels:
- person
cameras:
street:
review:
alerts:
labels: [] # this camera never creates alerts
```
**Maps are merged key by key.** A camera can add an entry without redeclaring the others.
<ConfigTabs>
<TabItem value="ui">
Adding a filter for one object under <NavPath path="Settings > Camera configuration > Objects" /> does not remove the filters inherited from <NavPath path="Settings > Global configuration > Objects" />. The camera keeps both.
</TabItem>
<TabItem value="yaml">
```yaml
objects:
filters:
person:
min_area: 5000
cameras:
driveway:
objects:
filters:
car:
min_area: 10000
```
The `driveway` camera ends up with both the `car` filter it defined and the `person` filter from the global configuration.
</TabItem>
</ConfigTabs>
## Which settings can be overridden
Most, but not all. The [full reference config](./advanced/reference.md) is the authoritative source: sections that support camera-level overrides are marked with the comment `# NOTE: Can be overridden at the camera level`. In the UI, a setting can be overridden if it appears under both <NavPath path="Settings > Global configuration" /> and <NavPath path="Settings > Camera configuration" />.
A few things worth knowing beyond that:
- Some sections are **global only** and have no camera-level equivalent, including `go2rtc`, `genai` providers, `classification`, `telemetry`, `camera_groups`, and `ui`.
- Some sections exist **only at the camera level**, such as `zones` and `onvif`.
- Some sections are **partially overridable**, meaning a camera accepts only a few of the keys available globally. `face_recognition`, `lpr`, and `audio_transcription` work this way, and the reference config notes which keys apply.
## Enrichments that must be enabled globally first
License plate recognition and face recognition are special: the global setting is not just a default, it is a switch that must be on before any camera can use the feature. Enabling one on a camera while it is disabled globally is a configuration error, and Frigate will refuse to start:
```
Camera driveway has lpr enabled but lpr is disabled at the global level of the config. You must enable lpr at the global level.
```
Enable the feature globally, then turn it off on the cameras that don't need it.
<ConfigTabs>
<TabItem value="ui">
1. Navigate to <NavPath path="Settings > Global configuration > License plate recognition" /> and enable **LPR**.
2. Navigate to <NavPath path="Settings > Camera configuration > License plate recognition" />, select each camera that should not run LPR, and disable the **Enable LPR** toggle.
</TabItem>
<TabItem value="yaml">
```yaml
lpr:
enabled: true
cameras:
driveway:
ffmpeg: ... # inherits lpr, enabled
backyard:
ffmpeg: ...
lpr:
enabled: false # opted out
```
</TabItem>
</ConfigTabs>
:::note
This applies only to `lpr` and `face_recognition`, because the global setting controls whether the supporting background process starts at all. Other features do not work this way. Audio transcription, for example, can be enabled on a single camera without being enabled globally.
:::
## Profiles
[Profiles](./profiles.md) add a further layer on top of everything described above. A profile is a named set of camera overrides that you can switch on and off while Frigate is running, for example to change detection and recording behavior when you leave the house.
Profiles are applied on top of a camera's already-resolved configuration, so a profile value wins over both the camera and the global value while that profile is active. Profiles cover a subset of the camera sections and do not modify your config file.
## Summary
- A camera inherits every value you don't set on it.
- Overriding one value does not detach the rest of the section.
- Writing a value on a camera overrides it, even if it matches the global value. Remove it to inherit again.
- Lists replace the global list. Maps merge into it.
- An empty list is an override, not an omission.
- `lpr` and `face_recognition` must be enabled globally before a camera can use them.
@@ -73,13 +73,9 @@ classification:
interval: 10 # also run every N seconds (optional)
cameras:
front:
# [x1, y1, x2, y2] as decimals between 0 and 1, relative to the
# camera's detect resolution
crop: [0.0, 0.25, 0.3, 0.85]
crop: [0, 180, 220, 400]
```
Crop coordinates are normalized: each value is a fraction of the camera's `detect` width or height, not a pixel value. Drawing the crop in the UI wizard writes these values for you.
An optional config, `save_attempts`, can be set as a key under the model name. This defines the number of classification attempts to save in the Recent Classifications tab. For state classification models, the default is 100.
</TabItem>
+54 -183
View File
@@ -6,46 +6,12 @@ title: Configuring Generative AI
import ConfigTabs from "@site/src/components/ConfigTabs";
import TabItem from "@theme/TabItem";
import NavPath from "@site/src/components/NavPath";
import FaqItem from "@site/src/components/FaqItem";
## Configuration
A Generative AI provider can be configured in the global config, which will make the Generative AI features available for use. There are currently 5 native providers available to integrate with Frigate. Other providers that support the OpenAI standard API can also be used. See the OpenAI-Compatible section below.
A Generative AI provider can be configured in the global config, which will make the Generative AI features available for use. There are currently 4 native providers available to integrate with Frigate. Other providers that support the OpenAI standard API can also be used. See the OpenAI-Compatible section below.
`genai` is a map of named providers. Each key under `genai` is a name you choose, and its value is that provider's settings:
<ConfigTabs>
<TabItem value="ui">
1. Navigate to <NavPath path="Settings > Enrichments > Generative AI" />.
- Click **Add** and enter a **Provider name**. Any name of letters, numbers, hyphens, and underscores is accepted, but it cannot be changed from the UI after the provider is created.
- Set **Provider** to the service you are using (e.g., `ollama`)
- Set **Base URL**, **API key**, and **Model** as required by that provider
- Set **Roles** to the roles this provider should handle.
</TabItem>
<TabItem value="yaml">
```yaml
genai:
my_provider: # any name you like
provider: ollama
base_url: http://localhost:11434
model: qwen3-vl:4b
roles:
- descriptions
- embeddings
- chat
```
</TabItem>
</ConfigTabs>
The examples on this page all use `my_provider`, but the name is arbitrary and is only used to reference the provider elsewhere in the config (for example, `semantic_search.model`).
Each provider handles one or more **roles**: `chat`, `descriptions`, and `embeddings`. A provider handles all three by default, and each role may be assigned to exactly one provider. Define a single provider if you want it to do everything, or split the roles across several providers using the `roles` option.
If the provider you choose requires an API key, you may either directly paste it in your configuration, or store it in an environment variable prefixed with `FRIGATE_`.
To use Generative AI, you must define a single provider at the global level of your Frigate configuration. If the provider you choose requires an API key, you may either directly paste it in your configuration, or store it in an environment variable prefixed with `FRIGATE_`.
## Local Providers
@@ -59,20 +25,15 @@ Running Generative AI models on CPU is not recommended, as high inference times
### Recommended Local Models
You must use a vision-capable model with Frigate. The following models are recommended for local deployment of the `descriptions` and `chat` roles:
You must use a vision-capable model with Frigate. The following models are recommended for local deployment:
| Model | Notes |
| ---------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `qwen3-vl` | Strong visual and situational understanding, enhanced ability to identify smaller objects and interactions with object. |
| `qwen3.6` | Strong situational understanding, but missing DeepStack from qwen3-vl leading to worse performance for identifying objects in people's hand and other small details. |
| `qwen3.5` | Strong situational understanding, but missing DeepStack from qwen3-vl leading to worse performance for identifying objects in people's hand and other small details. |
| `qwen3.6` | Strong situational understanding, similar to qwen3-vl |
| `gemma4` | Strong situational understanding, sometimes resorts to more vague terms like 'interacts' instead of assigning a specific action. |
The `embeddings` role needs a different kind of model. Text queries are matched against the stored image embeddings, so the model must be trained to place images and text into the same vector space. A chat or description model will still return vectors when asked, but those vectors are not trained for retrieval and text searches will return poor matches with no error to indicate why.
| Model | Notes |
| -------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `qwen3-vl-embedding` | Multimodal embeddings for [Semantic Search](/configuration/semantic_search#genai-provider). Must be served by llama.cpp started with `--embeddings` and `--mmproj`. |
:::info
Each model is available in multiple parameter sizes (3b, 4b, 8b, etc.). Larger sizes are more capable of complex tasks and understanding of situations, but requires more memory and computational resources. It is recommended to try multiple models and experiment to see which performs best.
@@ -124,12 +85,11 @@ All llama.cpp native options can be passed through `provider_options`, including
```yaml
genai:
my_provider:
provider: llamacpp
base_url: http://localhost:8080
model: your-model-name
provider_options:
context_size: 16000 # Optional, overrides the context size reported by the server.
provider: llamacpp
base_url: http://localhost:8080
model: your-model-name
provider_options:
context_size: 16000 # Optional, overrides the context size reported by the server.
```
</TabItem>
@@ -169,14 +129,13 @@ Note that Frigate will not automatically download the model you specify in your
```yaml
genai:
my_provider:
provider: ollama
base_url: http://localhost:11434
model: qwen3-vl:4b
provider_options: # other Ollama client options can be defined
keep_alive: -1
options:
num_ctx: 8192 # make sure the context matches other services that are using ollama
provider: ollama
base_url: http://localhost:11434
model: qwen3-vl:4b
provider_options: # other Ollama client options can be defined
keep_alive: -1
options:
num_ctx: 8192 # make sure the context matches other services that are using ollama
```
</TabItem>
@@ -192,12 +151,11 @@ For OpenAI-compatible servers (such as llama.cpp) that don't expose the configur
```yaml
genai:
my_provider:
provider: openai
base_url: http://your-llama-server
model: your-model-name
provider_options:
context_size: 8192 # Specify the configured context size
provider: openai
base_url: http://your-llama-server
model: your-model-name
provider_options:
context_size: 8192 # Specify the configured context size
```
This ensures Frigate uses the correct context window size when generating prompts.
@@ -220,11 +178,10 @@ This ensures Frigate uses the correct context window size when generating prompt
```yaml
genai:
my_provider:
provider: openai
base_url: http://your-server:port
api_key: your-api-key # May not be required for local servers
model: your-model-name
provider: openai
base_url: http://your-server:port
api_key: your-api-key # May not be required for local servers
model: your-model-name
```
</TabItem>
@@ -262,21 +219,19 @@ Ollama also supports [cloud models](https://ollama.com/cloud), where model infer
```yaml
genai:
my_provider:
provider: ollama
base_url: http://localhost:11434
model: cloud-model-name
provider: ollama
base_url: http://localhost:11434
model: cloud-model-name
```
or when using Ollama Cloud directly
```yaml
genai:
my_provider:
provider: ollama
base_url: https://ollama.com
model: cloud-model-name
api_key: your-api-key
provider: ollama
base_url: https://ollama.com
model: cloud-model-name
api_key: your-api-key
```
</TabItem>
@@ -314,10 +269,9 @@ To start using Gemini, you must first get an API key from [Google AI Studio](htt
```yaml
genai:
my_provider:
provider: gemini
api_key: "{FRIGATE_GEMINI_API_KEY}"
model: gemini-2.5-flash
provider: gemini
api_key: "{FRIGATE_GEMINI_API_KEY}"
model: gemini-2.5-flash
```
</TabItem>
@@ -327,13 +281,12 @@ genai:
To use a different Gemini-compatible API endpoint, set the `provider_options` with the `base_url` key to your provider's API URL. For example:
```yaml {5,6}
```yaml {4,5}
genai:
my_provider:
provider: gemini
...
provider_options:
base_url: https://...
provider: gemini
...
provider_options:
base_url: https://...
```
Other HTTP options are available, see the [python-genai documentation](https://github.com/googleapis/python-genai).
@@ -367,10 +320,9 @@ To start using OpenAI, you must first [create an API key](https://platform.opena
```yaml
genai:
my_provider:
provider: openai
api_key: "{FRIGATE_OPENAI_API_KEY}"
model: gpt-4o
provider: openai
api_key: "{FRIGATE_OPENAI_API_KEY}"
model: gpt-4o
```
</TabItem>
@@ -386,14 +338,13 @@ To use a different OpenAI-compatible API endpoint, set the `OPENAI_BASE_URL` env
For OpenAI-compatible servers (such as llama.cpp) that don't expose the configured context size in the API response, you can manually specify the context size in `provider_options`:
```yaml {6,7}
```yaml {5,6}
genai:
my_provider:
provider: openai
base_url: http://your-llama-server
model: your-model-name
provider_options:
context_size: 8192 # Specify the configured context size
provider: openai
base_url: http://your-llama-server
model: your-model-name
provider_options:
context_size: 8192 # Specify the configured context size
```
This ensures Frigate uses the correct context window size when generating prompts.
@@ -428,91 +379,11 @@ To start using Azure OpenAI, you must first [create a resource](https://learn.mi
```yaml
genai:
my_provider:
provider: azure_openai
base_url: https://instance.cognitiveservices.azure.com/openai/responses?api-version=2025-04-01-preview
model: gpt-5-mini
api_key: "{FRIGATE_OPENAI_API_KEY}"
provider: azure_openai
base_url: https://instance.cognitiveservices.azure.com/openai/responses?api-version=2025-04-01-preview
model: gpt-5-mini
api_key: "{FRIGATE_OPENAI_API_KEY}"
```
</TabItem>
</ConfigTabs>
## FAQ
<FaqItem id="how-do-i-debug-genai-issues" question="How do I debug GenAI issues?">
Frigate's Generative AI features are configured and enabled separately. [Review descriptions and summaries](/configuration/genai/genai_review) live under `review.genai`, and [object descriptions](/configuration/genai/genai_objects) live under `objects.genai`. Configuring a provider on this page does not enable either feature, and enabling one does not enable the other. Decide which of the two is not working, then work through the steps below.
1. Confirm a provider is available and holds the `descriptions` role.
- Review descriptions, review summaries, and object descriptions all use the provider that has the `descriptions` role assigned in <NavPath path="Settings > Enrichments > Generative AI > Roles" /> (`genai.<provider>.roles`).
- A provider is contacted the first time one of its roles is actually used. A provider holding the `embeddings` role for semantic search is initialized during startup, while a `descriptions` provider is not initialized until the first description is requested, which may be well after boot.
- In <NavPath path="Settings > Enrichments > Generative AI" />, use **Refresh models** next to the model field. It queries the provider for its model list and is a quick way to verify that the base URL, API key, and network path between Frigate and your provider are correct.
2. Confirm the feature you expect is actually enabled.
- Object descriptions are disabled by default. Turn on <NavPath path="Settings > Global configuration > Objects > GenAI object config > Enable GenAI" /> (`objects.genai.enabled`), either globally or per camera. This is the most common reason custom prompts appear to be ignored while review summaries are still being generated.
- Review descriptions are disabled by default. Turn on <NavPath path="Settings > Global configuration > Review > GenAI config > Enable GenAI descriptions" /> (`review.genai.enabled`). Once enabled, alerts are described by default but detections are not, so a detection-only review item will never get a summary unless **Enable GenAI for detections** (`review.genai.detections`) is also on.
3. If object descriptions are never requested, check the filters that skip generation.
- <NavPath path="Settings > Global configuration > Objects > GenAI object config > GenAI objects" /> (`objects.genai.objects`) limits generation to specific labels, and **Required zones** (`objects.genai.required_zones`) requires the object to have entered one of those zones. If either is set and does not match, Frigate skips the request silently.
- Thumbnails are only collected while an object is moving. Objects that go stationary early contribute fewer frames.
- **Use snapshots** (`objects.genai.use_snapshot`) requires snapshots to be enabled for the camera. If the snapshot cannot be read, Frigate logs `Cannot load snapshot for <id>, file not found` and no description is generated.
- **Send on end** (`objects.genai.send_triggers.tracked_object_end`) is on by default. If you have turned it off in favor of **Early GenAI trigger** (`objects.genai.send_triggers.after_significant_updates`), descriptions are only requested once that number of updates is reached.
4. Enable debug logs to see exactly what Frigate is doing. Restart Frigate after this change. The next step also requires a restart, so turn both on at the same time to avoid restarting twice.
```yaml
logger:
default: info
logs:
# highlight-start
frigate.genai: debug
frigate.data_processing.post.object_descriptions: debug
frigate.data_processing.post.review_descriptions: debug
# highlight-end
```
5. Save the exact images and prompts that were sent to your provider.
- Turn on **Save thumbnails** for the feature you are debugging (`review.genai.debug_save_thumbnails` or `objects.genai.debug_save_thumbnails`). Both features write to `/media/frigate/clips/genai-requests/`, and these files are admin-only.
- Review descriptions write `genai-requests/<review_id>/` containing the numbered frames that were sent, plus `prompt.txt` and `response.txt` with the exact prompt and the raw, unparsed model response.
- Review summary reports write `genai-requests/<start_ts>-<end_ts>/prompt.txt` and `response.txt`. No images are involved, since a report summarizes existing review descriptions.
- Object descriptions write `genai-requests/<event_id>/` containing the numbered thumbnails. The prompt for object descriptions is not written to a file, it is only visible in the debug logs from step 4.
- Look at the saved images before blaming the model. If the object is small, blurry, or out of frame, no prompt will fix the result. For object descriptions, consider turning on **Use snapshots** (`objects.genai.use_snapshot`) to send a higher quality image. For review items, consider setting **Review image source** (`review.genai.image_source`) to `recordings` for 480p frames instead of the lower resolution preview frames.
<ConfigTabs>
<TabItem value="ui">
For review descriptions, navigate to <NavPath path="Settings > Global configuration > Review" /> and set **GenAI config > Save thumbnails** to on.
For object descriptions, navigate to <NavPath path="Settings > Global configuration > Objects" />, expand **GenAI object config**, and set **Save thumbnails** to on.
</TabItem>
<TabItem value="yaml">
```yaml
review:
genai:
enabled: true
# highlight-next-line
debug_save_thumbnails: true
objects:
genai:
enabled: true
# highlight-next-line
debug_save_thumbnails: true
```
</TabItem>
</ConfigTabs>
6. Verify the prompt is what you think it is.
- Object description prompts are the ones you control directly. A camera-level <NavPath path="Settings > Camera configuration > Objects > GenAI object config > Caption prompt" /> (`objects.genai.prompt`) overrides the global one, and an entry in **Object prompts** (`objects.genai.object_prompts`) for a label overrides both for that label. Only `{label}`, `{sub_label}`, and `{camera}` are substituted.
- Review description prompts are built by Frigate and request a structured JSON response, so they are not fully replaceable. The parts you control are <NavPath path="Settings > Global configuration > Review > GenAI config > Activity context prompt" /> (`review.genai.activity_context_prompt`) and **Additional concerns** (`review.genai.additional_concerns`). Keep the activity context prompt general, since overly specific rules will sway the model's threat level scoring.
7. If descriptions are generated but the results are poor or inconsistent, look at the model and the context window.
- Empty fields, missing `shortSummary` values, or `Failed to parse review description` errors usually mean the model is not following the requested JSON schema. Smaller models struggle with structured output. Try a larger parameter size or one of the [recommended models](#recommended-local-models).
- Frigate calculates how many frames to send from the context size the provider reports. If your server reports a different value than it is actually running with, frames will be truncated or the request will fail. Pin the value by adding `context_size` under <NavPath path="Settings > Enrichments > Generative AI > Provider options" /> (`genai.<provider>.provider_options`), and for Ollama also confirm `options.num_ctx` there matches the context you have configured.
- Check **Review Description Speed** and **Object Description Speed** in <NavPath path="System metrics > Enrichments" />. If inference takes tens of seconds, requests will queue behind each other and descriptions will appear to stop. For Ollama, review `OLLAMA_NUM_PARALLEL`, `OLLAMA_MAX_QUEUE`, and `OLLAMA_MAX_LOADED_MODELS` so that concurrent requests from Frigate are handled the way you expect.
</FaqItem>
+3 -8
View File
@@ -52,10 +52,9 @@ You can define custom prompts at the global level and per-object type. To config
```yaml
genai:
my_provider:
provider: ollama
base_url: http://localhost:11434
model: qwen3-vl:8b-instruct
provider: ollama
base_url: http://localhost:11434
model: qwen3-vl:8b-instruct
objects:
genai:
@@ -113,7 +112,3 @@ Many providers also have a public facing chat interface for their models. Downlo
- OpenAI - [ChatGPT](https://chatgpt.com)
- Gemini - [Google AI Studio](https://aistudio.google.com)
- Ollama - [Open WebUI](https://docs.openwebui.com/)
## Troubleshooting
If descriptions are not being generated, or the generated descriptions are not what you expect, see [How do I debug GenAI issues?](/configuration/genai/genai_config#how-do-i-debug-genai-issues).
@@ -201,7 +201,3 @@ Along with individual review item summaries, Generative AI can also produce a si
Review reports can be requested via the [API](/integrations/api/generate-review-summary-review-summarize-start-start-ts-end-end-ts-post) by sending a POST request to `/api/review/summarize/start/{start_ts}/end/{end_ts}` with Unix timestamps.
For Home Assistant users, there is a built-in service (`frigate.review_summarize`) that makes it easy to request review reports as part of automations or scripts. This allows you to automatically generate daily summaries, vacation reports, or custom time period reports based on your specific needs.
## Troubleshooting
If summaries are not being generated, or the generated summaries are not what you expect, see [How do I debug GenAI issues?](/configuration/genai/genai_config#how-do-i-debug-genai-issues).
+1 -1
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@@ -15,7 +15,7 @@ Frigate uses the bundled go2rtc to power a number of key features:
:::tip[Most users no longer need to configure go2rtc by hand]
The [**camera setup wizard**](cameras.md#adding-a-camera-with-the-add-camera-wizard) is the recommended way to add cameras. Click **Add Camera** in <NavPath path="Settings > Global configuration > Camera management" />, and the wizard probes your camera and writes its configuration for you, including the go2rtc restream and the live stream mapping, so go2rtc is set up automatically.
The **camera setup wizard** is the recommended way to add cameras. Click **Add Camera** in <NavPath path="Settings > Global configuration > Camera management" />, and the wizard probes your camera and writes its configuration for you, including the go2rtc restream and the live stream mapping, so go2rtc is set up automatically.
This guide is mainly useful if you are **upgrading from an older version and have existing cameras that don't yet use go2rtc**, or if you want to fine-tune a stream by hand (for example, to transcode a codec your browser can't play). The [go2rtc troubleshooting guide](/troubleshooting/go2rtc) applies regardless of how your cameras were added.
+2 -2
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@@ -34,7 +34,7 @@ If you are using go2rtc, you should adjust the following settings in your camera
- Video codec: **H.264** - provides the most compatible video codec with all Live view technologies and browsers. Avoid any kind of "smart codec" or "+" codec like _H.264+_ or _H.265+_. as these non-standard codecs remove keyframes (see below).
- Audio codec: **AAC** - provides the most compatible audio codec with all Live view technologies and browsers that support audio.
- I-frame interval (sometimes called the keyframe interval, the interframe space, or the GOP length): match your camera's frame rate, or choose "1x" (for interframe space on Reolink cameras). For example, if your stream outputs 20fps, your i-frame interval should be 20 (or 1x on Reolink). Values higher than the frame rate will cause the stream to take longer to begin playback. See [this page](https://web.archive.org/web/20251213190836/https://gardinal.net/understanding-the-keyframe-interval/) for more on keyframes. For many users this may not be an issue, but it should be noted that a 1x i-frame interval will cause more storage utilization if you are using the stream for the `record` role as well.
- I-frame interval (sometimes called the keyframe interval, the interframe space, or the GOP length): match your camera's frame rate, or choose "1x" (for interframe space on Reolink cameras). For example, if your stream outputs 20fps, your i-frame interval should be 20 (or 1x on Reolink). Values higher than the frame rate will cause the stream to take longer to begin playback. See [this page](https://gardinal.net/understanding-the-keyframe-interval/) for more on keyframes. For many users this may not be an issue, but it should be noted that a 1x i-frame interval will cause more storage utilization if you are using the stream for the `record` role as well.
The default video and audio codec on your camera may not always be compatible with your browser, which is why setting them to H.264 and AAC is recommended. See the [go2rtc docs](https://github.com/AlexxIT/go2rtc?tab=readme-ov-file#codecs-madness) for codec support information.
@@ -196,7 +196,7 @@ services:
:::
See [go2rtc WebRTC docs](https://github.com/AlexxIT/go2rtc/tree/v1.9.14#module-webrtc) for more information about this.
See [go2rtc WebRTC docs](https://github.com/AlexxIT/go2rtc/tree/v1.8.3#module-webrtc) for more information about this.
### Two way talk
+2 -2
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@@ -163,8 +163,8 @@ genai:
model: your-model-name
roles:
- embeddings
- descriptions
- chat
- vision
- tools
semantic_search:
enabled: True
+1 -1
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@@ -144,7 +144,7 @@ At this point you should be able to start Frigate and a basic config will be cre
### Step 2: Add a camera
Click the **Add Camera** button in <NavPath path="Settings > Global configuration > Camera management" /> to use the camera setup wizard to get your first camera added into Frigate. See [Adding a camera with the Add Camera Wizard](../configuration/cameras.md#adding-a-camera-with-the-add-camera-wizard) for a walkthrough of each step.
Click the **Add Camera** button in <NavPath path="Settings > Global configuration > Camera management" /> to use the camera setup wizard to get your first camera added into Frigate.
### Step 3: Configure hardware acceleration (recommended)
+1 -1
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@@ -281,7 +281,7 @@ For advanced usecases, this behavior can be changed with the [RTSP URL
template](#options) option. When set, this string will override the default stream
address that is derived from the default behavior described above. This option supports
[jinja2 templates](https://jinja.palletsprojects.com/) and has the `camera` dict
variables from [Frigate API](/integrations/api/frigate-http-api)
variables from [Frigate API](../integrations/api)
available for the template. Note that no Home Assistant state is available to the
template, only the camera dict from Frigate.
+1 -1
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@@ -16,7 +16,7 @@ MQTT requires a network connection to your broker. This is typically local, but
### `frigate/available`
Designed to be used as an availability topic with Home Assistant. Possible message are:
"online": published once Frigate is running and has published its initial state. Note that this is published on every connection to the broker, so it is republished if the broker restarts or the connection drops and recovers, without Frigate itself restarting.
"online": published when Frigate is running (on startup)
"stopped": published when Frigate is stopped normally
"offline": published automatically by the MQTT broker if Frigate disconnects unexpectedly (via MQTT Will Message)
-238
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@@ -1,238 +0,0 @@
---
id: common_errors
title: Common Error Messages
---
import FaqItem from "@site/src/components/FaqItem";
This page is an index of error messages you might see in Frigate's logs, what each one means, and where to go next. It is organized by the kind of problem, not by which component logged the message.
Two things to know before you start:
- **Many of these messages come from FFmpeg, go2rtc, GPU drivers, or the operating system, not from Frigate itself.** Frigate captures and re-logs their output, so the log level shown in the Frigate UI does not always reflect the original severity.
- **Wrapped errors put the real cause on the next line.** When Frigate logs a generic message like `Error occurred when attempting to maintain recording cache`, the actual exception is logged immediately after it. When a camera's FFmpeg process exits, Frigate logs `The following ffmpeg logs include the last 100 lines prior to exit` and dumps that camera's FFmpeg output. Always read those lines, they are where the answer usually is.
## Camera connection and streams
<FaqItem id="connection-refused-no-route-to-host-401-404" question="Connection refused / No route to host / 401 Unauthorized / 404 Not Found">
These are FFmpeg errors about reaching the camera (or the go2rtc restream). `Connection refused` and `No route to host` mean nothing is listening at that address or the host is unreachable; `401 Unauthorized` is wrong credentials; `404 Not Found` is a wrong stream path (or a `restream` input pointing at a go2rtc stream name that does not exist). A camera that has hit its concurrent-connection limit can also return `refused` or `401` on a URL that works in VLC.
See [go2rtc troubleshooting](/troubleshooting/go2rtc#1-read-the-go2rtc-logs) for how to isolate the stream.
</FaqItem>
<FaqItem id="no-frames-received-in-20-seconds" question="No frames received from <camera> in 20 seconds. Exiting ffmpeg...">
FFmpeg is running but has stopped delivering video for 20 seconds, so Frigate's camera watchdog restarts it. The stream connected at least once, then went quiet: a camera reboot, a network drop, the camera evicting the connection, or a stalled decoder. If it repeats on a loop, the stream is unstable.
</FaqItem>
<FaqItem id="ffmpeg-process-crashed-unexpectedly" question="Ffmpeg process crashed unexpectedly for <camera>">
The detect FFmpeg process exited on its own. This message is only the notification; the cause is in the 100 FFmpeg log lines Frigate dumps right after it (look for a `Failed to sync surface`, `Connection refused`, codec, or audio error in that block). Related watchdog messages include `<camera> exceeded fps limit`, which means the camera is delivering frames faster than `detect.fps` (usually a camera whose real frame rate differs from what is configured).
</FaqItem>
<FaqItem id="non-monotonically-increasing-dts" question="Non-monotonic DTS / non monotonically increasing dts to muxer / Queue input is backward in time">
These are FFmpeg messages indicating the camera sent packets with out-of-order timestamps, either on the video or the audio stream. Timestamp jitter like this is common with WiFi cameras and restreamed or proxied sources; other causes are a camera "Smart Codec" / H.264+ / H.265+ mode or a camera clock that jumps. A sustained flood of these messages usually precedes the stream stalling and the watchdog restarting FFmpeg.
In most cases, the fix is to improve the network, reduce system resource usage, or switch to non-WiFi cameras. In general, WiFi cameras are [not recommended](https://ipcamtalk.com/threads/multiple-cameras-high-bandwidth.77100/#post-861110).
On the video stream, this can affect recordings: because they are copied without re-encoding, FFmpeg cannot fix the timestamps, and the segment muxer often splits early, producing one-second segments and a cache backlog. See [Recordings: segments are only 1 second long](/troubleshooting/recordings#segments-are-only-1-second-long).
On the audio stream, the messages can come from the output's audio encoding. If the audio stream is the problem, it may help to have go2rtc transcode it by adding `#audio=aac` to the camera's go2rtc stream to produce clean timestamps for everything consuming the restream.
</FaqItem>
<FaqItem id="bad-cseq" question="RTP: PT=xx: bad cseq (packet loss / reordering)">
An FFmpeg message meaning RTP packets arrived out of sequence, which almost always means the stream is using UDP transport. Frigate's RTSP presets force TCP, so seeing this points at a custom `input_args`, `preset-rtsp-udp`, or a go2rtc source that is not using TCP. Switch to TCP unless your camera is [UDP-only](/configuration/camera_specific#udp-only-cameras).
</FaqItem>
<FaqItem id="error-while-decoding-mb-non-existing-pps" question="error while decoding MB / non-existing PPS referenced (corrupt frames)">
FFmpeg decoder messages meaning the received video bitstream was incomplete or damaged. A few of these at every stream start are normal (the decoder connected before the first keyframe) and Frigate discards them. A continuous stream of them means real packet loss, from Wi-Fi or a saturated link, an overloaded camera, or an FFmpeg restart loop caused by another problem. Fix the underlying instability rather than the message.
</FaqItem>
<FaqItem id="could-not-find-codec-parameters" question="Could not find codec parameters for stream ... unspecified size">
An FFmpeg message meaning it probed the stream but never saw enough decodable video to determine the frame size, often because the probe window ended before the first keyframe on a long-GOP stream, or because the stream is not delivering usable video. If it is a Reolink HTTP stream, use `preset-http-reolink`, which raises the probe size for exactly this case.
</FaqItem>
## Recording
<FaqItem id="no-new-recording-segments" question="No new recording segments were created for <camera> in the last 120s">
Frigate's record watchdog is restarting the record FFmpeg process because no valid segment has reached the cache. This means the record stream is not connecting or the segments are being rejected (see the audio-codec entry below).
See [Recordings: the record stream isn't connecting](/troubleshooting/recordings#the-record-stream-isnt-connecting).
</FaqItem>
<FaqItem id="invalid-or-missing-video-stream-in-segment" question="Invalid or missing video stream in segment. Discarding.">
A cached recording segment failed validation (no readable video stream) and was deleted. The most common cause is a segment that was truncated because the record FFmpeg process was killed mid-write, so this often appears alongside, and as a consequence of, the record-stream restarts above. A segment containing only audio triggers it too.
</FaqItem>
<FaqItem id="incompatible-audio-codec" question="Recordings silently fail to save (incompatible audio codec)">
Some camera audio codecs (G.711 variants such as `pcm_alaw` and `pcm_mulaw`) cannot be stored in an MP4 container, so segments never finalize even though live view works.
See [Recordings: incompatible audio codec](/troubleshooting/recordings#incompatible-audio-codec-recordings-silently-fail-to-save) for the FFmpeg preset that transcodes the audio to AAC.
</FaqItem>
<FaqItem id="error-maintaining-recording-cache" question="Error occurred when attempting to maintain recording cache">
A generic wrapper; the real exception is on the next log line. Frequently it is `[Errno 28] No space left on device` or `[Errno 17] File exists` on a network share.
See [Recordings cache warnings and errors](/troubleshooting/recordings#i-see-the-message-error--error-occurred-when-attempting-to-maintain-recording-cache), which covers this message and the common `Errno` cases.
</FaqItem>
## Hardware acceleration
<FaqItem id="failed-to-sync-surface" question="Failed to sync surface / Failed to download frame: -5 / Error while filtering">
A VAAPI/QSV hardware frame-sync failure between FFmpeg and the GPU driver, not a Frigate bug. It usually appears when the detect stream is being scaled or decoded on the GPU.
See [GPU: Failed to download frame: -5](/troubleshooting/gpu#failed-to-download-frame--5), which lists the fixes in order (switch VAAPI/QSV preset, change `LIBVA_DRIVER_NAME`, use an H.264 substream, match detect resolution and fps to the stream).
</FaqItem>
<FaqItem id="no-decoder-surfaces-left" question="No decoder surfaces left / Can't allocate a surface">
Both mean the GPU ran out of decode surfaces: `No decoder surfaces left` is NVIDIA NVDEC, `Can't allocate a surface` is Intel QSV. This is surface-pool exhaustion, typically from too many concurrent hardware-decoded cameras on one GPU (consumer NVIDIA cards have a driver-enforced limit on simultaneous decode sessions). Reduce the number of cameras decoding on that GPU, decode some on the CPU, or move to hardware without the session cap.
</FaqItem>
<FaqItem id="nvidia-container-cli-nvml-error" question="nvidia-container-cli: nvml error: driver not loaded">
This comes from the NVIDIA container runtime while starting the container, not from Frigate, and the container never starts. The NVIDIA driver is not loaded on the host. Confirm `nvidia-smi` works on the host itself (not inside the container) before troubleshooting Frigate. In a VM or LXC, the driver must be available inside the guest. See [Hardware: Nvidia GPU](/configuration/hardware_acceleration_video).
</FaqItem>
## Detectors and models
<FaqItem id="illegal-instruction" question="Illegal instruction (core dumped)">
The process was killed by the CPU for executing an unsupported instruction. There are two distinct causes in Frigate:
- **A Coral EdgeTPU** on a newer kernel with an outdated gasket driver. See [EdgeTPU: Illegal instruction](/troubleshooting/edgetpu#attempting-to-load-tpu-as-pci--fatal-python-error-illegal-instruction).
- **A CPU without AVX/AVX2**, when enabling semantic search, face recognition, license plate recognition, classification, or audio transcription. These features use libraries compiled with AVX and crash immediately on CPUs that lack it (commonly Intel Celeron/Pentium before the 2020 Tiger Lake generation). See the [CPU requirements](/frigate/planning_setup#cpu).
</FaqItem>
<FaqItem id="onnx-invalidprotobuf" question="ONNX Runtime InvalidProtobuf / failed to load model">
ONNX Runtime could not parse the model file. The file exists but its contents are not a valid ONNX model, usually a corrupted or interrupted download in `model_cache`, or the wrong file pointed at by `model.path`. Delete the cached model file so Frigate re-downloads it, and confirm `model.path` points at an actual `.onnx` model. See [ONNX detector configuration](/configuration/object_detectors#onnx).
</FaqItem>
<FaqItem id="cuda-failure-999-901" question="CUDA failure 999 / CUDA failure 901">
ONNX Runtime CUDA errors. `999` (`cudaErrorUnknown`) is a general, unrecoverable CUDA context failure, usually a driver/runtime version mismatch between the host and the container or a GPU in a bad state. `901` is a CUDA-graph capture error, which points at a custom model whose operations are not capture-safe. For `999`, align the host driver with the container's CUDA version and confirm the GPU is healthy.
</FaqItem>
<FaqItem id="openvino-no-supported-devices" question="Can't get OPTIMIZATION_CAPABILITIES property as no supported devices found">
OpenVINO could not find the configured device (usually `GPU` or `NPU`). Most often the `/dev/dri` render node is not passed into the container, or the wrong render node is mapped when an iGPU and a discrete GPU coexist.
See [GPU: no supported devices found](/troubleshooting/gpu#cant-get-optimization_capabilities-property-as-no-supported-devices-found).
</FaqItem>
## Memory and storage
<FaqItem id="fatal-python-error-bus-error" question="Fatal Python error: Bus error">
Frigate ran out of shared memory (`/dev/shm`). The container's `shm_size` is too small for the number and resolution of your detect streams, or you added cameras after startup without increasing it.
See [Calculating required shm-size](/frigate/installation#calculating-required-shm-size). If you cannot increase `shm_size`, lowering the `SHM_MAX_FRAMES` environment variable reduces how many frames Frigate buffers per camera.
</FaqItem>
<FaqItem id="errno-28-no-space-left" question="[Errno 28] No space left on device">
A filesystem is full: the recordings volume (`/media/frigate`), the cache tmpfs (`/tmp/cache`), or `/dev/shm`. Check which one, and note that inode exhaustion can produce this while `df -h` still shows free space.
See [Recordings: No space left on device](/troubleshooting/recordings#i-see-the-message-error--error-occurred-when-attempting-to-maintain-recording-cache).
</FaqItem>
<FaqItem id="container-exits-with-no-logs" question="The container exits or restarts with no error in the logs">
A silent exit is usually the host or container out-of-memory killer. Because `/dev/shm` and `/tmp/cache` are memory-backed, they count against the container's memory limit, so aggressive shm or cache sizing can trigger it. Give the container more memory, or reduce shm/cache sizing, and check the host's OOM messages (`dmesg`).
</FaqItem>
## Database
<FaqItem id="database-is-locked" question="database is locked">
SQLite could not acquire the write lock. Frigate's timeout already scales with camera count, so under normal local-disk operation this essentially only happens when the database is on a network share (SMB/NFS), where file locking is unreliable, or when two instances point at the same file.
See [Database is locked](/troubleshooting/faqs#error-database-is-locked).
</FaqItem>
<FaqItem id="database-disk-image-is-malformed" question="database disk image is malformed">
The SQLite database file is corrupted, typically after hard power loss, a network-share database, or a filesystem with unsafe write semantics. Frigate does not repair it automatically, but the database can usually be recovered by hand.
**Stop Frigate first**, then work on the database file directly (by default `/config/frigate.db`). Start by checking what is actually wrong:
```bash
sqlite3 frigate.db "PRAGMA integrity_check;"
```
If the only problems reported are index-related (lines such as `row 14 missing from index recordings_path` or `non-unique entry in index ...`), rebuilding the indexes is usually enough and is the least destructive fix:
```bash
sqlite3 frigate.db "REINDEX;"
```
If the integrity check reports page or byte-level corruption instead (for example `Multiple uses for byte 2706 of page 142272`), dump the readable contents into a new database:
```bash
# dump what can still be read
sqlite3 frigate.db .dump > frigate.dump
# keep the corrupt file, then rebuild from the dump
mv frigate.db frigate.db.bak
cat frigate.dump | sqlite3 frigate.db
# confirm the rebuilt database is clean, this should print "ok"
sqlite3 frigate.db "PRAGMA integrity_check;"
```
Rows stored in the corrupted pages cannot be recovered, so expect to lose some tracked objects, review items, or thumbnails. Recordings themselves are files on disk and are not affected.
As a last resort, stop Frigate, delete `frigate.db`, and restart. Frigate recreates it, but existing recordings lose all of their metadata. If a `backup.db` exists next to your database, Frigate wrote it before the last schema migration and restoring it recovers everything up to that point.
Repeat corruption usually points at the underlying storage: move the database off a network share, and on Raspberry Pi check power delivery and the SD card or SSD.
</FaqItem>
## Startup and web access
<FaqItem id="unable-to-start-frigate-in-safe-mode" question="Unable to start Frigate in safe mode / Starting Frigate in safe mode">
When your config fails validation at startup, Frigate prints the validation errors (with line numbers), then starts in **safe mode**: a minimal configuration with no cameras and MQTT disabled, so the UI stays reachable. In safe mode the only available page is the Config Editor, which shows the validation errors so you can fix them, then save and restart. Note that recording retention and storage cleanup do **not** run while in safe mode, so do not leave a low-disk system sitting in it.
`Unable to start Frigate in safe mode` means even the minimal config failed, which points at an error in your `auth`, `proxy`, or `database` section, or a config file that is not valid YAML at all. Safe mode is not sticky; fix the config and restart and Frigate returns to normal.
</FaqItem>
<FaqItem id="502-bad-gateway" question="502 Bad Gateway / connection refused to 127.0.0.1:5001">
The web server is up but the Frigate backend (port 5001) is not answering yet. By far the most common reason is that the page was loaded during startup: the API binds last, after database migrations (which can take minutes on a large database), model downloads, and process startup, while the web server is already serving. Wait for startup to finish. If it persists, the backend has failed to start, and the reason is earlier in the logs. This also explains a `connection refused to 127.0.0.1:5001` seen while loading `/ws`, because every authenticated request first makes an auth subrequest to that port.
</FaqItem>
-2
View File
@@ -30,7 +30,6 @@ const sidebars: SidebarsConfig = {
],
Configuration: [
"configuration/config",
"configuration/config_overrides",
{
type: "category",
label: "Detectors",
@@ -166,7 +165,6 @@ const sidebars: SidebarsConfig = {
],
Troubleshooting: [
"troubleshooting/faqs",
"troubleshooting/common_errors",
"troubleshooting/go2rtc",
"troubleshooting/recordings",
"troubleshooting/dummy-camera",
+1 -1
View File
@@ -640,7 +640,7 @@ class FrigateConfig(FrigateBaseModel):
# set notifications state
self.notifications.enabled_in_config = self.notifications.enabled
# validate genai: each role (chat, descriptions, embeddings) at most once
# validate genai: each role (tools, vision, embeddings) at most once
role_to_name: dict[GenAIRoleEnum, str] = {}
for name, genai_cfg in self.genai.items():
for role in genai_cfg.roles:
+1 -1
View File
@@ -93,7 +93,7 @@ class ModelConfig(BaseModel):
model_type: ModelTypeEnum = Field(
default=ModelTypeEnum.ssd,
title="Object Detection Model Type",
description="Detector model architecture type (ssd, yolox, yolonas, yolo-generic, rfdetr, dfine) used by some detectors for optimization.",
description="Detector model architecture type (ssd, yolox, yolonas) used by some detectors for optimization.",
)
_merged_labelmap: dict[int, str] | None = PrivateAttr()
_colormap: dict[int, tuple[int, int, int]] = PrivateAttr()
-2
View File
@@ -159,8 +159,6 @@ class FFMpegConverter(threading.Thread):
f"duration {self.frame_times[t_idx + 1] - self.frame_times[t_idx]}"
)
Path(self.path).parent.mkdir(parents=True, exist_ok=True)
try:
p = sp.run(
self.ffmpeg_cmd.split(" "),
+4 -18
View File
@@ -115,11 +115,9 @@ class PendingReviewSegment:
if self._frame is not None:
self.thumb_time = datetime.datetime.now().timestamp()
self.has_frame = True
Path(self.frame_path).parent.mkdir(parents=True, exist_ok=True)
if not cv2.imwrite(
cv2.imwrite(
self.frame_path, self._frame, [int(cv2.IMWRITE_WEBP_QUALITY), 60]
):
logger.error("Failed to write review thumbnail to %s", self.frame_path)
)
def save_full_frame(self, camera_config: CameraConfig, frame: np.ndarray) -> None:
color_frame = cv2.cvtColor(frame, cv2.COLOR_YUV2BGR_I420)
@@ -130,11 +128,9 @@ class PendingReviewSegment:
if self._frame is not None:
self.has_frame = True
Path(self.frame_path).parent.mkdir(parents=True, exist_ok=True)
if not cv2.imwrite(
cv2.imwrite(
self.frame_path, self._frame, [int(cv2.IMWRITE_WEBP_QUALITY), 60]
):
logger.error("Failed to write review thumbnail to %s", self.frame_path)
)
def get_data(self, ended: bool) -> dict:
end_time = None
@@ -378,16 +374,6 @@ class ReviewSegmentMaintainer(threading.Thread):
"""Forcibly end the pending segment for a camera."""
segment = self.active_review_segments.get(camera)
if segment:
if self.indefinite_events.get(camera):
self.indefinite_events[camera] = {}
now = datetime.datetime.now().timestamp()
if segment.last_alert_time == sys.maxsize:
segment.last_alert_time = now
if segment.last_detection_time == sys.maxsize:
segment.last_detection_time = now
prev_data = segment.get_data(False)
return self._publish_segment_end(segment, prev_data)
return None
+1 -1
View File
@@ -326,7 +326,7 @@ def get_ort_providers(
{
"device_id": device_id,
"trt_fp16_enable": requires_fp16
and os.environ.get("USE_FP16", "True") != "False",
and os.environ.get("USE_FP_16", "True") != "False",
"trt_timing_cache_enable": True,
"trt_engine_cache_enable": True,
"trt_timing_cache_path": os.path.join(
+46 -16
View File
@@ -39,7 +39,7 @@
"@rjsf/utils": "^6.4.1",
"@rjsf/validator-ajv8": "^6.4.1",
"apexcharts": "^3.52.0",
"axios": "^1.13.6",
"axios": "^1.18.0",
"class-variance-authority": "^0.7.1",
"clsx": "^2.1.1",
"cmdk": "^1.0.0",
@@ -73,7 +73,7 @@
"react-markdown": "^9.0.1",
"react-router-dom": "^6.30.3",
"react-swipeable": "^7.0.2",
"react-zoom-pan-pinch": "3.4.4",
"react-zoom-pan-pinch": "^3.7.0",
"remark-gfm": "^4.0.0",
"scroll-into-view-if-needed": "^3.1.0",
"sonner": "^2.0.7",
@@ -6458,14 +6458,40 @@
}
},
"node_modules/axios": {
"version": "1.13.6",
"resolved": "https://registry.npmjs.org/axios/-/axios-1.13.6.tgz",
"integrity": "sha512-ChTCHMouEe2kn713WHbQGcuYrr6fXTBiu460OTwWrWob16g1bXn4vtz07Ope7ewMozJAnEquLk5lWQWtBig9DQ==",
"version": "1.18.0",
"resolved": "https://registry.npmjs.org/axios/-/axios-1.18.0.tgz",
"integrity": "sha512-E32NzpYKp++W7XRe52rHiXV2ehxmh3wbdgO7MHeFM+vqxLBYHzt0ElkiImtOBxtOmyp0yoC8C6uESVV84Y2/hw==",
"license": "MIT",
"dependencies": {
"follow-redirects": "^1.15.11",
"follow-redirects": "^1.16.0",
"form-data": "^4.0.5",
"proxy-from-env": "^1.1.0"
"https-proxy-agent": "^5.0.1",
"proxy-from-env": "^2.1.0"
}
},
"node_modules/axios/node_modules/agent-base": {
"version": "6.0.2",
"resolved": "https://registry.npmjs.org/agent-base/-/agent-base-6.0.2.tgz",
"integrity": "sha512-RZNwNclF7+MS/8bDg70amg32dyeZGZxiDuQmZxKLAlQjr3jGyLx+4Kkk58UO7D2QdgFIQCovuSuZESne6RG6XQ==",
"license": "MIT",
"dependencies": {
"debug": "4"
},
"engines": {
"node": ">= 6.0.0"
}
},
"node_modules/axios/node_modules/https-proxy-agent": {
"version": "5.0.1",
"resolved": "https://registry.npmjs.org/https-proxy-agent/-/https-proxy-agent-5.0.1.tgz",
"integrity": "sha512-dFcAjpTQFgoLMzC2VwU+C/CbS7uRL0lWmxDITmqm7C+7F0Odmj6s9l6alZc6AELXhrnggM2CeWSXHGOdX2YtwA==",
"license": "MIT",
"dependencies": {
"agent-base": "6",
"debug": "4"
},
"engines": {
"node": ">= 6"
}
},
"node_modules/bail": {
@@ -8099,9 +8125,9 @@
"license": "ISC"
},
"node_modules/follow-redirects": {
"version": "1.15.11",
"resolved": "https://registry.npmjs.org/follow-redirects/-/follow-redirects-1.15.11.tgz",
"integrity": "sha512-deG2P0JfjrTxl50XGCDyfI97ZGVCxIpfKYmfyrQ54n5FO/0gfIES8C/Psl6kWVDolizcaaxZJnTS0QSMxvnsBQ==",
"version": "1.16.0",
"resolved": "https://registry.npmjs.org/follow-redirects/-/follow-redirects-1.16.0.tgz",
"integrity": "sha512-y5rN/uOsadFT/JfYwhxRS5R7Qce+g3zG97+JrtFZlC9klX/W5hD7iiLzScI4nZqUS7DNUdhPgw4xI8W2LuXlUw==",
"funding": [
{
"type": "individual",
@@ -11922,9 +11948,13 @@
}
},
"node_modules/proxy-from-env": {
"version": "1.1.0",
"resolved": "https://registry.npmjs.org/proxy-from-env/-/proxy-from-env-1.1.0.tgz",
"integrity": "sha512-D+zkORCbA9f1tdWRK0RaCR3GPv50cMxcrz4X8k5LTSUD1Dkw47mKJEZQNunItRTkWwgtaUSo1RVFRIG9ZXiFYg=="
"version": "2.1.0",
"resolved": "https://registry.npmjs.org/proxy-from-env/-/proxy-from-env-2.1.0.tgz",
"integrity": "sha512-cJ+oHTW1VAEa8cJslgmUZrc+sjRKgAKl3Zyse6+PV38hZe/V6Z14TbCuXcan9F9ghlz4QrFr2c92TNF82UkYHA==",
"license": "MIT",
"engines": {
"node": ">=10"
}
},
"node_modules/psl": {
"version": "1.9.0",
@@ -12354,9 +12384,9 @@
}
},
"node_modules/react-zoom-pan-pinch": {
"version": "3.4.4",
"resolved": "https://registry.npmjs.org/react-zoom-pan-pinch/-/react-zoom-pan-pinch-3.4.4.tgz",
"integrity": "sha512-lGTu7D9lQpYEQ6sH+NSlLA7gicgKRW8j+D/4HO1AbSV2POvKRFzdWQ8eI0r3xmOsl4dYQcY+teV6MhULeg1xBw==",
"version": "3.7.0",
"resolved": "https://registry.npmjs.org/react-zoom-pan-pinch/-/react-zoom-pan-pinch-3.7.0.tgz",
"integrity": "sha512-UmReVZ0TxlKzxSbYiAj+LeGRW8s8LraAFTXRAxzMYnNRgGPsxCudwZKVkjvGmjtx7SW/hZamt69NUmGf4xrkXA==",
"license": "MIT",
"engines": {
"node": ">=8",
+2 -2
View File
@@ -53,7 +53,7 @@
"@rjsf/utils": "^6.4.1",
"@rjsf/validator-ajv8": "^6.4.1",
"apexcharts": "^3.52.0",
"axios": "^1.13.6",
"axios": "^1.18.0",
"class-variance-authority": "^0.7.1",
"clsx": "^2.1.1",
"cmdk": "^1.0.0",
@@ -87,7 +87,7 @@
"react-markdown": "^9.0.1",
"react-router-dom": "^6.30.3",
"react-swipeable": "^7.0.2",
"react-zoom-pan-pinch": "3.4.4",
"react-zoom-pan-pinch": "^3.7.0",
"remark-gfm": "^4.0.0",
"scroll-into-view-if-needed": "^3.1.0",
"sonner": "^2.0.7",
+2 -2
View File
@@ -322,7 +322,7 @@
},
"model_type": {
"label": "Object Detection Model Type",
"description": "Detector model architecture type (ssd, yolox, yolonas, yolo-generic, rfdetr, dfine) used by some detectors for optimization."
"description": "Detector model architecture type (ssd, yolox, yolonas) used by some detectors for optimization."
}
},
"model_path": {
@@ -495,7 +495,7 @@
},
"model_type": {
"label": "Object Detection Model Type",
"description": "Detector model architecture type (ssd, yolox, yolonas, yolo-generic, rfdetr, dfine) used by some detectors for optimization."
"description": "Detector model architecture type (ssd, yolox, yolonas) used by some detectors for optimization."
}
},
"genai": {
+1 -3
View File
@@ -125,7 +125,5 @@
"baby": "Baby",
"baby_stroller": "Baby Stroller",
"rickshaw": "Rickshaw",
"rodent": "Rodent",
"possum": "Possum",
"garbage_truck": "Garbage Truck"
"rodent": "Rodent"
}
@@ -14,7 +14,6 @@ const logger: SectionConfigOverrides = {
additionalProperties: {
"ui:options": {
enumI18nPrefix: "logger.logLevel",
additionalPropertyKeySize: "lg",
additionalPropertyKeyLabel:
"configForm.additionalProperties.loggerNameLabel",
additionalPropertyKeyPlaceholder:
@@ -15,14 +15,6 @@ import { useTranslation } from "react-i18next";
import { LuTrash2 } from "react-icons/lu";
import type { ConfigFormContext } from "@/types/configForm";
const KEY_SIZE_CLASSES = {
sm: { key: "md:col-span-2", value: "md:col-span-9" },
md: { key: "md:col-span-4", value: "md:col-span-7" },
lg: { key: "md:col-span-7", value: "md:col-span-4" },
} as const;
type AdditionalPropertyKeySize = keyof typeof KEY_SIZE_CLASSES;
export function WrapIfAdditionalTemplate<
T = unknown,
S extends StrictRJSFSchema = RJSFSchema,
@@ -66,14 +58,6 @@ export function WrapIfAdditionalTemplate<
: undefined;
const preventKeyRename = uiOptions.preventKeyRename === true;
const keySize =
typeof uiOptions.additionalPropertyKeySize === "string" &&
uiOptions.additionalPropertyKeySize in KEY_SIZE_CLASSES
? (uiOptions.additionalPropertyKeySize as AdditionalPropertyKeySize)
: "sm";
const keySpanClass = KEY_SIZE_CLASSES[keySize].key;
const valueSpanClass = KEY_SIZE_CLASSES[keySize].value;
const formContext = registry?.formContext as ConfigFormContext | undefined;
// optionally, lock the key once it's been saved
@@ -142,7 +126,7 @@ export function WrapIfAdditionalTemplate<
style={style}
>
{!keyIsReadonly && (
<div className={cn("col-span-12 space-y-2", keySpanClass)}>
<div className="col-span-12 space-y-2 md:col-span-2">
{displayLabel && <Label htmlFor={keyId}>{keyLabel}</Label>}
{keyLocked ? (
<div
@@ -174,7 +158,7 @@ export function WrapIfAdditionalTemplate<
<div
className={cn(
"col-span-12 space-y-2",
!keyIsReadonly && valueSpanClass,
!keyIsReadonly && "md:col-span-9",
)}
>
{!keyIsReadonly && displayLabel && (
-39
View File
@@ -1,39 +0,0 @@
import { SVGProps } from "react";
/**
* Skunk silhouette for the `skunk` object label.
*
* react-icons has no skunk in any of its packs. The usable stand-ins are
* either squirrels, which are indistinguishable from the `squirrel` label, or
* animals such as porcupine and hedgehog that are themselves Frigate+
* candidate labels.
*
* Adapted from "skunk silhouette" by dear_theophilus, published by Openclipart
* and released into the public domain, which permits reproduction,
* distribution and derivative works:
* https://openclipart.org/detail/170808/skunk-silhouette-by-dear_theophilus-170808
*
* Changes from the original: the unused Inkscape text region was dropped, the
* layer translate was folded into the viewBox, the viewBox was padded to give
* the same optical margin as the surrounding react-icons, and the fill was
* switched to currentColor. The white back stripe is negative space in a
* single path under the default nonzero fill rule, so no fill-rule override is
* needed here.
*
* Sized to sit alongside the react-icons set: currentColor fill and a 1em
* default box.
*/
export default function SkunkIcon(props: SVGProps<SVGSVGElement>) {
return (
<svg
xmlns="http://www.w3.org/2000/svg"
viewBox="96.87 93.174 110.58 109.81"
fill="currentColor"
height="1em"
width="1em"
{...props}
>
<path d="m169.58 196.93c-0.18864-0.85889 0.0134-1.3274 0.99603-2.31 0.67796-0.67797 1.7065-1.3304 2.2857-1.4498 1.3854-0.2857 5.2538-1.7692 5.8796-2.2549 0.27087-0.2102 0.4925-0.61406 0.4925-0.89746 0-0.77202-6.6659-6.0863-7.6343-6.0863-0.46161 0-2.0798 0.36441-3.596 0.80981-3.4618 1.0169-10.449 1.4599-16.39 1.0391-7.1408-0.50577-6.6473-0.58559-8.3439 1.3494-0.8327 0.94969-1.9642 2.5979-2.5144 3.6627-1.164 2.2525-4.5952 6.5163-5.8025 7.2106-1.0288 0.59154-4.5445 0.64844-5.9949 0.097-0.71722-0.27269-1.4467-0.28055-2.184-0.0235-2.4986 0.871-1.4597-1.341 1.2885-2.7437 0.78536-0.40084 1.9099-1.3016 2.499-2.0016 1.0163-1.2078 1.0634-1.4452 0.92116-4.6468-0.12622-2.8412-0.38301-3.9062-1.6262-6.7446-2.6443-6.0373-7.3573-11.099-12.678-13.617-1.5889-0.75179-2.62-0.93285-5.3302-0.93595-3.0016-0.004-3.6532-0.14511-6.107-1.3278-5.2109-2.5116-5.8227-4.8841-1.4913-5.7833 1.8591-0.38596 2.618-0.82052 4.4338-2.539 1.2049-1.1403 2.7581-2.3618 3.4516-2.7146 1.9684-1.001 7.7872-0.84521 13.816 0.37 5.7138 1.1517 10.339 1.3571 13.488 0.59905 1.1919-0.28691 4.6492-1.5446 7.683-2.7949 9.8002-4.0389 14.311-4.9373 19.109-3.806 1.4086 0.33208 2.7106 0.4572 2.8935 0.27806 1.0374-1.0164-1.1645-3.1382-6.6365-6.3947-5.6439-3.3588-9.8091-9.1231-10.764-14.897-0.60953-3.6839 0.72362-12.081 1.2923-13.596 0.56871-1.5152 1.4436-3.3754 1.9442-4.1338 2.9223-4.4276 8.177-9.1772 12.256-11.078 6.691-3.1177 17.754-2.3107 25.847 1.8855 3.5353 1.8329 6.7739 4.7994 8.0035 7.3309 1.3563 2.7924 2.3788 9.4802 1.6321 10.675-0.28831 0.46149-1.0187 1.9915-1.6231 3.4001-1.0066 2.3458-2.3392 4.3362-2.9009 4.3326-0.12475-0.00078-0.81827-1.1453-1.5412-2.5434-1.642-3.1756-6.3156-7.6992-7.9544-7.6992-0.58481 0-2.2156 0.52248-3.624 1.1611-3.1804 1.4421-4.0269 2.8569-3.7769 6.3127 0.24247 3.3521 2.1549 6.8946 9.8511 18.247 3.3307 4.9132 4.5143 10.219 3.7106 16.634-0.40898 3.2645-0.77579 4.5016-2.1396 7.2158-0.90527 1.8017-2.1169 3.8932-2.6924 4.6478-1.3686 1.7944-3.6318 10.202-4.0199 14.935-0.34632 4.2221-1.4143 6.7775-3.7479 8.9681l-1.5853 1.4881s-10.87 1.3087-11.076 0.36929zm-0.94988-19.482c5.4569-0.84327 10.316-2.9685 15.305-6.694 2.2799-1.7026 7.2867-9.9628 7.5372-11.17 1.1907-5.7355-0.81743-10.348-8.1457-18.709-1.1818-1.3484-3.251-4.3132-4.5981-6.5886 0 0-1.8246-3.0395-2.2503-4.734-0.4037-1.6068-0.24133-4.9643-0.24133-4.9643-0.0233-3.0587 1.7125-7.8176 2.7258-8.9913 2.4126-2.7945 5.1792-3.93 8.9395-3.6689 2.4539 0.17036 6.2631 1.6358 6.8904 2.6509 0.46463 0.75179 1.7776 0.45185 1.7776-0.40608 0-2.1062-2.1313-4.3793-5.8702-6.261-8.5709-4.3134-18.12-1.6112-22.089 6.2506-0.84198 1.6679-1.9752 7.8544-1.5778 9.9776 0.98137 5.2435 7.314 15.066 15.216 23.602 2.3474 2.5357 2.891 3.3814 3.2505 5.0579 0.62386 2.909 0.53762 3.9625-0.45679 5.5804-2.2494 3.6597-6.0764 5.9532-12.424 7.446-5.4931 1.2918-14.085 0.80251-19.932-1.135-2.8291-0.93745-3.2146-1.1799-3.3204-2.0877-0.26031-2.2347 5.8542-6.1292 12.294-7.8306 1.712-0.45228 3.469-1.013 3.9045-1.2461 2.613-1.3984-5.139-1.3894-10.001 0.0116-1.4244 0.41047-4.1726 1.3784-6.107 2.151-4.0916 1.6341-9.9725 3.2146-13.412 3.6046-1.9171 0.21734-3.2711 0.0654-6.6311-0.74437-6.6813-1.6101-8.8678-1.2892-6.6918 0.98197 1.1258 1.1751 6.0865 4.3046 6.8234 4.3046 0.22537 0 0.58888 0.3347 0.80781 0.74378 0.50815 0.94949 5.6856 4.2866 11.253 7.2529 3.5996 1.918 5.4022 2.5812 10.638 3.9141 3.4672 0.88264 7.7224 1.7278 9.456 1.8781 1.7336 0.15029 3.1675 0.30072 3.1864 0.33427 0.0189 0.0336 1.7032-0.1969 3.743-0.5121zm-55.67-16.07c0.0817-0.43098-0.25131-0.85888-0.89769-1.1534-0.8518-0.38811-1.1373-0.35853-1.6687 0.17289-0.53858 0.53858-0.55739 0.74197-0.11767 1.2718 0.67722 0.816 2.5119 0.61688 2.6841-0.29131zm7.5598-0.11521c0-0.95213-0.94275-1.7372-1.4622-1.2177-0.30143 0.30141 0.67899 2.2151 1.1348 2.2151 0.18008 0 0.32742-0.44882 0.32742-0.99738z" />
</svg>
);
}
@@ -20,26 +20,6 @@ function formatCalendarDay(day: Date): string {
return `${y}-${m}-${d}`;
}
function getTodayInTimezone(timezone?: string): {
year: number;
month: number;
day: number;
offset: number;
} {
const now = new Date();
const offset = Math.round(getUTCOffset(now, timezone));
// shifting by the offset makes the UTC getters read the timezone's wall clock
const wallClock = new Date(now.getTime() + offset * 60000);
return {
year: wallClock.getUTCFullYear(),
month: wallClock.getUTCMonth(),
day: wallClock.getUTCDate(),
offset,
};
}
type ReviewActivityCalendarProps = {
reviewSummary?: ReviewSummary;
recordingsSummary?: RecordingsSummary;
@@ -57,14 +37,12 @@ export default function ReviewActivityCalendar({
const [weekStartsOn] = useUserPersistence("weekStartsOn", 0);
const disabledDates = useMemo(() => {
// day cells are TZDate in `timezone`, so the cutoff must be a real instant
const { year, month, day, offset } = getTodayInTimezone(timezone);
// midday: ranges match by calendar day, so this dodges DST edges
const from = new Date(Date.UTC(year, month, day + 1, 12) - offset * 60000);
const to = new Date(from);
to.setFullYear(from.getFullYear() + 10);
return { from, to };
}, [timezone]);
const tomorrow = new Date();
tomorrow.setHours(tomorrow.getHours() + 24, -1, 0, 0);
const future = new Date();
future.setFullYear(tomorrow.getFullYear() + 10);
return { from: tomorrow, to: future };
}, []);
const modifiers = useMemo(() => {
const recordingsSet = new Set<string>();
@@ -204,25 +182,48 @@ export function TimezoneAwareCalendar({
};
}, [recordingsSummary]);
// callers pre-shift dates so the local clock reads `timezone`, so boundaries
// are built in local time rather than as instants
const { year, month, day } = useMemo(
() => getTodayInTimezone(timezone),
const timezoneOffset = useMemo(
() =>
timezone ? Math.round(getUTCOffset(new Date(), timezone)) : undefined,
[timezone],
);
const disabledDates = useMemo(() => {
// midday: ranges match by calendar day, so this dodges DST edges
const from = new Date(year, month, day + 1, 12);
const to = new Date(from);
to.setFullYear(from.getFullYear() + 10);
return { from, to };
}, [year, month, day]);
const tomorrow = new Date();
const today = useMemo(
() => new Date(year, month, day, 12),
[year, month, day],
);
if (timezoneOffset) {
tomorrow.setHours(
tomorrow.getHours() + 24,
tomorrow.getMinutes() + timezoneOffset,
0,
0,
);
} else {
tomorrow.setHours(tomorrow.getHours() + 24, -1, 0, 0);
}
const future = new Date();
future.setFullYear(tomorrow.getFullYear() + 10);
return { from: tomorrow, to: future };
}, [timezoneOffset]);
const today = useMemo(() => {
if (!timezoneOffset) {
return undefined;
}
const date = new Date();
const utc = Date.UTC(
date.getUTCFullYear(),
date.getUTCMonth(),
date.getUTCDate(),
date.getUTCHours(),
date.getUTCMinutes(),
date.getUTCSeconds(),
);
const todayUtc = new Date(utc);
todayUtc.setMinutes(todayUtc.getMinutes() + timezoneOffset, 0, 0);
return todayUtc;
}, [timezoneOffset]);
return (
<Calendar
+2 -24
View File
@@ -1,12 +1,9 @@
import { IconName } from "@/components/icons/IconPicker";
import SkunkIcon from "@/components/icons/SkunkIcon";
import { FrigateConfig } from "@/types/frigateConfig";
import { EventType } from "@/types/search";
import { BsPersonWalking } from "react-icons/bs";
import {
FaAmazon,
FaBaby,
FaBabyCarriage,
FaBicycle,
FaBus,
FaCarSide,
@@ -27,8 +24,6 @@ import {
FaUsps,
} from "react-icons/fa";
import {
GiBarbecue,
GiCow,
GiDeer,
GiFox,
GiGoat,
@@ -37,9 +32,7 @@ import {
GiPostStamp,
GiRabbit,
GiRaccoonHead,
GiRat,
GiSailboat,
GiSeatedMouse,
GiSoundWaves,
GiSquirrel,
} from "react-icons/gi";
@@ -47,7 +40,6 @@ import { LuBox, LuLassoSelect, LuScanBarcode } from "react-icons/lu";
import * as LuIcons from "react-icons/lu";
import { MdRecordVoiceOver } from "react-icons/md";
import { PiBirdFill } from "react-icons/pi";
import { HiMiniTruck } from "react-icons/hi2";
export function getAttributeLabels(config?: FrigateConfig) {
if (!config) {
@@ -82,12 +74,6 @@ export function getIconForLabel(
switch (label) {
// objects
case "baby":
return <FaBaby key={iconKey} className={className} />;
case "baby_stroller":
return <FaBabyCarriage key={iconKey} className={className} />;
case "bbq_grill":
return <GiBarbecue key={iconKey} className={className} />;
case "bear":
return <GiPolarBear key={iconKey} className={className} />;
case "bicycle":
@@ -104,8 +90,6 @@ export function getIconForLabel(
return <FaCarSide key={iconKey} className={className} />;
case "cat":
return <FaCat key={iconKey} className={className} />;
case "cow":
return <GiCow key={iconKey} className={className} />;
case "deer":
return <GiDeer key={iconKey} className={className} />;
case "animal":
@@ -114,8 +98,6 @@ export function getIconForLabel(
return <FaDog key={iconKey} className={className} />;
case "fox":
return <GiFox key={iconKey} className={className} />;
case "garbage_truck":
return <HiMiniTruck key={iconKey} className={className} />;
case "goat":
return <GiGoat key={iconKey} className={className} />;
case "horse":
@@ -132,22 +114,18 @@ export function getIconForLabel(
return <LuBox key={iconKey} className={className} />;
case "person":
return <BsPersonWalking key={iconKey} className={className} />;
case "possum":
return <GiSeatedMouse key={iconKey} className={className} />;
case "rabbit":
return <GiRabbit key={iconKey} className={className} />;
case "raccoon":
return <GiRaccoonHead key={iconKey} className={className} />;
case "robot_lawnmower":
return <FaHockeyPuck key={iconKey} className={className} />;
case "rodent":
return <GiRat key={iconKey} className={className} />;
case "sports_ball":
return <FaFootballBall key={iconKey} className={className} />;
case "skunk":
return <SkunkIcon key={iconKey} className={className} />;
case "squirrel":
return <GiSquirrel key={iconKey} className={className} />;
case "squirrel":
return <LuIcons.LuSquirrel key={iconKey} className={className} />;
case "umbrella":
return <FaUmbrella key={iconKey} className={className} />;
case "waste_bin":