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Author SHA1 Message Date
dependabot[bot]
d7de519a13
Merge ad3c8f3f25 into 097673b845 2025-11-14 23:42:08 +01:00
93 changed files with 1842 additions and 3035 deletions

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@ -1,6 +1,6 @@
The MIT License The MIT License
Copyright (c) 2025 Frigate LLC (Frigate™) Copyright (c) 2020 Blake Blackshear
Permission is hereby granted, free of charge, to any person obtaining a copy Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal of this software and associated documentation files (the "Software"), to deal

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@ -1,10 +1,8 @@
<p align="center"> <p align="center">
<img align="center" alt="logo" src="docs/static/img/branding/frigate.png"> <img align="center" alt="logo" src="docs/static/img/frigate.png">
</p> </p>
# Frigate NVR™ - Realtime Object Detection for IP Cameras # Frigate - NVR With Realtime Object Detection for IP Cameras
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
<a href="https://hosted.weblate.org/engage/frigate-nvr/"> <a href="https://hosted.weblate.org/engage/frigate-nvr/">
<img src="https://hosted.weblate.org/widget/frigate-nvr/language-badge.svg" alt="Translation status" /> <img src="https://hosted.weblate.org/widget/frigate-nvr/language-badge.svg" alt="Translation status" />
@ -14,7 +12,7 @@
A complete and local NVR designed for [Home Assistant](https://www.home-assistant.io) with AI object detection. Uses OpenCV and Tensorflow to perform realtime object detection locally for IP cameras. A complete and local NVR designed for [Home Assistant](https://www.home-assistant.io) with AI object detection. Uses OpenCV and Tensorflow to perform realtime object detection locally for IP cameras.
Use of a GPU or AI accelerator is highly recommended. AI accelerators will outperform even the best CPUs with very little overhead. See Frigate's supported [object detectors](https://docs.frigate.video/configuration/object_detectors/). Use of a GPU or AI accelerator such as a [Google Coral](https://coral.ai/products/) or [Hailo](https://hailo.ai/) is highly recommended. AI accelerators will outperform even the best CPUs with very little overhead.
- Tight integration with Home Assistant via a [custom component](https://github.com/blakeblackshear/frigate-hass-integration) - Tight integration with Home Assistant via a [custom component](https://github.com/blakeblackshear/frigate-hass-integration)
- Designed to minimize resource use and maximize performance by only looking for objects when and where it is necessary - Designed to minimize resource use and maximize performance by only looking for objects when and where it is necessary
@ -35,15 +33,6 @@ View the documentation at https://docs.frigate.video
If you would like to make a donation to support development, please use [Github Sponsors](https://github.com/sponsors/blakeblackshear). If you would like to make a donation to support development, please use [Github Sponsors](https://github.com/sponsors/blakeblackshear).
## License
This project is licensed under the **MIT License**.
- **Code:** The source code, configuration files, and documentation in this repository are available under the [MIT License](LICENSE). You are free to use, modify, and distribute the code as long as you include the original copyright notice.
- **Trademarks:** The "Frigate" name, the "Frigate NVR" brand, and the Frigate logo are **trademarks of Frigate LLC** and are **not** covered by the MIT License.
Please see our [Trademark Policy](TRADEMARK.md) for details on acceptable use of our brand assets.
## Screenshots ## Screenshots
### Live dashboard ### Live dashboard
@ -77,7 +66,3 @@ We use [Weblate](https://hosted.weblate.org/projects/frigate-nvr/) to support la
<a href="https://hosted.weblate.org/engage/frigate-nvr/"> <a href="https://hosted.weblate.org/engage/frigate-nvr/">
<img src="https://hosted.weblate.org/widget/frigate-nvr/multi-auto.svg" alt="Translation status" /> <img src="https://hosted.weblate.org/widget/frigate-nvr/multi-auto.svg" alt="Translation status" />
</a> </a>
---
**Copyright © 2025 Frigate LLC.**

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@ -1,58 +0,0 @@
# Trademark Policy
**Last Updated:** November 2025
This document outlines the policy regarding the use of the trademarks associated with the Frigate NVR project.
## 1. Our Trademarks
The following terms and visual assets are trademarks (the "Marks") of **Frigate LLC**:
- **Frigate™**
- **Frigate NVR™**
- **Frigate+™**
- **The Frigate Logo**
**Note on Common Law Rights:**
Frigate LLC asserts all common law rights in these Marks. The absence of a federal registration symbol (®) does not constitute a waiver of our intellectual property rights.
## 2. Interaction with the MIT License
The software in this repository is licensed under the [MIT License](LICENSE).
**Crucial Distinction:**
- The **Code** is free to use, modify, and distribute under the MIT terms.
- The **Brand (Trademarks)** is **NOT** licensed under MIT.
You may not use the Marks in any way that is not explicitly permitted by this policy or by written agreement with Frigate LLC.
## 3. Acceptable Use
You may use the Marks without prior written permission in the following specific contexts:
- **Referential Use:** To truthfully refer to the software (e.g., _"I use Frigate NVR for my home security"_).
- **Compatibility:** To indicate that your product or project works with the software (e.g., _"MyPlugin for Frigate NVR"_ or _"Compatible with Frigate"_).
- **Commentary:** In news articles, blog posts, or tutorials discussing the software.
## 4. Prohibited Use
You may **NOT** use the Marks in the following ways:
- **Commercial Products:** You may not use "Frigate" in the name of a commercial product, service, or app (e.g., selling an app named _"Frigate Viewer"_ is prohibited).
- **Implying Affiliation:** You may not use the Marks in a way that suggests your project is official, sponsored by, or endorsed by Frigate LLC.
- **Confusing Forks:** If you fork this repository to create a derivative work, you **must** remove the Frigate logo and rename your project to avoid user confusion. You cannot distribute a modified version of the software under the name "Frigate".
- **Domain Names:** You may not register domain names containing "Frigate" that are likely to confuse users (e.g., `frigate-official-support.com`).
## 5. The Logo
The Frigate logo (the bird icon) is a visual trademark.
- You generally **cannot** use the logo on your own website or product packaging without permission.
- If you are building a dashboard or integration that interfaces with Frigate, you may use the logo only to represent the Frigate node/service, provided it does not imply you _are_ Frigate.
## 6. Questions & Permissions
If you are unsure if your intended use violates this policy, or if you wish to request a specific license to use the Marks (e.g., for a partnership), please contact us at:
**help@frigate.video**

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@ -145,6 +145,6 @@ rm -rf /var/lib/apt/lists/*
# Install yq, for frigate-prepare and go2rtc echo source # Install yq, for frigate-prepare and go2rtc echo source
curl -fsSL \ curl -fsSL \
"https://github.com/mikefarah/yq/releases/download/v4.48.2/yq_linux_$(dpkg --print-architecture)" \ "https://github.com/mikefarah/yq/releases/download/v4.33.3/yq_linux_$(dpkg --print-architecture)" \
--output /usr/local/bin/yq --output /usr/local/bin/yq
chmod +x /usr/local/bin/yq chmod +x /usr/local/bin/yq

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@ -320,12 +320,6 @@ http {
add_header Cache-Control "public"; add_header Cache-Control "public";
} }
location /fonts/ {
access_log off;
expires 1y;
add_header Cache-Control "public";
}
location /locales/ { location /locales/ {
access_log off; access_log off;
add_header Cache-Control "public"; add_header Cache-Control "public";

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@ -25,7 +25,7 @@ Examples of available modules are:
- `frigate.app` - `frigate.app`
- `frigate.mqtt` - `frigate.mqtt`
- `frigate.object_detection.base` - `frigate.object_detection`
- `detector.<detector_name>` - `detector.<detector_name>`
- `watchdog.<camera_name>` - `watchdog.<camera_name>`
- `ffmpeg.<camera_name>.<sorted_roles>` NOTE: All FFmpeg logs are sent as `error` level. - `ffmpeg.<camera_name>.<sorted_roles>` NOTE: All FFmpeg logs are sent as `error` level.
@ -53,17 +53,6 @@ environment_vars:
VARIABLE_NAME: variable_value VARIABLE_NAME: variable_value
``` ```
#### TensorFlow Thread Configuration
If you encounter thread creation errors during classification model training, you can limit TensorFlow's thread usage:
```yaml
environment_vars:
TF_INTRA_OP_PARALLELISM_THREADS: "2" # Threads within operations (0 = use default)
TF_INTER_OP_PARALLELISM_THREADS: "2" # Threads between operations (0 = use default)
TF_DATASET_THREAD_POOL_SIZE: "2" # Data pipeline threads (0 = use default)
```
### `database` ### `database`
Tracked object and recording information is managed in a sqlite database at `/config/frigate.db`. If that database is deleted, recordings will be orphaned and will need to be cleaned up manually. They also won't show up in the Media Browser within Home Assistant. Tracked object and recording information is managed in a sqlite database at `/config/frigate.db`. If that database is deleted, recordings will be orphaned and will need to be cleaned up manually. They also won't show up in the Media Browser within Home Assistant.
@ -258,7 +247,7 @@ curl -X POST http://frigate_host:5000/api/config/save -d @config.json
if you'd like you can use your yaml config directly by using [`yq`](https://github.com/mikefarah/yq) to convert it to json: if you'd like you can use your yaml config directly by using [`yq`](https://github.com/mikefarah/yq) to convert it to json:
```bash ```bash
yq -o=json '.' config.yaml | curl -X POST 'http://frigate_host:5000/api/config/save?save_option=saveonly' --data-binary @- yq r -j config.yml | curl -X POST http://frigate_host:5000/api/config/save -d @-
``` ```
### Via Command Line ### Via Command Line

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@ -35,15 +35,6 @@ For object classification:
- Ideal when multiple attributes can coexist independently. - Ideal when multiple attributes can coexist independently.
- Example: Detecting if a `person` in a construction yard is wearing a helmet or not. - Example: Detecting if a `person` in a construction yard is wearing a helmet or not.
## Assignment Requirements
Sub labels and attributes are only assigned when both conditions are met:
1. **Threshold**: Each classification attempt must have a confidence score that meets or exceeds the configured `threshold` (default: `0.8`).
2. **Class Consensus**: After at least 3 classification attempts, 60% of attempts must agree on the same class label. If the consensus class is `none`, no assignment is made.
This two-step verification prevents false positives by requiring consistent predictions across multiple frames before assigning a sub label or attribute.
## Example use cases ## Example use cases
### Sub label ### Sub label
@ -75,18 +66,14 @@ classification:
## Training the model ## Training the model
Creating and training the model is done within the Frigate UI using the `Classification` page. The process consists of two steps: Creating and training the model is done within the Frigate UI using the `Classification` page.
### Step 1: Name and Define ### Getting Started
Enter a name for your model, select the object label to classify (e.g., `person`, `dog`, `car`), choose the classification type (sub label or attribute), and define your classes. Include a `none` class for objects that don't fit any specific category.
### Step 2: Assign Training Examples
The system will automatically generate example images from detected objects matching your selected label. You'll be guided through each class one at a time to select which images represent that class. Any images not assigned to a specific class will automatically be assigned to `none` when you complete the last class. Once all images are processed, training will begin automatically.
When choosing which objects to classify, start with a small number of visually distinct classes and ensure your training samples match camera viewpoints and distances typical for those objects. When choosing which objects to classify, start with a small number of visually distinct classes and ensure your training samples match camera viewpoints and distances typical for those objects.
// TODO add this section once UI is implemented. Explain process of selecting objects and curating training examples.
### Improving the Model ### Improving the Model
- **Problem framing**: Keep classes visually distinct and relevant to the chosen object types. - **Problem framing**: Keep classes visually distinct and relevant to the chosen object types.

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@ -48,23 +48,13 @@ classification:
## Training the model ## Training the model
Creating and training the model is done within the Frigate UI using the `Classification` page. The process consists of three steps: Creating and training the model is done within the Frigate UI using the `Classification` page.
### Step 1: Name and Define ### Getting Started
Enter a name for your model and define at least 2 classes (states) that represent mutually exclusive states. For example, `open` and `closed` for a door, or `on` and `off` for lights. When choosing a portion of the camera frame for state classification, it is important to make the crop tight around the area of interest to avoid extra signals unrelated to what is being classified.
### Step 2: Select the Crop Area // TODO add this section once UI is implemented. Explain process of selecting a crop.
Choose one or more cameras and draw a rectangle over the area of interest for each camera. The crop should be tight around the region you want to classify to avoid extra signals unrelated to what is being classified. You can drag and resize the rectangle to adjust the crop area.
### Step 3: Assign Training Examples
The system will automatically generate example images from your camera feeds. You'll be guided through each class one at a time to select which images represent that state.
**Important**: All images must be assigned to a state before training can begin. This includes images that may not be optimal, such as when people temporarily block the view, sun glare is present, or other distractions occur. Assign these images to the state that is actually present (based on what you know the state to be), not based on the distraction. This training helps the model correctly identify the state even when such conditions occur during inference.
Once all images are assigned, training will begin automatically.
### Improving the Model ### Improving the Model

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@ -70,7 +70,7 @@ You should have at least 8 GB of RAM available (or VRAM if running on GPU) to ru
genai: genai:
provider: ollama provider: ollama
base_url: http://localhost:11434 base_url: http://localhost:11434
model: qwen3-vl:4b model: llava:7b
``` ```
## Google Gemini ## Google Gemini

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@ -35,18 +35,19 @@ Each model is available in multiple parameter sizes (3b, 4b, 8b, etc.). Larger s
:::tip :::tip
If you are trying to use a single model for Frigate and HomeAssistant, it will need to support vision and tools calling. qwen3-VL supports vision and tools simultaneously in Ollama. If you are trying to use a single model for Frigate and HomeAssistant, it will need to support vision and tools calling. https://github.com/skye-harris/ollama-modelfiles contains optimized model configs for this task.
::: :::
The following models are recommended: The following models are recommended:
| Model | Notes | | Model | Notes |
| ----------------- | -------------------------------------------------------------------- | | ----------------- | ----------------------------------------------------------- |
| `qwen3-vl` | Strong visual and situational understanding, higher vram requirement | | `qwen3-vl` | Strong visual and situational understanding |
| `Intern3.5VL` | Relatively fast with good vision comprehension | | `Intern3.5VL` | Relatively fast with good vision comprehension |
| `gemma3` | Strong frame-to-frame understanding, slower inference times | | `gemma3` | Strong frame-to-frame understanding, slower inference times |
| `qwen2.5-vl` | Fast but capable model with good vision comprehension | | `qwen2.5-vl` | Fast but capable model with good vision comprehension |
| `llava-phi3` | Lightweight and fast model with vision comprehension |
:::note :::note

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@ -3,18 +3,18 @@ id: license_plate_recognition
title: License Plate Recognition (LPR) title: License Plate Recognition (LPR)
--- ---
Frigate can recognize license plates on vehicles and automatically add the detected characters to the `recognized_license_plate` field or a [known](#matching) name as a `sub_label` to tracked objects of type `car` or `motorcycle`. A common use case may be to read the license plates of cars pulling into a driveway or cars passing by on a street. Frigate can recognize license plates on vehicles and automatically add the detected characters to the `recognized_license_plate` field or a known name as a `sub_label` to tracked objects of type `car` or `motorcycle`. A common use case may be to read the license plates of cars pulling into a driveway or cars passing by on a street.
LPR works best when the license plate is clearly visible to the camera. For moving vehicles, Frigate continuously refines the recognition process, keeping the most confident result. When a vehicle becomes stationary, LPR continues to run for a short time after to attempt recognition. LPR works best when the license plate is clearly visible to the camera. For moving vehicles, Frigate continuously refines the recognition process, keeping the most confident result. When a vehicle becomes stationary, LPR continues to run for a short time after to attempt recognition.
When a plate is recognized, the details are: When a plate is recognized, the details are:
- Added as a `sub_label` (if [known](#matching)) or the `recognized_license_plate` field (if unknown) to a tracked object. - Added as a `sub_label` (if known) or the `recognized_license_plate` field (if unknown) to a tracked object.
- Viewable in the Details pane in Review/History. - Viewable in the Review Item Details pane in Review (sub labels).
- Viewable in the Tracked Object Details pane in Explore (sub labels and recognized license plates). - Viewable in the Tracked Object Details pane in Explore (sub labels and recognized license plates).
- Filterable through the More Filters menu in Explore. - Filterable through the More Filters menu in Explore.
- Published via the `frigate/events` MQTT topic as a `sub_label` ([known](#matching)) or `recognized_license_plate` (unknown) for the `car` or `motorcycle` tracked object. - Published via the `frigate/events` MQTT topic as a `sub_label` (known) or `recognized_license_plate` (unknown) for the `car` or `motorcycle` tracked object.
- Published via the `frigate/tracked_object_update` MQTT topic with `name` (if [known](#matching)) and `plate`. - Published via the `frigate/tracked_object_update` MQTT topic with `name` (if known) and `plate`.
## Model Requirements ## Model Requirements
@ -31,7 +31,6 @@ In the default mode, Frigate's LPR needs to first detect a `car` or `motorcycle`
## Minimum System Requirements ## Minimum System Requirements
License plate recognition works by running AI models locally on your system. The YOLOv9 plate detector model and the OCR models ([PaddleOCR](https://github.com/PaddlePaddle/PaddleOCR)) are relatively lightweight and can run on your CPU or GPU, depending on your configuration. At least 4GB of RAM is required. License plate recognition works by running AI models locally on your system. The YOLOv9 plate detector model and the OCR models ([PaddleOCR](https://github.com/PaddlePaddle/PaddleOCR)) are relatively lightweight and can run on your CPU or GPU, depending on your configuration. At least 4GB of RAM is required.
## Configuration ## Configuration
License plate recognition is disabled by default. Enable it in your config file: License plate recognition is disabled by default. Enable it in your config file:
@ -74,8 +73,8 @@ Fine-tune the LPR feature using these optional parameters at the global level of
- Default: `small` - Default: `small`
- This can be `small` or `large`. - This can be `small` or `large`.
- The `small` model is fast and identifies groups of Latin and Chinese characters. - The `small` model is fast and identifies groups of Latin and Chinese characters.
- The `large` model identifies Latin characters only, and uses an enhanced text detector to find characters on multi-line plates. It is significantly slower than the `small` model. - The `large` model identifies Latin characters only, but uses an enhanced text detector and is more capable at finding characters on multi-line plates. It is significantly slower than the `small` model. Note that using the `large` model does not improve _text recognition_, but it may improve _text detection_.
- If your country or region does not use multi-line plates, you should use the `small` model as performance is much better for single-line plates. - For most users, the `small` model is recommended.
### Recognition ### Recognition
@ -178,7 +177,7 @@ lpr:
:::note :::note
If a camera is configured to detect `car` or `motorcycle` but you don't want Frigate to run LPR for that camera, disable LPR at the camera level: If you want to detect cars on cameras but don't want to use resources to run LPR on those cars, you should disable LPR for those specific cameras.
```yaml ```yaml
cameras: cameras:
@ -306,7 +305,7 @@ With this setup:
- Review items will always be classified as a `detection`. - Review items will always be classified as a `detection`.
- Snapshots will always be saved. - Snapshots will always be saved.
- Zones and object masks are **not** used. - Zones and object masks are **not** used.
- The `frigate/events` MQTT topic will **not** publish tracked object updates with the license plate bounding box and score, though `frigate/reviews` will publish if recordings are enabled. If a plate is recognized as a [known](#matching) plate, publishing will occur with an updated `sub_label` field. If characters are recognized, publishing will occur with an updated `recognized_license_plate` field. - The `frigate/events` MQTT topic will **not** publish tracked object updates with the license plate bounding box and score, though `frigate/reviews` will publish if recordings are enabled. If a plate is recognized as a known plate, publishing will occur with an updated `sub_label` field. If characters are recognized, publishing will occur with an updated `recognized_license_plate` field.
- License plate snapshots are saved at the highest-scoring moment and appear in Explore. - License plate snapshots are saved at the highest-scoring moment and appear in Explore.
- Debug view will not show `license_plate` bounding boxes. - Debug view will not show `license_plate` bounding boxes.

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@ -214,42 +214,6 @@ For restreamed cameras, go2rtc remains active but does not use system resources
Note that disabling a camera through the config file (`enabled: False`) removes all related UI elements, including historical footage access. To retain access while disabling the camera, keep it enabled in the config and use the UI or MQTT to disable it temporarily. Note that disabling a camera through the config file (`enabled: False`) removes all related UI elements, including historical footage access. To retain access while disabling the camera, keep it enabled in the config and use the UI or MQTT to disable it temporarily.
### Live player error messages
When your browser runs into problems playing back your camera streams, it will log short error messages to the browser console. They indicate playback, codec, or network issues on the client/browser side, not something server side with Frigate itself. Below are the common messages you may see and simple actions you can take to try to resolve them.
- **startup**
- What it means: The player failed to initialize or connect to the live stream (network or startup error).
- What to try: Reload the Live view or click _Reset_. Verify `go2rtc` is running and the camera stream is reachable. Try switching to a different stream from the Live UI dropdown (if available) or use a different browser.
- Possible console messages from the player code:
- `Error opening MediaSource.`
- `Browser reported a network error.`
- `Max error count ${errorCount} exceeded.` (the numeric value will vary)
- **mse-decode**
- What it means: The browser reported a decoding error while trying to play the stream, which usually is a result of a codec incompatibility or corrupted frames.
- What to try: Ensure your camera/restream is using H.264 video and AAC audio (these are the most compatible). If your camera uses a non-standard audio codec, configure `go2rtc` to transcode the stream to AAC. Try another browser (some browsers have stricter MSE/codec support) and, for iPhone, ensure you're on iOS 17.1 or newer.
- Possible console messages from the player code:
- `Safari cannot open MediaSource.`
- `Safari reported InvalidStateError.`
- `Safari reported decoding errors.`
- **stalled**
- What it means: Playback has stalled because the player has fallen too far behind live (extended buffering or no data arriving).
- What to try: This is usually indicative of the browser struggling to decode too many high-resolution streams at once. Try selecting a lower-bandwidth stream (substream), reduce the number of live streams open, improve the network connection, or lower the camera resolution. Also check your camera's keyframe (I-frame) interval — shorter intervals make playback start and recover faster. You can also try increasing the timeout value in the UI pane of Frigate's settings.
- Possible console messages from the player code:
- `Buffer time (10 seconds) exceeded, browser may not be playing media correctly.`
- `Media playback has stalled after <n> seconds due to insufficient buffering or a network interruption.` (the seconds value will vary)
## Live view FAQ ## Live view FAQ
1. **Why don't I have audio in my Live view?** 1. **Why don't I have audio in my Live view?**
@ -313,38 +277,3 @@ When your browser runs into problems playing back your camera streams, it will l
7. **My camera streams have lots of visual artifacts / distortion.** 7. **My camera streams have lots of visual artifacts / distortion.**
Some cameras don't include the hardware to support multiple connections to the high resolution stream, and this can cause unexpected behavior. In this case it is recommended to [restream](./restream.md) the high resolution stream so that it can be used for live view and recordings. Some cameras don't include the hardware to support multiple connections to the high resolution stream, and this can cause unexpected behavior. In this case it is recommended to [restream](./restream.md) the high resolution stream so that it can be used for live view and recordings.
8. **Why does my camera stream switch aspect ratios on the Live dashboard?**
Your camera may change aspect ratios on the dashboard because Frigate uses different streams for different purposes. With go2rtc and Smart Streaming, Frigate shows a static image from the `detect` stream when no activity is present, and switches to the live stream when motion is detected. The camera image will change size if your streams use different aspect ratios.
To prevent this, make the `detect` stream match the go2rtc live stream's aspect ratio (resolution does not need to match, just the aspect ratio). You can either adjust the camera's output resolution or set the `width` and `height` values in your config's `detect` section to a resolution with an aspect ratio that matches.
Example: Resolutions from two streams
- Mismatched (may cause aspect ratio switching on the dashboard):
- Live/go2rtc stream: 1920x1080 (16:9)
- Detect stream: 640x352 (~1.82:1, not 16:9)
- Matched (prevents switching):
- Live/go2rtc stream: 1920x1080 (16:9)
- Detect stream: 640x360 (16:9)
You can update the detect settings in your camera config to match the aspect ratio of your go2rtc live stream. For example:
```yaml
cameras:
front_door:
detect:
width: 640
height: 360 # set this to 360 instead of 352
ffmpeg:
inputs:
- path: rtsp://127.0.0.1:8554/front_door # main stream 1920x1080
roles:
- record
- path: rtsp://127.0.0.1:8554/front_door_sub # sub stream 640x352
roles:
- detect
```

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@ -3,8 +3,6 @@ id: object_detectors
title: Object Detectors title: Object Detectors
--- ---
import CommunityBadge from '@site/src/components/CommunityBadge';
# Supported Hardware # Supported Hardware
:::info :::info
@ -15,8 +13,8 @@ Frigate supports multiple different detectors that work on different types of ha
- [Coral EdgeTPU](#edge-tpu-detector): The Google Coral EdgeTPU is available in USB and m.2 format allowing for a wide range of compatibility with devices. - [Coral EdgeTPU](#edge-tpu-detector): The Google Coral EdgeTPU is available in USB and m.2 format allowing for a wide range of compatibility with devices.
- [Hailo](#hailo-8): The Hailo8 and Hailo8L AI Acceleration module is available in m.2 format with a HAT for RPi devices, offering a wide range of compatibility with devices. - [Hailo](#hailo-8): The Hailo8 and Hailo8L AI Acceleration module is available in m.2 format with a HAT for RPi devices, offering a wide range of compatibility with devices.
- <CommunityBadge /> [MemryX](#memryx-mx3): The MX3 Acceleration module is available in m.2 format, offering broad compatibility across various platforms. - [MemryX](#memryx-mx3): The MX3 Acceleration module is available in m.2 format, offering broad compatibility across various platforms.
- <CommunityBadge /> [DeGirum](#degirum): Service for using hardware devices in the cloud or locally. Hardware and models provided on the cloud on [their website](https://hub.degirum.com). - [DeGirum](#degirum): Service for using hardware devices in the cloud or locally. Hardware and models provided on the cloud on [their website](https://hub.degirum.com).
**AMD** **AMD**
@ -36,16 +34,16 @@ Frigate supports multiple different detectors that work on different types of ha
- [ONNX](#onnx): TensorRT will automatically be detected and used as a detector in the `-tensorrt` Frigate image when a supported ONNX model is configured. - [ONNX](#onnx): TensorRT will automatically be detected and used as a detector in the `-tensorrt` Frigate image when a supported ONNX model is configured.
**Nvidia Jetson** <CommunityBadge /> **Nvidia Jetson**
- [TensortRT](#nvidia-tensorrt-detector): TensorRT can run on Jetson devices, using one of many default models. - [TensortRT](#nvidia-tensorrt-detector): TensorRT can run on Jetson devices, using one of many default models.
- [ONNX](#onnx): TensorRT will automatically be detected and used as a detector in the `-tensorrt-jp6` Frigate image when a supported ONNX model is configured. - [ONNX](#onnx): TensorRT will automatically be detected and used as a detector in the `-tensorrt-jp6` Frigate image when a supported ONNX model is configured.
**Rockchip** <CommunityBadge /> **Rockchip**
- [RKNN](#rockchip-platform): RKNN models can run on Rockchip devices with included NPUs. - [RKNN](#rockchip-platform): RKNN models can run on Rockchip devices with included NPUs.
**Synaptics** <CommunityBadge /> **Synaptics**
- [Synaptics](#synaptics): synap models can run on Synaptics devices(e.g astra machina) with included NPUs. - [Synaptics](#synaptics): synap models can run on Synaptics devices(e.g astra machina) with included NPUs.
@ -964,6 +962,7 @@ model:
# path: /config/yolov9.zip # path: /config/yolov9.zip
# The .zip file must contain: # The .zip file must contain:
# ├── yolov9.dfp (a file ending with .dfp) # ├── yolov9.dfp (a file ending with .dfp)
# └── yolov9_post.onnx (optional; only if the model includes a cropped post-processing network)
``` ```
#### YOLOX #### YOLOX

View File

@ -246,7 +246,7 @@ birdseye:
# Optional: ffmpeg configuration # Optional: ffmpeg configuration
# More information about presets at https://docs.frigate.video/configuration/ffmpeg_presets # More information about presets at https://docs.frigate.video/configuration/ffmpeg_presets
ffmpeg: ffmpeg:
# Optional: ffmpeg binary path (default: shown below) # Optional: ffmpeg binry path (default: shown below)
# can also be set to `7.0` or `5.0` to specify one of the included versions # can also be set to `7.0` or `5.0` to specify one of the included versions
# or can be set to any path that holds `bin/ffmpeg` & `bin/ffprobe` # or can be set to any path that holds `bin/ffmpeg` & `bin/ffprobe`
path: "default" path: "default"

View File

@ -141,7 +141,7 @@ Triggers are best configured through the Frigate UI.
Check the `Add Attribute` box to add the trigger's internal ID (e.g., "red_car_alert") to a data attribute on the tracked object that can be processed via the API or MQTT. Check the `Add Attribute` box to add the trigger's internal ID (e.g., "red_car_alert") to a data attribute on the tracked object that can be processed via the API or MQTT.
5. Save the trigger to update the configuration and store the embedding in the database. 5. Save the trigger to update the configuration and store the embedding in the database.
When a trigger fires, the UI highlights the trigger with a blue dot for 3 seconds for easy identification. Additionally, the UI will show the last date/time and tracked object ID that activated your trigger. The last triggered timestamp is not saved to the database or persisted through restarts of Frigate. When a trigger fires, the UI highlights the trigger with a blue dot for 3 seconds for easy identification.
### Usage and Best Practices ### Usage and Best Practices

View File

@ -3,8 +3,6 @@ id: hardware
title: Recommended hardware title: Recommended hardware
--- ---
import CommunityBadge from '@site/src/components/CommunityBadge';
## Cameras ## Cameras
Cameras that output H.264 video and AAC audio will offer the most compatibility with all features of Frigate and Home Assistant. It is also helpful if your camera supports multiple substreams to allow different resolutions to be used for detection, streaming, and recordings without re-encoding. Cameras that output H.264 video and AAC audio will offer the most compatibility with all features of Frigate and Home Assistant. It is also helpful if your camera supports multiple substreams to allow different resolutions to be used for detection, streaming, and recordings without re-encoding.
@ -61,7 +59,7 @@ Frigate supports multiple different detectors that work on different types of ha
- [Supports primarily ssdlite and mobilenet model architectures](../../configuration/object_detectors#edge-tpu-detector) - [Supports primarily ssdlite and mobilenet model architectures](../../configuration/object_detectors#edge-tpu-detector)
- <CommunityBadge /> [MemryX](#memryx-mx3): The MX3 M.2 accelerator module is available in m.2 format allowing for a wide range of compatibility with devices. - [MemryX](#memryx-mx3): The MX3 M.2 accelerator module is available in m.2 format allowing for a wide range of compatibility with devices.
- [Supports many model architectures](../../configuration/object_detectors#memryx-mx3) - [Supports many model architectures](../../configuration/object_detectors#memryx-mx3)
- Runs best with tiny, small, or medium-size models - Runs best with tiny, small, or medium-size models
@ -86,26 +84,32 @@ Frigate supports multiple different detectors that work on different types of ha
**Nvidia** **Nvidia**
- [TensortRT](#tensorrt---nvidia-gpu): TensorRT can run on Nvidia GPUs to provide efficient object detection. - [TensortRT](#tensorrt---nvidia-gpu): TensorRT can run on Nvidia GPUs and Jetson devices.
- [Supports majority of model architectures via ONNX](../../configuration/object_detectors#onnx-supported-models) - [Supports majority of model architectures via ONNX](../../configuration/object_detectors#onnx-supported-models)
- Runs well with any size models including large - Runs well with any size models including large
- <CommunityBadge /> [Jetson](#nvidia-jetson): Jetson devices are supported via the TensorRT or ONNX detectors when running Jetpack 6. **Rockchip**
**Rockchip** <CommunityBadge />
- [RKNN](#rockchip-platform): RKNN models can run on Rockchip devices with included NPUs to provide efficient object detection. - [RKNN](#rockchip-platform): RKNN models can run on Rockchip devices with included NPUs to provide efficient object detection.
- [Supports limited model architectures](../../configuration/object_detectors#choosing-a-model) - [Supports limited model architectures](../../configuration/object_detectors#choosing-a-model)
- Runs best with tiny or small size models - Runs best with tiny or small size models
- Runs efficiently on low power hardware - Runs efficiently on low power hardware
**Synaptics** <CommunityBadge /> **Synaptics**
- [Synaptics](#synaptics): synap models can run on Synaptics devices(e.g astra machina) with included NPUs to provide efficient object detection. - [Synaptics](#synaptics): synap models can run on Synaptics devices(e.g astra machina) with included NPUs to provide efficient object detection.
::: :::
### Synaptics
- **Synaptics** Default model is **mobilenet**
| Name | Synaptics SL1680 Inference Time |
| ---------------- | ------------------------------- |
| ssd mobilenet | ~ 25 ms |
| yolov5m | ~ 118 ms |
### Hailo-8 ### Hailo-8
Frigate supports both the Hailo-8 and Hailo-8L AI Acceleration Modules on compatible hardware platforms—including the Raspberry Pi 5 with the PCIe hat from the AI kit. The Hailo detector integration in Frigate automatically identifies your hardware type and selects the appropriate default model when a custom model isnt provided. Frigate supports both the Hailo-8 and Hailo-8L AI Acceleration Modules on compatible hardware platforms—including the Raspberry Pi 5 with the PCIe hat from the AI kit. The Hailo detector integration in Frigate automatically identifies your hardware type and selects the appropriate default model when a custom model isnt provided.
@ -257,7 +261,7 @@ Inference speeds may vary depending on the host platform. The above data was mea
### Nvidia Jetson ### Nvidia Jetson
Jetson devices are supported via the TensorRT or ONNX detectors when running Jetpack 6. It will [make use of the Jetson's hardware media engine](/configuration/hardware_acceleration_video#nvidia-jetson-orin-agx-orin-nx-orin-nano-xavier-agx-xavier-nx-tx2-tx1-nano) when configured with the [appropriate presets](/configuration/ffmpeg_presets#hwaccel-presets), and will make use of the Jetson's GPU and DLA for object detection when configured with the [TensorRT detector](/configuration/object_detectors#nvidia-tensorrt-detector). Frigate supports all Jetson boards, from the inexpensive Jetson Nano to the powerful Jetson Orin AGX. It will [make use of the Jetson's hardware media engine](/configuration/hardware_acceleration_video#nvidia-jetson-orin-agx-orin-nx-orin-nano-xavier-agx-xavier-nx-tx2-tx1-nano) when configured with the [appropriate presets](/configuration/ffmpeg_presets#hwaccel-presets), and will make use of the Jetson's GPU and DLA for object detection when configured with the [TensorRT detector](/configuration/object_detectors#nvidia-tensorrt-detector).
Inference speed will vary depending on the YOLO model, jetson platform and jetson nvpmodel (GPU/DLA/EMC clock speed). It is typically 20-40 ms for most models. The DLA is more efficient than the GPU, but not faster, so using the DLA will reduce power consumption but will slightly increase inference time. Inference speed will vary depending on the YOLO model, jetson platform and jetson nvpmodel (GPU/DLA/EMC clock speed). It is typically 20-40 ms for most models. The DLA is more efficient than the GPU, but not faster, so using the DLA will reduce power consumption but will slightly increase inference time.
@ -278,15 +282,6 @@ Frigate supports hardware video processing on all Rockchip boards. However, hard
The inference time of a rk3588 with all 3 cores enabled is typically 25-30 ms for yolo-nas s. The inference time of a rk3588 with all 3 cores enabled is typically 25-30 ms for yolo-nas s.
### Synaptics
- **Synaptics** Default model is **mobilenet**
| Name | Synaptics SL1680 Inference Time |
| ------------- | ------------------------------- |
| ssd mobilenet | ~ 25 ms |
| yolov5m | ~ 118 ms |
## What does Frigate use the CPU for and what does it use a detector for? (ELI5 Version) ## What does Frigate use the CPU for and what does it use a detector for? (ELI5 Version)
This is taken from a [user question on reddit](https://www.reddit.com/r/homeassistant/comments/q8mgau/comment/hgqbxh5/?utm_source=share&utm_medium=web2x&context=3). Modified slightly for clarity. This is taken from a [user question on reddit](https://www.reddit.com/r/homeassistant/comments/q8mgau/comment/hgqbxh5/?utm_source=share&utm_medium=web2x&context=3). Modified slightly for clarity.

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@ -56,7 +56,7 @@ services:
volumes: volumes:
- /path/to/your/config:/config - /path/to/your/config:/config
- /path/to/your/storage:/media/frigate - /path/to/your/storage:/media/frigate
- type: tmpfs # Recommended: 1GB of memory - type: tmpfs # Optional: 1GB of memory, reduces SSD/SD Card wear
target: /tmp/cache target: /tmp/cache
tmpfs: tmpfs:
size: 1000000000 size: 1000000000
@ -310,7 +310,7 @@ services:
- /etc/localtime:/etc/localtime:ro - /etc/localtime:/etc/localtime:ro
- /path/to/your/config:/config - /path/to/your/config:/config
- /path/to/your/storage:/media/frigate - /path/to/your/storage:/media/frigate
- type: tmpfs # Recommended: 1GB of memory - type: tmpfs # Optional: 1GB of memory, reduces SSD/SD Card wear
target: /tmp/cache target: /tmp/cache
tmpfs: tmpfs:
size: 1000000000 size: 1000000000

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@ -159,44 +159,11 @@ Message published for updates to tracked object metadata, for example:
} }
``` ```
#### Object Classification Update
Message published when [object classification](/configuration/custom_classification/object_classification) reaches consensus on a classification result.
**Sub label type:**
```json
{
"type": "classification",
"id": "1607123955.475377-mxklsc",
"camera": "front_door_cam",
"timestamp": 1607123958.748393,
"model": "person_classifier",
"sub_label": "delivery_person",
"score": 0.87
}
```
**Attribute type:**
```json
{
"type": "classification",
"id": "1607123955.475377-mxklsc",
"camera": "front_door_cam",
"timestamp": 1607123958.748393,
"model": "helmet_detector",
"attribute": "yes",
"score": 0.92
}
```
### `frigate/reviews` ### `frigate/reviews`
Message published for each changed review item. The first message is published when the `detection` or `alert` is initiated. Message published for each changed review item. The first message is published when the `detection` or `alert` is initiated.
An `update` with the same ID will be published when: An `update` with the same ID will be published when:
- The severity changes from `detection` to `alert` - The severity changes from `detection` to `alert`
- Additional objects are detected - Additional objects are detected
- An object is recognized via face, lpr, etc. - An object is recognized via face, lpr, etc.
@ -341,11 +308,6 @@ Publishes transcribed text for audio detected on this camera.
**NOTE:** Requires audio detection and transcription to be enabled **NOTE:** Requires audio detection and transcription to be enabled
### `frigate/<camera_name>/classification/<model_name>`
Publishes the current state detected by a state classification model for the camera. The topic name includes the model name as configured in your classification settings.
The published value is the detected state class name (e.g., `open`, `closed`, `on`, `off`). The state is only published when it changes, helping to reduce unnecessary MQTT traffic.
### `frigate/<camera_name>/enabled/set` ### `frigate/<camera_name>/enabled/set`
Topic to turn Frigate's processing of a camera on and off. Expected values are `ON` and `OFF`. Topic to turn Frigate's processing of a camera on and off. Expected values are `ON` and `OFF`.

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@ -10,7 +10,7 @@ const config: Config = {
baseUrl: "/", baseUrl: "/",
onBrokenLinks: "throw", onBrokenLinks: "throw",
onBrokenMarkdownLinks: "warn", onBrokenMarkdownLinks: "warn",
favicon: "img/branding/favicon.ico", favicon: "img/favicon.ico",
organizationName: "blakeblackshear", organizationName: "blakeblackshear",
projectName: "frigate", projectName: "frigate",
themes: [ themes: [
@ -116,8 +116,8 @@ const config: Config = {
title: "Frigate", title: "Frigate",
logo: { logo: {
alt: "Frigate", alt: "Frigate",
src: "img/branding/logo.svg", src: "img/logo.svg",
srcDark: "img/branding/logo-dark.svg", srcDark: "img/logo-dark.svg",
}, },
items: [ items: [
{ {
@ -170,7 +170,7 @@ const config: Config = {
], ],
}, },
], ],
copyright: `Copyright © ${new Date().getFullYear()} Frigate LLC`, copyright: `Copyright © ${new Date().getFullYear()} Blake Blackshear`,
}, },
}, },
plugins: [ plugins: [

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@ -1,23 +0,0 @@
import React from "react";
export default function CommunityBadge() {
return (
<span
title="This detector is maintained by community members who provide code, maintenance, and support. See the contributing boards documentation for more information."
style={{
display: "inline-block",
backgroundColor: "#f1f3f5",
color: "#24292f",
fontSize: "11px",
fontWeight: 600,
padding: "2px 6px",
borderRadius: "3px",
border: "1px solid #d1d9e0",
marginLeft: "4px",
cursor: "help",
}}
>
Community Supported
</span>
);
}

View File

@ -1,30 +0,0 @@
# COPYRIGHT AND TRADEMARK NOTICE
The images, logos, and icons contained in this directory (the "Brand Assets") are
proprietary to Frigate LLC and are NOT covered by the MIT License governing the
rest of this repository.
1. TRADEMARK STATUS
The "Frigate" name and the accompanying logo are common law trademarks™ of
Frigate LLC. Frigate LLC reserves all rights to these marks.
2. LIMITED PERMISSION FOR USE
Permission is hereby granted to display these Brand Assets strictly for the
following purposes:
a. To execute the software interface on a local machine.
b. To identify the software in documentation or reviews (nominative use).
3. RESTRICTIONS
You may NOT:
a. Use these Brand Assets to represent a derivative work (fork) as an official
product of Frigate LLC.
b. Use these Brand Assets in a way that implies endorsement, sponsorship, or
commercial affiliation with Frigate LLC.
c. Modify or alter the Brand Assets.
If you fork this repository with the intent to distribute a modified or competing
version of the software, you must replace these Brand Assets with your own
original content.
ALL RIGHTS RESERVED.
Copyright (c) 2025 Frigate LLC.

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@ -179,36 +179,6 @@ def config(request: Request):
return JSONResponse(content=config) return JSONResponse(content=config)
@router.get("/config/raw_paths", dependencies=[Depends(require_role(["admin"]))])
def config_raw_paths(request: Request):
"""Admin-only endpoint that returns camera paths and go2rtc streams without credential masking."""
config_obj: FrigateConfig = request.app.frigate_config
raw_paths = {"cameras": {}, "go2rtc": {"streams": {}}}
# Extract raw camera ffmpeg input paths
for camera_name, camera in config_obj.cameras.items():
raw_paths["cameras"][camera_name] = {
"ffmpeg": {
"inputs": [
{"path": input.path, "roles": input.roles}
for input in camera.ffmpeg.inputs
]
}
}
# Extract raw go2rtc stream URLs
go2rtc_config = config_obj.go2rtc.model_dump(
mode="json", warnings="none", exclude_none=True
)
for stream_name, stream in go2rtc_config.get("streams", {}).items():
if stream is None:
continue
raw_paths["go2rtc"]["streams"][stream_name] = stream
return JSONResponse(content=raw_paths)
@router.get("/config/raw") @router.get("/config/raw")
def config_raw(): def config_raw():
config_file = find_config_file() config_file = find_config_file()

View File

@ -1781,8 +1781,9 @@ def create_trigger_embedding(
logger.debug( logger.debug(
f"Writing thumbnail for trigger with data {body.data} in {camera_name}." f"Writing thumbnail for trigger with data {body.data} in {camera_name}."
) )
except Exception: except Exception as e:
logger.exception( logger.error(e.with_traceback())
logger.error(
f"Failed to write thumbnail for trigger with data {body.data} in {camera_name}" f"Failed to write thumbnail for trigger with data {body.data} in {camera_name}"
) )
@ -1806,8 +1807,8 @@ def create_trigger_embedding(
status_code=200, status_code=200,
) )
except Exception: except Exception as e:
logger.exception("Error creating trigger embedding") logger.error(e.with_traceback())
return JSONResponse( return JSONResponse(
content={ content={
"success": False, "success": False,
@ -1916,8 +1917,9 @@ def update_trigger_embedding(
logger.debug( logger.debug(
f"Deleted thumbnail for trigger with data {trigger.data} in {camera_name}." f"Deleted thumbnail for trigger with data {trigger.data} in {camera_name}."
) )
except Exception: except Exception as e:
logger.exception( logger.error(e.with_traceback())
logger.error(
f"Failed to delete thumbnail for trigger with data {trigger.data} in {camera_name}" f"Failed to delete thumbnail for trigger with data {trigger.data} in {camera_name}"
) )
@ -1956,8 +1958,9 @@ def update_trigger_embedding(
logger.debug( logger.debug(
f"Writing thumbnail for trigger with data {body.data} in {camera_name}." f"Writing thumbnail for trigger with data {body.data} in {camera_name}."
) )
except Exception: except Exception as e:
logger.exception( logger.error(e.with_traceback())
logger.error(
f"Failed to write thumbnail for trigger with data {body.data} in {camera_name}" f"Failed to write thumbnail for trigger with data {body.data} in {camera_name}"
) )
@ -1969,8 +1972,8 @@ def update_trigger_embedding(
status_code=200, status_code=200,
) )
except Exception: except Exception as e:
logger.exception("Error updating trigger embedding") logger.error(e.with_traceback())
return JSONResponse( return JSONResponse(
content={ content={
"success": False, "success": False,
@ -2030,8 +2033,9 @@ def delete_trigger_embedding(
logger.debug( logger.debug(
f"Deleted thumbnail for trigger with data {trigger.data} in {camera_name}." f"Deleted thumbnail for trigger with data {trigger.data} in {camera_name}."
) )
except Exception: except Exception as e:
logger.exception( logger.error(e.with_traceback())
logger.error(
f"Failed to delete thumbnail for trigger with data {trigger.data} in {camera_name}" f"Failed to delete thumbnail for trigger with data {trigger.data} in {camera_name}"
) )
@ -2043,8 +2047,8 @@ def delete_trigger_embedding(
status_code=200, status_code=200,
) )
except Exception: except Exception as e:
logger.exception("Error deleting trigger embedding") logger.error(e.with_traceback())
return JSONResponse( return JSONResponse(
content={ content={
"success": False, "success": False,

View File

@ -762,15 +762,6 @@ async def recording_clip(
.order_by(Recordings.start_time.asc()) .order_by(Recordings.start_time.asc())
) )
if recordings.count() == 0:
return JSONResponse(
content={
"success": False,
"message": "No recordings found for the specified time range",
},
status_code=400,
)
file_name = sanitize_filename(f"playlist_{camera_name}_{start_ts}-{end_ts}.txt") file_name = sanitize_filename(f"playlist_{camera_name}_{start_ts}-{end_ts}.txt")
file_path = os.path.join(CACHE_DIR, file_name) file_path = os.path.join(CACHE_DIR, file_name)
with open(file_path, "w") as file: with open(file_path, "w") as file:
@ -849,7 +840,6 @@ async def vod_ts(camera_name: str, start_ts: float, end_ts: float):
clips = [] clips = []
durations = [] durations = []
min_duration_ms = 100 # Minimum 100ms to ensure at least one video frame
max_duration_ms = MAX_SEGMENT_DURATION * 1000 max_duration_ms = MAX_SEGMENT_DURATION * 1000
recording: Recordings recording: Recordings
@ -867,11 +857,11 @@ async def vod_ts(camera_name: str, start_ts: float, end_ts: float):
if recording.end_time > end_ts: if recording.end_time > end_ts:
duration -= int((recording.end_time - end_ts) * 1000) duration -= int((recording.end_time - end_ts) * 1000)
if duration < min_duration_ms: if duration <= 0:
# skip if the clip has no valid duration (too short to contain frames) # skip if the clip has no valid duration
continue continue
if min_duration_ms <= duration < max_duration_ms: if 0 < duration < max_duration_ms:
clip["keyFrameDurations"] = [duration] clip["keyFrameDurations"] = [duration]
clips.append(clip) clips.append(clip)
durations.append(duration) durations.append(duration)

View File

@ -136,7 +136,6 @@ class CameraMaintainer(threading.Thread):
self.ptz_metrics[name], self.ptz_metrics[name],
self.region_grids[name], self.region_grids[name],
self.stop_event, self.stop_event,
self.config.logger,
) )
self.camera_processes[config.name] = camera_process self.camera_processes[config.name] = camera_process
camera_process.start() camera_process.start()
@ -157,11 +156,7 @@ class CameraMaintainer(threading.Thread):
self.frame_manager.create(f"{config.name}_frame{i}", frame_size) self.frame_manager.create(f"{config.name}_frame{i}", frame_size)
capture_process = CameraCapture( capture_process = CameraCapture(
config, config, count, self.camera_metrics[name], self.stop_event
count,
self.camera_metrics[name],
self.stop_event,
self.config.logger,
) )
capture_process.daemon = True capture_process.daemon = True
self.capture_processes[name] = capture_process self.capture_processes[name] = capture_process

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@ -792,10 +792,6 @@ class FrigateConfig(FrigateBaseModel):
# copy over auth and proxy config in case auth needs to be enforced # copy over auth and proxy config in case auth needs to be enforced
safe_config["auth"] = config.get("auth", {}) safe_config["auth"] = config.get("auth", {})
safe_config["proxy"] = config.get("proxy", {}) safe_config["proxy"] = config.get("proxy", {})
# copy over database config for auth and so a new db is not created
safe_config["database"] = config.get("database", {})
return cls.parse_object(safe_config, **context) return cls.parse_object(safe_config, **context)
# Validate and return the config dict. # Validate and return the config dict.

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@ -132,15 +132,17 @@ class ReviewDescriptionProcessor(PostProcessorApi):
if image_source == ImageSourceEnum.recordings: if image_source == ImageSourceEnum.recordings:
duration = final_data["end_time"] - final_data["start_time"] duration = final_data["end_time"] - final_data["start_time"]
buffer_extension = min(5, duration * RECORDING_BUFFER_EXTENSION_PERCENT) buffer_extension = min(
10, max(2, duration * RECORDING_BUFFER_EXTENSION_PERCENT)
)
# Ensure minimum total duration for short review items # Ensure minimum total duration for short review items
# This provides better context for brief events # This provides better context for brief events
total_duration = duration + (2 * buffer_extension) total_duration = duration + (2 * buffer_extension)
if total_duration < MIN_RECORDING_DURATION: if total_duration < MIN_RECORDING_DURATION:
# Expand buffer to reach minimum duration, still respecting max of 5s per side # Expand buffer to reach minimum duration, still respecting max of 10s per side
additional_buffer_per_side = (MIN_RECORDING_DURATION - duration) / 2 additional_buffer_per_side = (MIN_RECORDING_DURATION - duration) / 2
buffer_extension = min(5, additional_buffer_per_side) buffer_extension = min(10, additional_buffer_per_side)
thumbs = self.get_recording_frames( thumbs = self.get_recording_frames(
camera, camera,

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@ -1,7 +1,6 @@
"""Real time processor that works with classification tflite models.""" """Real time processor that works with classification tflite models."""
import datetime import datetime
import json
import logging import logging
import os import os
from typing import Any from typing import Any
@ -22,7 +21,6 @@ from frigate.config.classification import (
) )
from frigate.const import CLIPS_DIR, MODEL_CACHE_DIR from frigate.const import CLIPS_DIR, MODEL_CACHE_DIR
from frigate.log import redirect_output_to_logger from frigate.log import redirect_output_to_logger
from frigate.types import TrackedObjectUpdateTypesEnum
from frigate.util.builtin import EventsPerSecond, InferenceSpeed, load_labels from frigate.util.builtin import EventsPerSecond, InferenceSpeed, load_labels
from frigate.util.object import box_overlaps, calculate_region from frigate.util.object import box_overlaps, calculate_region
@ -286,7 +284,6 @@ class CustomObjectClassificationProcessor(RealTimeProcessorApi):
config: FrigateConfig, config: FrigateConfig,
model_config: CustomClassificationConfig, model_config: CustomClassificationConfig,
sub_label_publisher: EventMetadataPublisher, sub_label_publisher: EventMetadataPublisher,
requestor: InterProcessRequestor,
metrics: DataProcessorMetrics, metrics: DataProcessorMetrics,
): ):
super().__init__(config, metrics) super().__init__(config, metrics)
@ -295,7 +292,6 @@ class CustomObjectClassificationProcessor(RealTimeProcessorApi):
self.train_dir = os.path.join(CLIPS_DIR, self.model_config.name, "train") self.train_dir = os.path.join(CLIPS_DIR, self.model_config.name, "train")
self.interpreter: Interpreter | None = None self.interpreter: Interpreter | None = None
self.sub_label_publisher = sub_label_publisher self.sub_label_publisher = sub_label_publisher
self.requestor = requestor
self.tensor_input_details: dict[str, Any] | None = None self.tensor_input_details: dict[str, Any] | None = None
self.tensor_output_details: dict[str, Any] | None = None self.tensor_output_details: dict[str, Any] | None = None
self.classification_history: dict[str, list[tuple[str, float, float]]] = {} self.classification_history: dict[str, list[tuple[str, float, float]]] = {}
@ -490,8 +486,6 @@ class CustomObjectClassificationProcessor(RealTimeProcessorApi):
) )
if consensus_label is not None: if consensus_label is not None:
camera = obj_data["camera"]
if ( if (
self.model_config.object_config.classification_type self.model_config.object_config.classification_type
== ObjectClassificationType.sub_label == ObjectClassificationType.sub_label
@ -500,20 +494,6 @@ class CustomObjectClassificationProcessor(RealTimeProcessorApi):
(object_id, consensus_label, consensus_score), (object_id, consensus_label, consensus_score),
EventMetadataTypeEnum.sub_label, EventMetadataTypeEnum.sub_label,
) )
self.requestor.send_data(
"tracked_object_update",
json.dumps(
{
"type": TrackedObjectUpdateTypesEnum.classification,
"id": object_id,
"camera": camera,
"timestamp": now,
"model": self.model_config.name,
"sub_label": consensus_label,
"score": consensus_score,
}
),
)
elif ( elif (
self.model_config.object_config.classification_type self.model_config.object_config.classification_type
== ObjectClassificationType.attribute == ObjectClassificationType.attribute
@ -527,20 +507,6 @@ class CustomObjectClassificationProcessor(RealTimeProcessorApi):
), ),
EventMetadataTypeEnum.attribute.value, EventMetadataTypeEnum.attribute.value,
) )
self.requestor.send_data(
"tracked_object_update",
json.dumps(
{
"type": TrackedObjectUpdateTypesEnum.classification,
"id": object_id,
"camera": camera,
"timestamp": now,
"model": self.model_config.name,
"attribute": consensus_label,
"score": consensus_score,
}
),
)
def handle_request(self, topic, request_data): def handle_request(self, topic, request_data):
if topic == EmbeddingsRequestEnum.reload_classification_model.value: if topic == EmbeddingsRequestEnum.reload_classification_model.value:

View File

@ -424,7 +424,7 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
if not res: if not res:
return { return {
"message": "Model is still training, please try again in a few moments.", "message": "No face was recognized.",
"success": False, "success": False,
} }

View File

@ -18,6 +18,7 @@ from frigate.detectors.detector_config import (
ModelTypeEnum, ModelTypeEnum,
) )
from frigate.util.file import FileLock from frigate.util.file import FileLock
from frigate.util.model import post_process_yolo
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
@ -177,6 +178,13 @@ class MemryXDetector(DetectionApi):
logger.error(f"Failed to initialize MemryX model: {e}") logger.error(f"Failed to initialize MemryX model: {e}")
raise raise
def load_yolo_constants(self):
base = f"{self.cache_dir}/{self.model_folder}"
# constants for yolov9 post-processing
self.const_A = np.load(f"{base}/_model_22_Constant_9_output_0.npy")
self.const_B = np.load(f"{base}/_model_22_Constant_10_output_0.npy")
self.const_C = np.load(f"{base}/_model_22_Constant_12_output_0.npy")
def check_and_prepare_model(self): def check_and_prepare_model(self):
if not os.path.exists(self.cache_dir): if not os.path.exists(self.cache_dir):
os.makedirs(self.cache_dir, exist_ok=True) os.makedirs(self.cache_dir, exist_ok=True)
@ -228,6 +236,7 @@ class MemryXDetector(DetectionApi):
# Handle post model requirements by model type # Handle post model requirements by model type
if self.memx_model_type in [ if self.memx_model_type in [
ModelTypeEnum.yologeneric,
ModelTypeEnum.yolonas, ModelTypeEnum.yolonas,
ModelTypeEnum.ssd, ModelTypeEnum.ssd,
]: ]:
@ -236,10 +245,7 @@ class MemryXDetector(DetectionApi):
f"No *_post.onnx file found in custom model zip for {self.memx_model_type.name}." f"No *_post.onnx file found in custom model zip for {self.memx_model_type.name}."
) )
self.memx_post_model = post_candidates[0] self.memx_post_model = post_candidates[0]
elif self.memx_model_type in [ elif self.memx_model_type == ModelTypeEnum.yolox:
ModelTypeEnum.yolox,
ModelTypeEnum.yologeneric,
]:
# Explicitly ignore any post model even if present # Explicitly ignore any post model even if present
self.memx_post_model = None self.memx_post_model = None
else: else:
@ -267,6 +273,8 @@ class MemryXDetector(DetectionApi):
logger.info("Using cached models.") logger.info("Using cached models.")
self.memx_model_path = dfp_path self.memx_model_path = dfp_path
self.memx_post_model = post_path self.memx_post_model = post_path
if self.memx_model_type == ModelTypeEnum.yologeneric:
self.load_yolo_constants()
return return
# ---------- CASE 3: download MemryX model (no cache) ---------- # ---------- CASE 3: download MemryX model (no cache) ----------
@ -295,6 +303,9 @@ class MemryXDetector(DetectionApi):
else None else None
) )
if self.memx_model_type == ModelTypeEnum.yologeneric:
self.load_yolo_constants()
finally: finally:
if os.path.exists(zip_path): if os.path.exists(zip_path):
try: try:
@ -589,232 +600,127 @@ class MemryXDetector(DetectionApi):
self.output_queue.put(final_detections) self.output_queue.put(final_detections)
def _generate_anchors(self, sizes=[80, 40, 20]): def onnx_reshape_with_allowzero(
"""Generate anchor points for YOLOv9 style processing""" self, data: np.ndarray, shape: np.ndarray, allowzero: int = 0
yscales = []
xscales = []
for s in sizes:
r = np.arange(s) + 0.5
yscales.append(np.repeat(r, s))
xscales.append(np.repeat(r[None, ...], s, axis=0).flatten())
yscales = np.concatenate(yscales)
xscales = np.concatenate(xscales)
anchors = np.stack([xscales, yscales], axis=1)
return anchors
def _generate_scales(self, sizes=[80, 40, 20]):
"""Generate scaling factors for each detection level"""
factors = [8, 16, 32]
s = np.concatenate([np.ones([int(s * s)]) * f for s, f in zip(sizes, factors)])
return s[:, None]
@staticmethod
def _softmax(x: np.ndarray, axis: int) -> np.ndarray:
"""Efficient softmax implementation"""
x = x - np.max(x, axis=axis, keepdims=True)
np.exp(x, out=x)
x /= np.sum(x, axis=axis, keepdims=True)
return x
def dfl(self, x: np.ndarray) -> np.ndarray:
"""Distribution Focal Loss decoding - YOLOv9 style"""
x = x.reshape(-1, 4, 16)
weights = np.arange(16, dtype=np.float32)
p = self._softmax(x, axis=2)
p = p * weights[None, None, :]
out = np.sum(p, axis=2, keepdims=False)
return out
def dist2bbox(
self, x: np.ndarray, anchors: np.ndarray, scales: np.ndarray
) -> np.ndarray: ) -> np.ndarray:
"""Convert distances to bounding boxes - YOLOv9 style""" shape = shape.astype(int)
lt = x[:, :2] input_shape = data.shape
rb = x[:, 2:] output_shape = []
x1y1 = anchors - lt for i, dim in enumerate(shape):
x2y2 = anchors + rb if dim == 0 and allowzero == 0:
output_shape.append(input_shape[i]) # Copy dimension from input
else:
output_shape.append(dim)
wh = x2y2 - x1y1 # Now let NumPy infer any -1 if needed
c_xy = (x1y1 + x2y2) / 2 reshaped = np.reshape(data, output_shape)
out = np.concatenate([c_xy, wh], axis=1) return reshaped
out = out * scales
return out
def post_process_yolo_optimized(self, outputs):
"""
Custom YOLOv9 post-processing optimized for MemryX ONNX outputs.
Implements DFL decoding, confidence filtering, and NMS in pure NumPy.
"""
# YOLOv9 outputs: 6 outputs (lbox, lcls, mbox, mcls, sbox, scls)
conv_out1, conv_out2, conv_out3, conv_out4, conv_out5, conv_out6 = outputs
# Determine grid sizes based on input resolution
# YOLOv9 uses 3 detection heads with strides [8, 16, 32]
# Grid sizes = input_size / stride
sizes = [
self.memx_model_height
// 8, # Large objects (e.g., 80 for 640x640, 40 for 320x320)
self.memx_model_height
// 16, # Medium objects (e.g., 40 for 640x640, 20 for 320x320)
self.memx_model_height
// 32, # Small objects (e.g., 20 for 640x640, 10 for 320x320)
]
# Generate anchors and scales if not already done
if not hasattr(self, "anchors"):
self.anchors = self._generate_anchors(sizes)
self.scales = self._generate_scales(sizes)
# Process outputs in YOLOv9 format: reshape and moveaxis for ONNX format
lbox = np.moveaxis(conv_out1, 1, -1) # Large boxes
lcls = np.moveaxis(conv_out2, 1, -1) # Large classes
mbox = np.moveaxis(conv_out3, 1, -1) # Medium boxes
mcls = np.moveaxis(conv_out4, 1, -1) # Medium classes
sbox = np.moveaxis(conv_out5, 1, -1) # Small boxes
scls = np.moveaxis(conv_out6, 1, -1) # Small classes
# Determine number of classes dynamically from the class output shape
# lcls shape should be (batch, height, width, num_classes)
num_classes = lcls.shape[-1]
# Validate that all class outputs have the same number of classes
if not (mcls.shape[-1] == num_classes and scls.shape[-1] == num_classes):
raise ValueError(
f"Class output shapes mismatch: lcls={lcls.shape}, mcls={mcls.shape}, scls={scls.shape}"
)
# Concatenate boxes and classes
boxes = np.concatenate(
[
lbox.reshape(-1, 64), # 64 is for 4 bbox coords * 16 DFL bins
mbox.reshape(-1, 64),
sbox.reshape(-1, 64),
],
axis=0,
)
classes = np.concatenate(
[
lcls.reshape(-1, num_classes),
mcls.reshape(-1, num_classes),
scls.reshape(-1, num_classes),
],
axis=0,
)
# Apply sigmoid to classes
classes = self.sigmoid(classes)
# Apply DFL to box predictions
boxes = self.dfl(boxes)
# YOLOv9 postprocessing with confidence filtering and NMS
confidence_thres = 0.4
iou_thres = 0.6
# Find the class with the highest score for each detection
max_scores = np.max(classes, axis=1) # Maximum class score for each detection
class_ids = np.argmax(classes, axis=1) # Index of the best class
# Filter out detections with scores below the confidence threshold
valid_indices = np.where(max_scores >= confidence_thres)[0]
if len(valid_indices) == 0:
# Return empty detections array
final_detections = np.zeros((20, 6), np.float32)
return final_detections
# Select only valid detections
valid_boxes = boxes[valid_indices]
valid_class_ids = class_ids[valid_indices]
valid_scores = max_scores[valid_indices]
# Convert distances to actual bounding boxes using anchors and scales
valid_boxes = self.dist2bbox(
valid_boxes, self.anchors[valid_indices], self.scales[valid_indices]
)
# Convert bounding box coordinates from (x_center, y_center, w, h) to (x_min, y_min, x_max, y_max)
x_center, y_center, width, height = (
valid_boxes[:, 0],
valid_boxes[:, 1],
valid_boxes[:, 2],
valid_boxes[:, 3],
)
x_min = x_center - width / 2
y_min = y_center - height / 2
x_max = x_center + width / 2
y_max = y_center + height / 2
# Convert to format expected by cv2.dnn.NMSBoxes: [x, y, width, height]
boxes_for_nms = []
scores_for_nms = []
for i in range(len(valid_indices)):
# Ensure coordinates are within bounds and positive
x_min_clipped = max(0, x_min[i])
y_min_clipped = max(0, y_min[i])
x_max_clipped = min(self.memx_model_width, x_max[i])
y_max_clipped = min(self.memx_model_height, y_max[i])
width_clipped = x_max_clipped - x_min_clipped
height_clipped = y_max_clipped - y_min_clipped
if width_clipped > 0 and height_clipped > 0:
boxes_for_nms.append(
[x_min_clipped, y_min_clipped, width_clipped, height_clipped]
)
scores_for_nms.append(float(valid_scores[i]))
final_detections = np.zeros((20, 6), np.float32)
if len(boxes_for_nms) == 0:
return final_detections
# Apply NMS using OpenCV
indices = cv2.dnn.NMSBoxes(
boxes_for_nms, scores_for_nms, confidence_thres, iou_thres
)
if len(indices) > 0:
# Flatten indices if they are returned as a list of arrays
if isinstance(indices[0], list) or isinstance(indices[0], np.ndarray):
indices = [i[0] for i in indices]
# Limit to top 20 detections
indices = indices[:20]
# Convert to Frigate format: [class_id, confidence, y_min, x_min, y_max, x_max] (normalized)
for i, idx in enumerate(indices):
class_id = valid_class_ids[idx]
confidence = valid_scores[idx]
# Get the box coordinates
box = boxes_for_nms[idx]
x_min_norm = box[0] / self.memx_model_width
y_min_norm = box[1] / self.memx_model_height
x_max_norm = (box[0] + box[2]) / self.memx_model_width
y_max_norm = (box[1] + box[3]) / self.memx_model_height
final_detections[i] = [
class_id,
confidence,
y_min_norm, # Frigate expects y_min first
x_min_norm,
y_max_norm,
x_max_norm,
]
return final_detections
def process_output(self, *outputs): def process_output(self, *outputs):
"""Output callback function -- receives frames from the MX3 and triggers post-processing""" """Output callback function -- receives frames from the MX3 and triggers post-processing"""
if self.memx_model_type == ModelTypeEnum.yologeneric: if self.memx_model_type == ModelTypeEnum.yologeneric:
# Use complete YOLOv9-style postprocessing (includes NMS) if not self.memx_post_model:
final_detections = self.post_process_yolo_optimized(outputs) conv_out1 = outputs[0]
conv_out2 = outputs[1]
conv_out3 = outputs[2]
conv_out4 = outputs[3]
conv_out5 = outputs[4]
conv_out6 = outputs[5]
concat_1 = self.onnx_concat([conv_out1, conv_out2], axis=1)
concat_2 = self.onnx_concat([conv_out3, conv_out4], axis=1)
concat_3 = self.onnx_concat([conv_out5, conv_out6], axis=1)
shape = np.array([1, 144, -1], dtype=np.int64)
reshaped_1 = self.onnx_reshape_with_allowzero(
concat_1, shape, allowzero=0
)
reshaped_2 = self.onnx_reshape_with_allowzero(
concat_2, shape, allowzero=0
)
reshaped_3 = self.onnx_reshape_with_allowzero(
concat_3, shape, allowzero=0
)
concat_4 = self.onnx_concat([reshaped_1, reshaped_2, reshaped_3], 2)
axis = 1
split_sizes = [64, 80]
# Calculate indices at which to split
indices = np.cumsum(split_sizes)[
:-1
] # [64] — split before the second chunk
# Perform split along axis 1
split_0, split_1 = np.split(concat_4, indices, axis=axis)
num_boxes = 2100 if self.memx_model_height == 320 else 8400
shape1 = np.array([1, 4, 16, num_boxes])
reshape_4 = self.onnx_reshape_with_allowzero(
split_0, shape1, allowzero=0
)
transpose_1 = reshape_4.transpose(0, 2, 1, 3)
axis = 1 # As per ONNX softmax node
# Subtract max for numerical stability
x_max = np.max(transpose_1, axis=axis, keepdims=True)
x_exp = np.exp(transpose_1 - x_max)
x_sum = np.sum(x_exp, axis=axis, keepdims=True)
softmax_output = x_exp / x_sum
# Weight W from the ONNX initializer (1, 16, 1, 1) with values 0 to 15
W = np.arange(16, dtype=np.float32).reshape(
1, 16, 1, 1
) # (1, 16, 1, 1)
# Apply 1x1 convolution: this is a weighted sum over channels
conv_output = np.sum(
softmax_output * W, axis=1, keepdims=True
) # shape: (1, 1, 4, 8400)
shape2 = np.array([1, 4, num_boxes])
reshape_5 = self.onnx_reshape_with_allowzero(
conv_output, shape2, allowzero=0
)
# ONNX Slice — get first 2 channels: [0:2] along axis 1
slice_output1 = reshape_5[:, 0:2, :] # Result: (1, 2, 8400)
# Slice channels 2 to 4 → axis = 1
slice_output2 = reshape_5[:, 2:4, :]
# Perform Subtraction
sub_output = self.const_A - slice_output1 # Equivalent to ONNX Sub
# Perform the ONNX-style Add
add_output = self.const_B + slice_output2
sub1 = add_output - sub_output
add1 = sub_output + add_output
div_output = add1 / 2.0
concat_5 = self.onnx_concat([div_output, sub1], axis=1)
# Expand B to (1, 1, 8400) so it can broadcast across axis=1 (4 channels)
const_C_expanded = self.const_C[:, np.newaxis, :] # Shape: (1, 1, 8400)
# Perform ONNX-style element-wise multiplication
mul_output = concat_5 * const_C_expanded # Result: (1, 4, 8400)
sigmoid_output = self.sigmoid(split_1)
outputs = self.onnx_concat([mul_output, sigmoid_output], axis=1)
final_detections = post_process_yolo(
outputs, self.memx_model_width, self.memx_model_height
)
self.output_queue.put(final_detections) self.output_queue.put(final_detections)
elif self.memx_model_type == ModelTypeEnum.yolonas: elif self.memx_model_type == ModelTypeEnum.yolonas:

View File

@ -195,7 +195,6 @@ class EmbeddingMaintainer(threading.Thread):
self.config, self.config,
model_config, model_config,
self.event_metadata_publisher, self.event_metadata_publisher,
self.requestor,
self.metrics, self.metrics,
) )
) )
@ -340,7 +339,6 @@ class EmbeddingMaintainer(threading.Thread):
self.config, self.config,
model_config, model_config,
self.event_metadata_publisher, self.event_metadata_publisher,
self.requestor,
self.metrics, self.metrics,
) )

View File

@ -362,7 +362,7 @@ def stats_snapshot(
stats["embeddings"]["review_description_speed"] = round( stats["embeddings"]["review_description_speed"] = round(
embeddings_metrics.review_desc_speed.value * 1000, 2 embeddings_metrics.review_desc_speed.value * 1000, 2
) )
stats["embeddings"]["review_description_events_per_second"] = round( stats["embeddings"]["review_descriptions"] = round(
embeddings_metrics.review_desc_dps.value, 2 embeddings_metrics.review_desc_dps.value, 2
) )
@ -370,7 +370,7 @@ def stats_snapshot(
stats["embeddings"]["object_description_speed"] = round( stats["embeddings"]["object_description_speed"] = round(
embeddings_metrics.object_desc_speed.value * 1000, 2 embeddings_metrics.object_desc_speed.value * 1000, 2
) )
stats["embeddings"]["object_description_events_per_second"] = round( stats["embeddings"]["object_descriptions"] = round(
embeddings_metrics.object_desc_dps.value, 2 embeddings_metrics.object_desc_dps.value, 2
) )
@ -378,7 +378,7 @@ def stats_snapshot(
stats["embeddings"][f"{key}_classification_speed"] = round( stats["embeddings"][f"{key}_classification_speed"] = round(
embeddings_metrics.classification_speeds[key].value * 1000, 2 embeddings_metrics.classification_speeds[key].value * 1000, 2
) )
stats["embeddings"][f"{key}_classification_events_per_second"] = round( stats["embeddings"][f"{key}_classification"] = round(
embeddings_metrics.classification_cps[key].value, 2 embeddings_metrics.classification_cps[key].value, 2
) )

View File

@ -113,7 +113,6 @@ class StorageMaintainer(threading.Thread):
recordings: Recordings = ( recordings: Recordings = (
Recordings.select( Recordings.select(
Recordings.id, Recordings.id,
Recordings.camera,
Recordings.start_time, Recordings.start_time,
Recordings.end_time, Recordings.end_time,
Recordings.segment_size, Recordings.segment_size,
@ -138,7 +137,7 @@ class StorageMaintainer(threading.Thread):
) )
event_start = 0 event_start = 0
deleted_recordings = [] deleted_recordings = set()
for recording in recordings: for recording in recordings:
# check if 1 hour of storage has been reclaimed # check if 1 hour of storage has been reclaimed
if deleted_segments_size > hourly_bandwidth: if deleted_segments_size > hourly_bandwidth:
@ -173,7 +172,7 @@ class StorageMaintainer(threading.Thread):
if not keep: if not keep:
try: try:
clear_and_unlink(Path(recording.path), missing_ok=False) clear_and_unlink(Path(recording.path), missing_ok=False)
deleted_recordings.append(recording) deleted_recordings.add(recording.id)
deleted_segments_size += recording.segment_size deleted_segments_size += recording.segment_size
except FileNotFoundError: except FileNotFoundError:
# this file was not found so we must assume no space was cleaned up # this file was not found so we must assume no space was cleaned up
@ -187,9 +186,6 @@ class StorageMaintainer(threading.Thread):
recordings = ( recordings = (
Recordings.select( Recordings.select(
Recordings.id, Recordings.id,
Recordings.camera,
Recordings.start_time,
Recordings.end_time,
Recordings.path, Recordings.path,
Recordings.segment_size, Recordings.segment_size,
) )
@ -205,7 +201,7 @@ class StorageMaintainer(threading.Thread):
try: try:
clear_and_unlink(Path(recording.path), missing_ok=False) clear_and_unlink(Path(recording.path), missing_ok=False)
deleted_segments_size += recording.segment_size deleted_segments_size += recording.segment_size
deleted_recordings.append(recording) deleted_recordings.add(recording.id)
except FileNotFoundError: except FileNotFoundError:
# this file was not found so we must assume no space was cleaned up # this file was not found so we must assume no space was cleaned up
pass pass
@ -215,50 +211,7 @@ class StorageMaintainer(threading.Thread):
logger.debug(f"Expiring {len(deleted_recordings)} recordings") logger.debug(f"Expiring {len(deleted_recordings)} recordings")
# delete up to 100,000 at a time # delete up to 100,000 at a time
max_deletes = 100000 max_deletes = 100000
deleted_recordings_list = list(deleted_recordings)
# Update has_clip for events that overlap with deleted recordings
if deleted_recordings:
# Group deleted recordings by camera
camera_recordings = {}
for recording in deleted_recordings:
if recording.camera not in camera_recordings:
camera_recordings[recording.camera] = {
"min_start": recording.start_time,
"max_end": recording.end_time,
}
else:
camera_recordings[recording.camera]["min_start"] = min(
camera_recordings[recording.camera]["min_start"],
recording.start_time,
)
camera_recordings[recording.camera]["max_end"] = max(
camera_recordings[recording.camera]["max_end"],
recording.end_time,
)
# Find all events that overlap with deleted recordings time range per camera
events_to_update = []
for camera, time_range in camera_recordings.items():
overlapping_events = Event.select(Event.id).where(
Event.camera == camera,
Event.has_clip == True,
Event.start_time < time_range["max_end"],
Event.end_time > time_range["min_start"],
)
for event in overlapping_events:
events_to_update.append(event.id)
# Update has_clip to False for overlapping events
if events_to_update:
for i in range(0, len(events_to_update), max_deletes):
batch = events_to_update[i : i + max_deletes]
Event.update(has_clip=False).where(Event.id << batch).execute()
logger.debug(
f"Updated has_clip to False for {len(events_to_update)} events"
)
deleted_recordings_list = [r.id for r in deleted_recordings]
for i in range(0, len(deleted_recordings_list), max_deletes): for i in range(0, len(deleted_recordings_list), max_deletes):
Recordings.delete().where( Recordings.delete().where(
Recordings.id << deleted_recordings_list[i : i + max_deletes] Recordings.id << deleted_recordings_list[i : i + max_deletes]

View File

@ -30,4 +30,3 @@ class TrackedObjectUpdateTypesEnum(str, Enum):
description = "description" description = "description"
face = "face" face = "face"
lpr = "lpr" lpr = "lpr"
classification = "classification"

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@ -130,13 +130,8 @@ def get_soc_type() -> Optional[str]:
"""Get the SoC type from device tree.""" """Get the SoC type from device tree."""
try: try:
with open("/proc/device-tree/compatible") as file: with open("/proc/device-tree/compatible") as file:
content = file.read() soc = file.read().split(",")[-1].strip("\x00")
return soc
# Check for Jetson devices
if "nvidia" in content:
return None
return content.split(",")[-1].strip("\x00")
except FileNotFoundError: except FileNotFoundError:
logger.debug("Could not determine SoC type from device tree") logger.debug("Could not determine SoC type from device tree")
return None return None

View File

@ -16,7 +16,7 @@ from frigate.comms.recordings_updater import (
RecordingsDataSubscriber, RecordingsDataSubscriber,
RecordingsDataTypeEnum, RecordingsDataTypeEnum,
) )
from frigate.config import CameraConfig, DetectConfig, LoggerConfig, ModelConfig from frigate.config import CameraConfig, DetectConfig, ModelConfig
from frigate.config.camera.camera import CameraTypeEnum from frigate.config.camera.camera import CameraTypeEnum
from frigate.config.camera.updater import ( from frigate.config.camera.updater import (
CameraConfigUpdateEnum, CameraConfigUpdateEnum,
@ -539,7 +539,6 @@ class CameraCapture(FrigateProcess):
shm_frame_count: int, shm_frame_count: int,
camera_metrics: CameraMetrics, camera_metrics: CameraMetrics,
stop_event: MpEvent, stop_event: MpEvent,
log_config: LoggerConfig | None = None,
) -> None: ) -> None:
super().__init__( super().__init__(
stop_event, stop_event,
@ -550,10 +549,9 @@ class CameraCapture(FrigateProcess):
self.config = config self.config = config
self.shm_frame_count = shm_frame_count self.shm_frame_count = shm_frame_count
self.camera_metrics = camera_metrics self.camera_metrics = camera_metrics
self.log_config = log_config
def run(self) -> None: def run(self) -> None:
self.pre_run_setup(self.log_config) self.pre_run_setup()
camera_watchdog = CameraWatchdog( camera_watchdog = CameraWatchdog(
self.config, self.config,
self.shm_frame_count, self.shm_frame_count,
@ -579,7 +577,6 @@ class CameraTracker(FrigateProcess):
ptz_metrics: PTZMetrics, ptz_metrics: PTZMetrics,
region_grid: list[list[dict[str, Any]]], region_grid: list[list[dict[str, Any]]],
stop_event: MpEvent, stop_event: MpEvent,
log_config: LoggerConfig | None = None,
) -> None: ) -> None:
super().__init__( super().__init__(
stop_event, stop_event,
@ -595,10 +592,9 @@ class CameraTracker(FrigateProcess):
self.camera_metrics = camera_metrics self.camera_metrics = camera_metrics
self.ptz_metrics = ptz_metrics self.ptz_metrics = ptz_metrics
self.region_grid = region_grid self.region_grid = region_grid
self.log_config = log_config
def run(self) -> None: def run(self) -> None:
self.pre_run_setup(self.log_config) self.pre_run_setup()
frame_queue = self.camera_metrics.frame_queue frame_queue = self.camera_metrics.frame_queue
frame_shape = self.config.frame_shape frame_shape = self.config.frame_shape

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@ -1,33 +0,0 @@
# COPYRIGHT AND TRADEMARK NOTICE
The images, logos, and icons contained in this directory (the "Brand Assets") are
proprietary to Frigate LLC and are NOT covered by the MIT License governing the
rest of this repository.
1. TRADEMARK STATUS
The "Frigate" name and the accompanying logo are common law trademarks™ of
Frigate LLC. Frigate LLC reserves all rights to these marks.
2. LIMITED PERMISSION FOR USE
Permission is hereby granted to display these Brand Assets strictly for the
following purposes:
a. To execute the software interface on a local machine.
b. To identify the software in documentation or reviews (nominative use).
3. RESTRICTIONS
You may NOT:
a. Use these Brand Assets to represent a derivative work (fork) as an official
product of Frigate LLC.
b. Use these Brand Assets in a way that implies endorsement, sponsorship, or
commercial affiliation with Frigate LLC.
c. Modify or alter the Brand Assets.
If you fork this repository with the intent to distribute a modified or competing
version of the software, you must replace these Brand Assets with your own
original content.
For full usage guidelines, strictly see the TRADEMARK.md file in the
repository root.
ALL RIGHTS RESERVED.
Copyright (c) 2025 Frigate LLC.

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@ -2,29 +2,29 @@
<html lang="en"> <html lang="en">
<head> <head>
<meta charset="UTF-8" /> <meta charset="UTF-8" />
<link rel="icon" href="/images/branding/favicon.ico" /> <link rel="icon" href="/images/favicon.ico" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" /> <meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>Frigate</title> <title>Frigate</title>
<link <link
rel="apple-touch-icon" rel="apple-touch-icon"
sizes="180x180" sizes="180x180"
href="/images/branding/apple-touch-icon.png" href="/images/apple-touch-icon.png"
/> />
<link <link
rel="icon" rel="icon"
type="image/png" type="image/png"
sizes="32x32" sizes="32x32"
href="/images/branding/favicon-32x32.png" href="/images/favicon-32x32.png"
/> />
<link <link
rel="icon" rel="icon"
type="image/png" type="image/png"
sizes="16x16" sizes="16x16"
href="/images/branding/favicon-16x16.png" href="/images/favicon-16x16.png"
/> />
<link rel="icon" type="image/svg+xml" href="/images/branding/favicon.svg" /> <link rel="icon" type="image/svg+xml" href="/images/favicon.svg" />
<link rel="manifest" href="/site.webmanifest" crossorigin="use-credentials" /> <link rel="manifest" href="/site.webmanifest" crossorigin="use-credentials" />
<link rel="mask-icon" href="/images/branding/favicon.svg" color="#3b82f7" /> <link rel="mask-icon" href="/images/favicon.svg" color="#3b82f7" />
<meta name="theme-color" content="#ffffff" media="(prefers-color-scheme: light)" /> <meta name="theme-color" content="#ffffff" media="(prefers-color-scheme: light)" />
<meta name="theme-color" content="#000000" media="(prefers-color-scheme: dark)" /> <meta name="theme-color" content="#000000" media="(prefers-color-scheme: dark)" />
</head> </head>

View File

@ -2,29 +2,29 @@
<html lang="en"> <html lang="en">
<head> <head>
<meta charset="UTF-8" /> <meta charset="UTF-8" />
<link rel="icon" href="/images/branding/favicon.ico" /> <link rel="icon" href="/images/favicon.ico" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" /> <meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>Frigate</title> <title>Frigate</title>
<link <link
rel="apple-touch-icon" rel="apple-touch-icon"
sizes="180x180" sizes="180x180"
href="/images/branding/apple-touch-icon.png" href="/images/apple-touch-icon.png"
/> />
<link <link
rel="icon" rel="icon"
type="image/png" type="image/png"
sizes="32x32" sizes="32x32"
href="/images/branding/favicon-32x32.png" href="/images/favicon-32x32.png"
/> />
<link <link
rel="icon" rel="icon"
type="image/png" type="image/png"
sizes="16x16" sizes="16x16"
href="/images/branding/favicon-16x16.png" href="/images/favicon-16x16.png"
/> />
<link rel="icon" type="image/svg+xml" href="/images/branding/favicon.svg" /> <link rel="icon" type="image/svg+xml" href="/images/favicon.svg" />
<link rel="manifest" href="/site.webmanifest" crossorigin="use-credentials" /> <link rel="manifest" href="/site.webmanifest" crossorigin="use-credentials" />
<link rel="mask-icon" href="/images/branding/favicon.svg" color="#3b82f7" /> <link rel="mask-icon" href="/images/favicon.svg" color="#3b82f7" />
<meta name="theme-color" content="#ffffff" media="(prefers-color-scheme: light)" /> <meta name="theme-color" content="#ffffff" media="(prefers-color-scheme: light)" />
<meta name="theme-color" content="#000000" media="(prefers-color-scheme: dark)" /> <meta name="theme-color" content="#000000" media="(prefers-color-scheme: dark)" />
</head> </head>

View File

@ -103,7 +103,7 @@
"regenerate": "A new description has been requested from {{provider}}. Depending on the speed of your provider, the new description may take some time to regenerate.", "regenerate": "A new description has been requested from {{provider}}. Depending on the speed of your provider, the new description may take some time to regenerate.",
"updatedSublabel": "Successfully updated sub label.", "updatedSublabel": "Successfully updated sub label.",
"updatedLPR": "Successfully updated license plate.", "updatedLPR": "Successfully updated license plate.",
"audioTranscription": "Successfully requested audio transcription. Depending on the speed of your Frigate server, the transcription may take some time to complete." "audioTranscription": "Successfully requested audio transcription."
}, },
"error": { "error": {
"regenerate": "Failed to call {{provider}} for a new description: {{errorMessage}}", "regenerate": "Failed to call {{provider}} for a new description: {{errorMessage}}",

View File

@ -177,10 +177,6 @@
"noCameras": { "noCameras": {
"title": "No Cameras Configured", "title": "No Cameras Configured",
"description": "Get started by connecting a camera to Frigate.", "description": "Get started by connecting a camera to Frigate.",
"buttonText": "Add Camera", "buttonText": "Add Camera"
"restricted": {
"title": "No Cameras Available",
"description": "You don't have permission to view any cameras in this group."
}
} }
} }

View File

@ -76,12 +76,7 @@
} }
}, },
"npuUsage": "NPU Usage", "npuUsage": "NPU Usage",
"npuMemory": "NPU Memory", "npuMemory": "NPU Memory"
"intelGpuWarning": {
"title": "Intel GPU Stats Warning",
"message": "GPU stats unavailable",
"description": "This is a known bug in Intel's GPU stats reporting tools (intel_gpu_top) where it will break and repeatedly return a GPU usage of 0% even in cases where hardware acceleration and object detection are correctly running on the (i)GPU. This is not a Frigate bug. You can restart the host to temporarily fix the issue and confirm that the GPU is working correctly. This does not affect performance."
}
}, },
"otherProcesses": { "otherProcesses": {
"title": "Other Processes", "title": "Other Processes",
@ -174,7 +169,6 @@
"enrichments": { "enrichments": {
"title": "Enrichments", "title": "Enrichments",
"infPerSecond": "Inferences Per Second", "infPerSecond": "Inferences Per Second",
"averageInf": "Average Inference Time",
"embeddings": { "embeddings": {
"image_embedding": "Image Embedding", "image_embedding": "Image Embedding",
"text_embedding": "Text Embedding", "text_embedding": "Text Embedding",
@ -186,13 +180,7 @@
"plate_recognition_speed": "Plate Recognition Speed", "plate_recognition_speed": "Plate Recognition Speed",
"text_embedding_speed": "Text Embedding Speed", "text_embedding_speed": "Text Embedding Speed",
"yolov9_plate_detection_speed": "YOLOv9 Plate Detection Speed", "yolov9_plate_detection_speed": "YOLOv9 Plate Detection Speed",
"yolov9_plate_detection": "YOLOv9 Plate Detection", "yolov9_plate_detection": "YOLOv9 Plate Detection"
"review_description": "Review Description",
"review_description_speed": "Review Description Speed",
"review_description_events_per_second": "Review Description",
"object_description": "Object Description",
"object_description_speed": "Object Description Speed",
"object_description_events_per_second": "Object Description"
} }
} }
} }

View File

@ -44,16 +44,11 @@ self.addEventListener("notificationclick", (event) => {
switch (event.action ?? "default") { switch (event.action ?? "default") {
case "markReviewed": case "markReviewed":
if (event.notification.data) { if (event.notification.data) {
event.waitUntil( fetch("/api/reviews/viewed", {
fetch("/api/reviews/viewed", { method: "POST",
method: "POST", headers: { "Content-Type": "application/json", "X-CSRF-TOKEN": 1 },
headers: { body: JSON.stringify({ ids: [event.notification.data.id] }),
"Content-Type": "application/json", });
"X-CSRF-TOKEN": 1,
},
body: JSON.stringify({ ids: [event.notification.data.id] }),
}), // eslint-disable-line comma-dangle
);
} }
break; break;
default: default:
@ -63,7 +58,7 @@ self.addEventListener("notificationclick", (event) => {
// eslint-disable-next-line no-undef // eslint-disable-next-line no-undef
if (clients.openWindow) { if (clients.openWindow) {
// eslint-disable-next-line no-undef // eslint-disable-next-line no-undef
event.waitUntil(clients.openWindow(url)); return clients.openWindow(url);
} }
} }
} }

View File

@ -398,7 +398,11 @@ export function GroupedClassificationCard({
threshold={threshold} threshold={threshold}
selected={false} selected={false}
i18nLibrary={i18nLibrary} i18nLibrary={i18nLibrary}
onClick={() => {}} onClick={(data, meta) => {
if (meta || selectedItems.length > 0) {
onClick(data);
}
}}
> >
{children?.(data)} {children?.(data)}
</ClassificationCard> </ClassificationCard>

View File

@ -9,7 +9,7 @@ import useSWR from "swr";
import { MdHome } from "react-icons/md"; import { MdHome } from "react-icons/md";
import { usePersistedOverlayState } from "@/hooks/use-overlay-state"; import { usePersistedOverlayState } from "@/hooks/use-overlay-state";
import { Button, buttonVariants } from "../ui/button"; import { Button, buttonVariants } from "../ui/button";
import { useCallback, useEffect, useMemo, useState } from "react"; import { useCallback, useMemo, useState } from "react";
import { Tooltip, TooltipContent, TooltipTrigger } from "../ui/tooltip"; import { Tooltip, TooltipContent, TooltipTrigger } from "../ui/tooltip";
import { LuPencil, LuPlus } from "react-icons/lu"; import { LuPencil, LuPlus } from "react-icons/lu";
import { import {
@ -87,8 +87,6 @@ type CameraGroupSelectorProps = {
export function CameraGroupSelector({ className }: CameraGroupSelectorProps) { export function CameraGroupSelector({ className }: CameraGroupSelectorProps) {
const { t } = useTranslation(["components/camera"]); const { t } = useTranslation(["components/camera"]);
const { data: config } = useSWR<FrigateConfig>("config"); const { data: config } = useSWR<FrigateConfig>("config");
const allowedCameras = useAllowedCameras();
const isCustomRole = useIsCustomRole();
// tooltip // tooltip
@ -121,22 +119,10 @@ export function CameraGroupSelector({ className }: CameraGroupSelectorProps) {
return []; return [];
} }
const allGroups = Object.entries(config.camera_groups); return Object.entries(config.camera_groups).sort(
(a, b) => a[1].order - b[1].order,
// If custom role, filter out groups where user has no accessible cameras );
if (isCustomRole) { }, [config]);
return allGroups
.filter(([, groupConfig]) => {
// Check if user has access to at least one camera in this group
return groupConfig.cameras.some((cameraName) =>
allowedCameras.includes(cameraName),
);
})
.sort((a, b) => a[1].order - b[1].order);
}
return allGroups.sort((a, b) => a[1].order - b[1].order);
}, [config, allowedCameras, isCustomRole]);
// add group // add group
@ -153,7 +139,6 @@ export function CameraGroupSelector({ className }: CameraGroupSelectorProps) {
activeGroup={group} activeGroup={group}
setGroup={setGroup} setGroup={setGroup}
deleteGroup={deleteGroup} deleteGroup={deleteGroup}
isCustomRole={isCustomRole}
/> />
<Scroller className={`${isMobile ? "whitespace-nowrap" : ""}`}> <Scroller className={`${isMobile ? "whitespace-nowrap" : ""}`}>
<div <div
@ -221,16 +206,14 @@ export function CameraGroupSelector({ className }: CameraGroupSelectorProps) {
); );
})} })}
{!isCustomRole && ( <Button
<Button className="bg-secondary text-muted-foreground"
className="bg-secondary text-muted-foreground" aria-label={t("group.add")}
aria-label={t("group.add")} size="xs"
size="xs" onClick={() => setAddGroup(true)}
onClick={() => setAddGroup(true)} >
> <LuPlus className="size-4 text-primary" />
<LuPlus className="size-4 text-primary" /> </Button>
</Button>
)}
{isMobile && <ScrollBar orientation="horizontal" className="h-0" />} {isMobile && <ScrollBar orientation="horizontal" className="h-0" />}
</div> </div>
</Scroller> </Scroller>
@ -245,7 +228,6 @@ type NewGroupDialogProps = {
activeGroup?: string; activeGroup?: string;
setGroup: (value: string | undefined, replace?: boolean | undefined) => void; setGroup: (value: string | undefined, replace?: boolean | undefined) => void;
deleteGroup: () => void; deleteGroup: () => void;
isCustomRole?: boolean;
}; };
function NewGroupDialog({ function NewGroupDialog({
open, open,
@ -254,7 +236,6 @@ function NewGroupDialog({
activeGroup, activeGroup,
setGroup, setGroup,
deleteGroup, deleteGroup,
isCustomRole,
}: NewGroupDialogProps) { }: NewGroupDialogProps) {
const { t } = useTranslation(["components/camera"]); const { t } = useTranslation(["components/camera"]);
const { mutate: updateConfig } = useSWR<FrigateConfig>("config"); const { mutate: updateConfig } = useSWR<FrigateConfig>("config");
@ -280,12 +261,6 @@ function NewGroupDialog({
`${activeGroup}-draggable-layout`, `${activeGroup}-draggable-layout`,
); );
useEffect(() => {
if (!open) {
setEditState("none");
}
}, [open]);
// callbacks // callbacks
const onDeleteGroup = useCallback( const onDeleteGroup = useCallback(
@ -374,7 +349,13 @@ function NewGroupDialog({
position="top-center" position="top-center"
closeButton={true} closeButton={true}
/> />
<Overlay open={open} onOpenChange={setOpen}> <Overlay
open={open}
onOpenChange={(open) => {
setEditState("none");
setOpen(open);
}}
>
<Content <Content
className={cn( className={cn(
"scrollbar-container overflow-y-auto", "scrollbar-container overflow-y-auto",
@ -390,30 +371,28 @@ function NewGroupDialog({
> >
<Title>{t("group.label")}</Title> <Title>{t("group.label")}</Title>
<Description className="sr-only">{t("group.edit")}</Description> <Description className="sr-only">{t("group.edit")}</Description>
{!isCustomRole && ( <div
<div className={cn(
"absolute",
isDesktop && "right-6 top-10",
isMobile && "absolute right-0 top-4",
)}
>
<Button
size="sm"
className={cn( className={cn(
"absolute", isDesktop &&
isDesktop && "right-6 top-10", "size-6 rounded-md bg-secondary-foreground p-1 text-background",
isMobile && "absolute right-0 top-4", isMobile && "text-secondary-foreground",
)} )}
aria-label={t("group.add")}
onClick={() => {
setEditState("add");
}}
> >
<Button <LuPlus />
size="sm" </Button>
className={cn( </div>
isDesktop &&
"size-6 rounded-md bg-secondary-foreground p-1 text-background",
isMobile && "text-secondary-foreground",
)}
aria-label={t("group.add")}
onClick={() => {
setEditState("add");
}}
>
<LuPlus />
</Button>
</div>
)}
</Header> </Header>
<div className="flex flex-col gap-4 md:gap-3"> <div className="flex flex-col gap-4 md:gap-3">
{currentGroups.map((group) => ( {currentGroups.map((group) => (
@ -422,7 +401,6 @@ function NewGroupDialog({
group={group} group={group}
onDeleteGroup={() => onDeleteGroup(group[0])} onDeleteGroup={() => onDeleteGroup(group[0])}
onEditGroup={() => onEditGroup(group)} onEditGroup={() => onEditGroup(group)}
isReadOnly={isCustomRole}
/> />
))} ))}
</div> </div>
@ -534,14 +512,12 @@ type CameraGroupRowProps = {
group: [string, CameraGroupConfig]; group: [string, CameraGroupConfig];
onDeleteGroup: () => void; onDeleteGroup: () => void;
onEditGroup: () => void; onEditGroup: () => void;
isReadOnly?: boolean;
}; };
export function CameraGroupRow({ export function CameraGroupRow({
group, group,
onDeleteGroup, onDeleteGroup,
onEditGroup, onEditGroup,
isReadOnly,
}: CameraGroupRowProps) { }: CameraGroupRowProps) {
const { t } = useTranslation(["components/camera"]); const { t } = useTranslation(["components/camera"]);
const [deleteDialogOpen, setDeleteDialogOpen] = useState(false); const [deleteDialogOpen, setDeleteDialogOpen] = useState(false);
@ -588,7 +564,7 @@ export function CameraGroupRow({
</AlertDialogContent> </AlertDialogContent>
</AlertDialog> </AlertDialog>
{isMobile && !isReadOnly && ( {isMobile && (
<> <>
<DropdownMenu modal={!isDesktop}> <DropdownMenu modal={!isDesktop}>
<DropdownMenuTrigger> <DropdownMenuTrigger>
@ -613,7 +589,7 @@ export function CameraGroupRow({
</DropdownMenu> </DropdownMenu>
</> </>
)} )}
{!isMobile && !isReadOnly && ( {!isMobile && (
<div className="flex flex-row items-center gap-2"> <div className="flex flex-row items-center gap-2">
<Tooltip> <Tooltip>
<TooltipTrigger asChild> <TooltipTrigger asChild>

View File

@ -572,8 +572,9 @@ export function SortTypeContent({
className="w-full space-y-1" className="w-full space-y-1"
> >
{availableSortTypes.map((value) => ( {availableSortTypes.map((value) => (
<div key={value} className="flex flex-row gap-2"> <div className="flex flex-row gap-2">
<RadioGroupItem <RadioGroupItem
key={value}
value={value} value={value}
id={`sort-${value}`} id={`sort-${value}`}
className={ className={

View File

@ -4,7 +4,9 @@ import { FrigateConfig } from "@/types/frigateConfig";
import { baseUrl } from "@/api/baseUrl"; import { baseUrl } from "@/api/baseUrl";
import { toast } from "sonner"; import { toast } from "sonner";
import axios from "axios"; import axios from "axios";
import { LuCamera, LuDownload, LuTrash2 } from "react-icons/lu";
import { FiMoreVertical } from "react-icons/fi"; import { FiMoreVertical } from "react-icons/fi";
import { MdImageSearch } from "react-icons/md";
import { buttonVariants } from "@/components/ui/button"; import { buttonVariants } from "@/components/ui/button";
import { import {
ContextMenu, ContextMenu,
@ -29,8 +31,11 @@ import {
AlertDialogTitle, AlertDialogTitle,
} from "@/components/ui/alert-dialog"; } from "@/components/ui/alert-dialog";
import useSWR from "swr"; import useSWR from "swr";
import { Trans, useTranslation } from "react-i18next"; import { Trans, useTranslation } from "react-i18next";
import { BsFillLightningFill } from "react-icons/bs";
import BlurredIconButton from "../button/BlurredIconButton"; import BlurredIconButton from "../button/BlurredIconButton";
import { PiPath } from "react-icons/pi";
type SearchResultActionsProps = { type SearchResultActionsProps = {
searchResult: SearchResult; searchResult: SearchResult;
@ -93,6 +98,7 @@ export default function SearchResultActions({
href={`${baseUrl}api/events/${searchResult.id}/clip.mp4`} href={`${baseUrl}api/events/${searchResult.id}/clip.mp4`}
download={`${searchResult.camera}_${searchResult.label}.mp4`} download={`${searchResult.camera}_${searchResult.label}.mp4`}
> >
<LuDownload className="mr-2 size-4" />
<span>{t("itemMenu.downloadVideo.label")}</span> <span>{t("itemMenu.downloadVideo.label")}</span>
</a> </a>
</MenuItem> </MenuItem>
@ -104,6 +110,7 @@ export default function SearchResultActions({
href={`${baseUrl}api/events/${searchResult.id}/snapshot.jpg`} href={`${baseUrl}api/events/${searchResult.id}/snapshot.jpg`}
download={`${searchResult.camera}_${searchResult.label}.jpg`} download={`${searchResult.camera}_${searchResult.label}.jpg`}
> >
<LuCamera className="mr-2 size-4" />
<span>{t("itemMenu.downloadSnapshot.label")}</span> <span>{t("itemMenu.downloadSnapshot.label")}</span>
</a> </a>
</MenuItem> </MenuItem>
@ -113,31 +120,44 @@ export default function SearchResultActions({
aria-label={t("itemMenu.viewTrackingDetails.aria")} aria-label={t("itemMenu.viewTrackingDetails.aria")}
onClick={showTrackingDetails} onClick={showTrackingDetails}
> >
<PiPath className="mr-2 size-4" />
<span>{t("itemMenu.viewTrackingDetails.label")}</span> <span>{t("itemMenu.viewTrackingDetails.label")}</span>
</MenuItem> </MenuItem>
)} )}
{config?.semantic_search?.enabled && {config?.semantic_search?.enabled && isContextMenu && (
searchResult.data.type == "object" && ( <MenuItem
<MenuItem aria-label={t("itemMenu.findSimilar.aria")}
aria-label={t("itemMenu.findSimilar.aria")} onClick={findSimilar}
onClick={findSimilar} >
> <MdImageSearch className="mr-2 size-4" />
<span>{t("itemMenu.findSimilar.label")}</span> <span>{t("itemMenu.findSimilar.label")}</span>
</MenuItem> </MenuItem>
)} )}
{config?.semantic_search?.enabled && {config?.semantic_search?.enabled &&
searchResult.data.type == "object" && ( searchResult.data.type == "object" && (
<MenuItem <MenuItem
aria-label={t("itemMenu.addTrigger.aria")} aria-label={t("itemMenu.addTrigger.aria")}
onClick={addTrigger} onClick={addTrigger}
> >
<BsFillLightningFill className="mr-2 size-4" />
<span>{t("itemMenu.addTrigger.label")}</span> <span>{t("itemMenu.addTrigger.label")}</span>
</MenuItem> </MenuItem>
)} )}
{config?.semantic_search?.enabled &&
searchResult.data.type == "object" && (
<MenuItem
aria-label={t("itemMenu.findSimilar.aria")}
onClick={findSimilar}
>
<MdImageSearch className="mr-2 size-4" />
<span>{t("itemMenu.findSimilar.label")}</span>
</MenuItem>
)}
<MenuItem <MenuItem
aria-label={t("itemMenu.deleteTrackedObject.label")} aria-label={t("itemMenu.deleteTrackedObject.label")}
onClick={() => setDeleteDialogOpen(true)} onClick={() => setDeleteDialogOpen(true)}
> >
<LuTrash2 className="mr-2 size-4" />
<span>{t("button.delete", { ns: "common" })}</span> <span>{t("button.delete", { ns: "common" })}</span>
</MenuItem> </MenuItem>
</> </>

View File

@ -46,13 +46,13 @@ export default function NavItem({
onClick={onClick} onClick={onClick}
className={({ isActive }) => className={({ isActive }) =>
cn( cn(
"flex flex-col items-center justify-center rounded-lg p-[6px]", "flex flex-col items-center justify-center rounded-lg",
className, className,
variants[item.variant ?? "primary"][isActive ? "active" : "inactive"], variants[item.variant ?? "primary"][isActive ? "active" : "inactive"],
) )
} }
> >
<Icon className="size-5" /> <Icon className="size-5 md:m-[6px]" />
</NavLink> </NavLink>
); );

View File

@ -13,8 +13,7 @@ import { zodResolver } from "@hookform/resolvers/zod";
import { useForm } from "react-hook-form"; import { useForm } from "react-hook-form";
import { z } from "zod"; import { z } from "zod";
import ActivityIndicator from "../indicators/activity-indicator"; import ActivityIndicator from "../indicators/activity-indicator";
import { useEffect, useState, useMemo } from "react"; import { useEffect, useState } from "react";
import useSWR from "swr";
import { import {
Dialog, Dialog,
DialogContent, DialogContent,
@ -36,7 +35,6 @@ import { LuCheck, LuX } from "react-icons/lu";
import { useTranslation } from "react-i18next"; import { useTranslation } from "react-i18next";
import { isDesktop, isMobile } from "react-device-detect"; import { isDesktop, isMobile } from "react-device-detect";
import { cn } from "@/lib/utils"; import { cn } from "@/lib/utils";
import { FrigateConfig } from "@/types/frigateConfig";
import { import {
MobilePage, MobilePage,
MobilePageContent, MobilePageContent,
@ -56,15 +54,9 @@ export default function CreateUserDialog({
onCreate, onCreate,
onCancel, onCancel,
}: CreateUserOverlayProps) { }: CreateUserOverlayProps) {
const { data: config } = useSWR<FrigateConfig>("config");
const { t } = useTranslation(["views/settings"]); const { t } = useTranslation(["views/settings"]);
const [isLoading, setIsLoading] = useState<boolean>(false); const [isLoading, setIsLoading] = useState<boolean>(false);
const roles = useMemo(() => {
const existingRoles = config ? Object.keys(config.auth?.roles || {}) : [];
return Array.from(new Set(["admin", "viewer", ...(existingRoles || [])]));
}, [config]);
const formSchema = z const formSchema = z
.object({ .object({
user: z user: z
@ -77,7 +69,7 @@ export default function CreateUserDialog({
confirmPassword: z confirmPassword: z
.string() .string()
.min(1, t("users.dialog.createUser.confirmPassword")), .min(1, t("users.dialog.createUser.confirmPassword")),
role: z.string().min(1), role: z.enum(["admin", "viewer"]),
}) })
.refine((data) => data.password === data.confirmPassword, { .refine((data) => data.password === data.confirmPassword, {
message: t("users.dialog.form.password.notMatch"), message: t("users.dialog.form.password.notMatch"),
@ -254,22 +246,24 @@ export default function CreateUserDialog({
</SelectTrigger> </SelectTrigger>
</FormControl> </FormControl>
<SelectContent> <SelectContent>
{roles.map((r) => ( <SelectItem
<SelectItem value="admin"
value={r} className="flex items-center gap-2"
key={r} >
className="flex items-center gap-2" <div className="flex items-center gap-2">
> <Shield className="h-4 w-4 text-primary" />
<div className="flex items-center gap-2"> <span>{t("role.admin", { ns: "common" })}</span>
{r === "admin" ? ( </div>
<Shield className="h-4 w-4 text-primary" /> </SelectItem>
) : ( <SelectItem
<User className="h-4 w-4 text-muted-foreground" /> value="viewer"
)} className="flex items-center gap-2"
<span>{t(`role.${r}`, { ns: "common" }) || r}</span> >
</div> <div className="flex items-center gap-2">
</SelectItem> <User className="h-4 w-4 text-muted-foreground" />
))} <span>{t("role.viewer", { ns: "common" })}</span>
</div>
</SelectItem>
</SelectContent> </SelectContent>
</Select> </Select>
<FormDescription className="text-xs text-muted-foreground"> <FormDescription className="text-xs text-muted-foreground">

View File

@ -12,7 +12,6 @@ import {
DropdownMenuContent, DropdownMenuContent,
DropdownMenuItem, DropdownMenuItem,
DropdownMenuLabel, DropdownMenuLabel,
DropdownMenuSeparator,
DropdownMenuTrigger, DropdownMenuTrigger,
} from "@/components/ui/dropdown-menu"; } from "@/components/ui/dropdown-menu";
import { import {
@ -21,6 +20,7 @@ import {
TooltipTrigger, TooltipTrigger,
} from "@/components/ui/tooltip"; } from "@/components/ui/tooltip";
import { isDesktop, isMobile } from "react-device-detect"; import { isDesktop, isMobile } from "react-device-detect";
import { LuPlus, LuScanFace } from "react-icons/lu";
import { useTranslation } from "react-i18next"; import { useTranslation } from "react-i18next";
import { cn } from "@/lib/utils"; import { cn } from "@/lib/utils";
import React, { ReactNode, useMemo, useState } from "react"; import React, { ReactNode, useMemo, useState } from "react";
@ -89,26 +89,27 @@ export default function FaceSelectionDialog({
<DropdownMenuLabel>{t("trainFaceAs")}</DropdownMenuLabel> <DropdownMenuLabel>{t("trainFaceAs")}</DropdownMenuLabel>
<div <div
className={cn( className={cn(
"flex max-h-[40dvh] flex-col overflow-y-auto overflow-x-hidden", "flex max-h-[40dvh] flex-col overflow-y-auto",
isMobile && "gap-2 pb-4", isMobile && "gap-2 pb-4",
)} )}
> >
<SelectorItem
className="flex cursor-pointer gap-2 smart-capitalize"
onClick={() => setNewFace(true)}
>
<LuPlus />
{t("createFaceLibrary.new")}
</SelectorItem>
{faceNames.sort().map((faceName) => ( {faceNames.sort().map((faceName) => (
<SelectorItem <SelectorItem
key={faceName} key={faceName}
className="flex cursor-pointer gap-2 smart-capitalize" className="flex cursor-pointer gap-2 smart-capitalize"
onClick={() => onTrainAttempt(faceName)} onClick={() => onTrainAttempt(faceName)}
> >
<LuScanFace />
{faceName} {faceName}
</SelectorItem> </SelectorItem>
))} ))}
<DropdownMenuSeparator />
<SelectorItem
className="flex cursor-pointer gap-2 smart-capitalize"
onClick={() => setNewFace(true)}
>
{t("createFaceLibrary.new")}
</SelectorItem>
</div> </div>
</SelectorContent> </SelectorContent>
</Selector> </Selector>

View File

@ -171,18 +171,6 @@ export default function ImagePicker({
alt={selectedImage?.label || "Selected image"} alt={selectedImage?.label || "Selected image"}
className="size-16 rounded object-cover" className="size-16 rounded object-cover"
onLoad={() => handleImageLoad(selectedImageId || "")} onLoad={() => handleImageLoad(selectedImageId || "")}
onError={(e) => {
// If trigger thumbnail fails to load, fall back to event thumbnail
if (!selectedImage) {
const target = e.target as HTMLImageElement;
if (
target.src.includes("clips/triggers") &&
selectedImageId
) {
target.src = `${apiHost}api/events/${selectedImageId}/thumbnail.webp`;
}
}
}}
loading="lazy" loading="lazy"
/> />
{selectedImageId && !loadedImages.has(selectedImageId) && ( {selectedImageId && !loadedImages.has(selectedImageId) && (

View File

@ -42,10 +42,9 @@ export default function DetailActionsMenu({
return `start/${startTime}/end/${endTime}`; return `start/${startTime}/end/${endTime}`;
}, [search]); }, [search]);
// currently, audio event ids are not saved in review items const { data: reviewItem } = useSWR<ReviewSegment>([
const { data: reviewItem } = useSWR<ReviewSegment>( `review/event/${search.id}`,
search.data?.type === "audio" ? null : [`review/event/${search.id}`], ]);
);
return ( return (
<DropdownMenu open={isOpen} onOpenChange={setIsOpen}> <DropdownMenu open={isOpen} onOpenChange={setIsOpen}>

View File

@ -683,22 +683,6 @@ function ObjectDetailsTab({
const mutate = useGlobalMutation(); const mutate = useGlobalMutation();
// Helper to map over SWR cached search results while preserving
// either paginated format (SearchResult[][]) or flat format (SearchResult[])
const mapSearchResults = useCallback(
(
currentData: SearchResult[][] | SearchResult[] | undefined,
fn: (event: SearchResult) => SearchResult,
) => {
if (!currentData) return currentData;
if (Array.isArray(currentData[0])) {
return (currentData as SearchResult[][]).map((page) => page.map(fn));
}
return (currentData as SearchResult[]).map(fn);
},
[],
);
// users // users
const isAdmin = useIsAdmin(); const isAdmin = useIsAdmin();
@ -807,15 +791,6 @@ function ObjectDetailsTab({
} }
}, [search]); }, [search]);
const isEventsKey = useCallback((key: unknown): boolean => {
const candidate = Array.isArray(key) ? key[0] : key;
const EVENTS_KEY_PATTERNS = ["events", "events/search", "events/explore"];
return (
typeof candidate === "string" &&
EVENTS_KEY_PATTERNS.some((p) => candidate.includes(p))
);
}, []);
const updateDescription = useCallback(() => { const updateDescription = useCallback(() => {
if (!search) { if (!search) {
return; return;
@ -830,20 +805,28 @@ function ObjectDetailsTab({
}); });
} }
mutate( mutate(
(key) => isEventsKey(key), (key) =>
(currentData: SearchResult[][] | SearchResult[] | undefined) => typeof key === "string" &&
mapSearchResults(currentData, (event) => (key.includes("events") ||
event.id === search.id key.includes("events/search") ||
? { ...event, data: { ...event.data, description: desc } } key.includes("events/explore")),
: event, (currentData: SearchResult[][] | SearchResult[] | undefined) => {
), if (!currentData) return currentData;
// optimistic update
return currentData
.flat()
.map((event) =>
event.id === search.id
? { ...event, data: { ...event.data, description: desc } }
: event,
);
},
{ {
optimisticData: true, optimisticData: true,
rollbackOnError: true, rollbackOnError: true,
revalidate: false, revalidate: false,
}, },
); );
setSearch({ ...search, data: { ...search.data, description: desc } });
}) })
.catch((error) => { .catch((error) => {
const errorMessage = const errorMessage =
@ -860,7 +843,7 @@ function ObjectDetailsTab({
); );
setDesc(search.data.description); setDesc(search.data.description);
}); });
}, [desc, search, mutate, t, mapSearchResults, isEventsKey, setSearch]); }, [desc, search, mutate, t]);
const regenerateDescription = useCallback( const regenerateDescription = useCallback(
(source: "snapshot" | "thumbnails") => { (source: "snapshot" | "thumbnails") => {
@ -927,9 +910,14 @@ function ObjectDetailsTab({
}); });
mutate( mutate(
(key) => isEventsKey(key), (key) =>
(currentData: SearchResult[][] | SearchResult[] | undefined) => typeof key === "string" &&
mapSearchResults(currentData, (event) => (key.includes("events") ||
key.includes("events/search") ||
key.includes("events/explore")),
(currentData: SearchResult[][] | SearchResult[] | undefined) => {
if (!currentData) return currentData;
return currentData.flat().map((event) =>
event.id === search.id event.id === search.id
? { ? {
...event, ...event,
@ -940,7 +928,8 @@ function ObjectDetailsTab({
}, },
} }
: event, : event,
), );
},
{ {
optimisticData: true, optimisticData: true,
rollbackOnError: true, rollbackOnError: true,
@ -974,7 +963,7 @@ function ObjectDetailsTab({
); );
}); });
}, },
[search, apiHost, mutate, setSearch, t, mapSearchResults, isEventsKey], [search, apiHost, mutate, setSearch, t],
); );
// recognized plate // recognized plate
@ -998,9 +987,14 @@ function ObjectDetailsTab({
}); });
mutate( mutate(
(key) => isEventsKey(key), (key) =>
(currentData: SearchResult[][] | SearchResult[] | undefined) => typeof key === "string" &&
mapSearchResults(currentData, (event) => (key.includes("events") ||
key.includes("events/search") ||
key.includes("events/explore")),
(currentData: SearchResult[][] | SearchResult[] | undefined) => {
if (!currentData) return currentData;
return currentData.flat().map((event) =>
event.id === search.id event.id === search.id
? { ? {
...event, ...event,
@ -1011,7 +1005,8 @@ function ObjectDetailsTab({
}, },
} }
: event, : event,
), );
},
{ {
optimisticData: true, optimisticData: true,
rollbackOnError: true, rollbackOnError: true,
@ -1045,7 +1040,7 @@ function ObjectDetailsTab({
); );
}); });
}, },
[search, apiHost, mutate, setSearch, t, mapSearchResults, isEventsKey], [search, apiHost, mutate, setSearch, t],
); );
// speech transcription // speech transcription
@ -1101,15 +1096,23 @@ function ObjectDetailsTab({
}); });
setState("submitted"); setState("submitted");
setSearch({ ...search, plus_id: "new_upload" });
mutate( mutate(
(key) => isEventsKey(key), (key) =>
(currentData: SearchResult[][] | SearchResult[] | undefined) => typeof key === "string" &&
mapSearchResults(currentData, (event) => (key.includes("events") ||
event.id === search.id key.includes("events/search") ||
? { ...event, plus_id: "new_upload" } key.includes("events/explore")),
: event, (currentData: SearchResult[][] | SearchResult[] | undefined) => {
), if (!currentData) return currentData;
// optimistic update
return currentData
.flat()
.map((event) =>
event.id === search.id
? { ...event, plus_id: "new_upload" }
: event,
);
},
{ {
optimisticData: true, optimisticData: true,
rollbackOnError: true, rollbackOnError: true,
@ -1117,7 +1120,7 @@ function ObjectDetailsTab({
}, },
); );
}, },
[search, mutate, mapSearchResults, setSearch, isEventsKey], [search, mutate],
); );
const popoverContainerRef = useRef<HTMLDivElement | null>(null); const popoverContainerRef = useRef<HTMLDivElement | null>(null);
@ -1295,7 +1298,6 @@ function ObjectDetailsTab({
{search.data.type === "object" && {search.data.type === "object" &&
config?.plus?.enabled && config?.plus?.enabled &&
search.end_time != undefined &&
search.has_snapshot && ( search.has_snapshot && (
<div <div
className={cn( className={cn(
@ -1501,7 +1503,7 @@ function ObjectDetailsTab({
) : ( ) : (
<div className="flex flex-col gap-2"> <div className="flex flex-col gap-2">
<Textarea <Textarea
className="text-md h-32 md:text-sm" className="text-md h-32"
placeholder={t("details.description.placeholder")} placeholder={t("details.description.placeholder")}
value={desc} value={desc}
onChange={(e) => setDesc(e.target.value)} onChange={(e) => setDesc(e.target.value)}
@ -1509,25 +1511,7 @@ function ObjectDetailsTab({
onBlur={handleDescriptionBlur} onBlur={handleDescriptionBlur}
autoFocus autoFocus
/> />
<div className="mb-10 flex flex-row justify-end gap-5"> <div className="flex flex-row justify-end gap-4">
<Tooltip>
<TooltipTrigger asChild>
<button
aria-label={t("button.cancel", { ns: "common" })}
className="text-primary/40 hover:text-primary"
onClick={() => {
setIsEditingDesc(false);
setDesc(originalDescRef.current ?? "");
}}
>
<FaTimes className="size-5" />
</button>
</TooltipTrigger>
<TooltipContent>
{t("button.cancel", { ns: "common" })}
</TooltipContent>
</Tooltip>
<Tooltip> <Tooltip>
<TooltipTrigger asChild> <TooltipTrigger asChild>
<button <button
@ -1538,13 +1522,31 @@ function ObjectDetailsTab({
updateDescription(); updateDescription();
}} }}
> >
<FaCheck className="size-5" /> <FaCheck className="size-4" />
</button> </button>
</TooltipTrigger> </TooltipTrigger>
<TooltipContent> <TooltipContent>
{t("button.save", { ns: "common" })} {t("button.save", { ns: "common" })}
</TooltipContent> </TooltipContent>
</Tooltip> </Tooltip>
<Tooltip>
<TooltipTrigger asChild>
<button
aria-label={t("button.cancel", { ns: "common" })}
className="text-primary/40 hover:text-primary"
onClick={() => {
setIsEditingDesc(false);
setDesc(originalDescRef.current ?? "");
}}
>
<FaTimes className="size-4" />
</button>
</TooltipTrigger>
<TooltipContent>
{t("button.cancel", { ns: "common" })}
</TooltipContent>
</Tooltip>
</div> </div>
</div> </div>
)} )}

View File

@ -1,6 +1,5 @@
import useSWR from "swr"; import useSWR from "swr";
import { useCallback, useEffect, useMemo, useRef, useState } from "react"; import { useCallback, useEffect, useMemo, useRef, useState } from "react";
import { useResizeObserver } from "@/hooks/resize-observer";
import { Event } from "@/types/event"; import { Event } from "@/types/event";
import ActivityIndicator from "@/components/indicators/activity-indicator"; import ActivityIndicator from "@/components/indicators/activity-indicator";
import { TrackingDetailsSequence } from "@/types/timeline"; import { TrackingDetailsSequence } from "@/types/timeline";
@ -12,11 +11,7 @@ import { cn } from "@/lib/utils";
import HlsVideoPlayer from "@/components/player/HlsVideoPlayer"; import HlsVideoPlayer from "@/components/player/HlsVideoPlayer";
import { baseUrl } from "@/api/baseUrl"; import { baseUrl } from "@/api/baseUrl";
import { REVIEW_PADDING } from "@/types/review"; import { REVIEW_PADDING } from "@/types/review";
import { import { ASPECT_VERTICAL_LAYOUT, ASPECT_WIDE_LAYOUT } from "@/types/record";
ASPECT_VERTICAL_LAYOUT,
ASPECT_WIDE_LAYOUT,
Recording,
} from "@/types/record";
import { import {
DropdownMenu, DropdownMenu,
DropdownMenuTrigger, DropdownMenuTrigger,
@ -56,7 +51,6 @@ export function TrackingDetails({
const apiHost = useApiHost(); const apiHost = useApiHost();
const imgRef = useRef<HTMLImageElement | null>(null); const imgRef = useRef<HTMLImageElement | null>(null);
const [imgLoaded, setImgLoaded] = useState(false); const [imgLoaded, setImgLoaded] = useState(false);
const [isVideoLoading, setIsVideoLoading] = useState(true);
const [displaySource, _setDisplaySource] = useState<"video" | "image">( const [displaySource, _setDisplaySource] = useState<"video" | "image">(
"video", "video",
); );
@ -71,10 +65,6 @@ export function TrackingDetails({
(event.start_time ?? 0) + annotationOffset / 1000 - REVIEW_PADDING, (event.start_time ?? 0) + annotationOffset / 1000 - REVIEW_PADDING,
); );
useEffect(() => {
setIsVideoLoading(true);
}, [event.id]);
const { data: eventSequence } = useSWR<TrackingDetailsSequence[]>([ const { data: eventSequence } = useSWR<TrackingDetailsSequence[]>([
"timeline", "timeline",
{ {
@ -84,139 +74,6 @@ export function TrackingDetails({
const { data: config } = useSWR<FrigateConfig>("config"); const { data: config } = useSWR<FrigateConfig>("config");
// Fetch recording segments for the event's time range to handle motion-only gaps
const eventStartRecord = useMemo(
() => (event.start_time ?? 0) + annotationOffset / 1000,
[event.start_time, annotationOffset],
);
const eventEndRecord = useMemo(
() => (event.end_time ?? Date.now() / 1000) + annotationOffset / 1000,
[event.end_time, annotationOffset],
);
const { data: recordings } = useSWR<Recording[]>(
event.camera
? [
`${event.camera}/recordings`,
{
after: eventStartRecord - REVIEW_PADDING,
before: eventEndRecord + REVIEW_PADDING,
},
]
: null,
);
// Convert a timeline timestamp to actual video player time, accounting for
// motion-only recording gaps. Uses the same algorithm as DynamicVideoController.
const timestampToVideoTime = useCallback(
(timestamp: number): number => {
if (!recordings || recordings.length === 0) {
// Fallback to simple calculation if no recordings data
return timestamp - (eventStartRecord - REVIEW_PADDING);
}
const videoStartTime = eventStartRecord - REVIEW_PADDING;
// If timestamp is before video start, return 0
if (timestamp < videoStartTime) return 0;
// Check if timestamp is before the first recording or after the last
if (
timestamp < recordings[0].start_time ||
timestamp > recordings[recordings.length - 1].end_time
) {
// No recording available at this timestamp
return 0;
}
// Calculate the inpoint offset - the HLS video may start partway through the first segment
let inpointOffset = 0;
if (
videoStartTime > recordings[0].start_time &&
videoStartTime < recordings[0].end_time
) {
inpointOffset = videoStartTime - recordings[0].start_time;
}
let seekSeconds = 0;
for (const segment of recordings) {
// Skip segments that end before our timestamp
if (segment.end_time <= timestamp) {
// Add this segment's duration, but subtract inpoint offset from first segment
if (segment === recordings[0]) {
seekSeconds += segment.duration - inpointOffset;
} else {
seekSeconds += segment.duration;
}
} else if (segment.start_time <= timestamp) {
// The timestamp is within this segment
if (segment === recordings[0]) {
// For the first segment, account for the inpoint offset
seekSeconds +=
timestamp - Math.max(segment.start_time, videoStartTime);
} else {
seekSeconds += timestamp - segment.start_time;
}
break;
}
}
return seekSeconds;
},
[recordings, eventStartRecord],
);
// Convert video player time back to timeline timestamp, accounting for
// motion-only recording gaps. Reverse of timestampToVideoTime.
const videoTimeToTimestamp = useCallback(
(playerTime: number): number => {
if (!recordings || recordings.length === 0) {
// Fallback to simple calculation if no recordings data
const videoStartTime = eventStartRecord - REVIEW_PADDING;
return playerTime + videoStartTime;
}
const videoStartTime = eventStartRecord - REVIEW_PADDING;
// Calculate the inpoint offset - the video may start partway through the first segment
let inpointOffset = 0;
if (
videoStartTime > recordings[0].start_time &&
videoStartTime < recordings[0].end_time
) {
inpointOffset = videoStartTime - recordings[0].start_time;
}
let timestamp = 0;
let totalTime = 0;
for (const segment of recordings) {
const segmentDuration =
segment === recordings[0]
? segment.duration - inpointOffset
: segment.duration;
if (totalTime + segmentDuration > playerTime) {
// The player time is within this segment
if (segment === recordings[0]) {
// For the first segment, add the inpoint offset
timestamp =
Math.max(segment.start_time, videoStartTime) +
(playerTime - totalTime);
} else {
timestamp = segment.start_time + (playerTime - totalTime);
}
break;
} else {
totalTime += segmentDuration;
}
}
return timestamp;
},
[recordings, eventStartRecord],
);
eventSequence?.map((event) => { eventSequence?.map((event) => {
event.data.zones_friendly_names = event.data?.zones?.map((zone) => { event.data.zones_friendly_names = event.data?.zones?.map((zone) => {
return resolveZoneName(config, zone); return resolveZoneName(config, zone);
@ -232,16 +89,9 @@ export function TrackingDetails({
}, [manualOverride, currentTime, annotationOffset]); }, [manualOverride, currentTime, annotationOffset]);
const containerRef = useRef<HTMLDivElement | null>(null); const containerRef = useRef<HTMLDivElement | null>(null);
const timelineContainerRef = useRef<HTMLDivElement | null>(null);
const rowRefs = useRef<(HTMLDivElement | null)[]>([]);
const [_selectedZone, setSelectedZone] = useState(""); const [_selectedZone, setSelectedZone] = useState("");
const [_lifecycleZones, setLifecycleZones] = useState<string[]>([]); const [_lifecycleZones, setLifecycleZones] = useState<string[]>([]);
const [seekToTimestamp, setSeekToTimestamp] = useState<number | null>(null); const [seekToTimestamp, setSeekToTimestamp] = useState<number | null>(null);
const [lineBottomOffsetPx, setLineBottomOffsetPx] = useState<number>(32);
const [lineTopOffsetPx, setLineTopOffsetPx] = useState<number>(8);
const [blueLineHeightPx, setBlueLineHeightPx] = useState<number>(0);
const [timelineSize] = useResizeObserver(timelineContainerRef);
const aspectRatio = useMemo(() => { const aspectRatio = useMemo(() => {
if (!config) { if (!config) {
@ -290,14 +140,17 @@ export function TrackingDetails({
return; return;
} }
// For video mode: convert to video-relative time (accounting for motion-only gaps) // For video mode: convert to video-relative time and seek player
const relativeTime = timestampToVideoTime(targetTimeRecord); const eventStartRecord =
(event.start_time ?? 0) + annotationOffset / 1000;
const videoStartTime = eventStartRecord - REVIEW_PADDING;
const relativeTime = targetTimeRecord - videoStartTime;
if (videoRef.current) { if (videoRef.current) {
videoRef.current.currentTime = relativeTime; videoRef.current.currentTime = relativeTime;
} }
}, },
[annotationOffset, displaySource, timestampToVideoTime], [event.start_time, annotationOffset, displaySource],
); );
const formattedStart = config const formattedStart = config
@ -316,22 +169,21 @@ export function TrackingDetails({
}) })
: ""; : "";
const formattedEnd = const formattedEnd = config
config && event.end_time != null ? formatUnixTimestampToDateTime(event.end_time ?? 0, {
? formatUnixTimestampToDateTime(event.end_time, { timezone: config.ui.timezone,
timezone: config.ui.timezone, date_format:
date_format: config.ui.time_format == "24hour"
config.ui.time_format == "24hour" ? t("time.formattedTimestamp.24hour", {
? t("time.formattedTimestamp.24hour", { ns: "common",
ns: "common", })
}) : t("time.formattedTimestamp.12hour", {
: t("time.formattedTimestamp.12hour", { ns: "common",
ns: "common", }),
}), time_style: "medium",
time_style: "medium", date_style: "medium",
date_style: "medium", })
}) : "";
: "";
useEffect(() => { useEffect(() => {
if (!eventSequence || eventSequence.length === 0) return; if (!eventSequence || eventSequence.length === 0) return;
@ -350,83 +202,79 @@ export function TrackingDetails({
} }
// seekToTimestamp is a record stream timestamp // seekToTimestamp is a record stream timestamp
// Convert to video position (accounting for motion-only recording gaps) // event.start_time is detect stream time, convert to record
// The video clip starts at (eventStartRecord - REVIEW_PADDING)
if (!videoRef.current) return; if (!videoRef.current) return;
const relativeTime = timestampToVideoTime(seekToTimestamp); const eventStartRecord = event.start_time + annotationOffset / 1000;
const videoStartTime = eventStartRecord - REVIEW_PADDING;
const relativeTime = seekToTimestamp - videoStartTime;
if (relativeTime >= 0) { if (relativeTime >= 0) {
videoRef.current.currentTime = relativeTime; videoRef.current.currentTime = relativeTime;
} }
setSeekToTimestamp(null); setSeekToTimestamp(null);
}, [seekToTimestamp, displaySource, timestampToVideoTime]); }, [
seekToTimestamp,
event.start_time,
annotationOffset,
apiHost,
event.camera,
displaySource,
]);
const isWithinEventRange = useMemo(() => { const isWithinEventRange =
if (effectiveTime === undefined || event.start_time === undefined) { effectiveTime !== undefined &&
return false; event.start_time !== undefined &&
event.end_time !== undefined &&
effectiveTime >= event.start_time &&
effectiveTime <= event.end_time;
// Calculate how far down the blue line should extend based on effectiveTime
const calculateLineHeight = useCallback(() => {
if (!eventSequence || eventSequence.length === 0 || !isWithinEventRange) {
return 0;
} }
// If an event has not ended yet, fall back to last timestamp in eventSequence
let eventEnd = event.end_time; const currentTime = effectiveTime ?? 0;
if (eventEnd == null && eventSequence && eventSequence.length > 0) {
const last = eventSequence[eventSequence.length - 1]; // Find which events have been passed
if (last && last.timestamp !== undefined) { let lastPassedIndex = -1;
eventEnd = last.timestamp; for (let i = 0; i < eventSequence.length; i++) {
if (currentTime >= (eventSequence[i].timestamp ?? 0)) {
lastPassedIndex = i;
} else {
break;
} }
} }
if (eventEnd == null) { // No events passed yet
return false; if (lastPassedIndex < 0) return 0;
}
return effectiveTime >= event.start_time && effectiveTime <= eventEnd;
}, [effectiveTime, event.start_time, event.end_time, eventSequence]);
// Dynamically compute pixel offsets so the timeline line starts at the // All events passed
// first row midpoint and ends at the last row midpoint. For accuracy, if (lastPassedIndex >= eventSequence.length - 1) return 100;
// measure the center Y of each lifecycle row and interpolate the current
// effective time into a pixel position; then set the blue line height
// so it reaches the center dot at the same time the dot becomes active.
useEffect(() => {
if (!timelineContainerRef.current || !eventSequence) return;
const containerRect = timelineContainerRef.current.getBoundingClientRect(); // Calculate percentage based on item position, not time
const validRefs = rowRefs.current.filter((r) => r !== null); // Each item occupies an equal visual space regardless of time gaps
if (validRefs.length === 0) return; const itemPercentage = 100 / (eventSequence.length - 1);
const centers = validRefs.map((n) => { // Find progress between current and next event for smooth transition
const r = n.getBoundingClientRect(); const currentEvent = eventSequence[lastPassedIndex];
return r.top + r.height / 2 - containerRect.top; const nextEvent = eventSequence[lastPassedIndex + 1];
}); const currentTimestamp = currentEvent.timestamp ?? 0;
const nextTimestamp = nextEvent.timestamp ?? 0;
const topOffset = Math.max(0, centers[0]); // Calculate interpolation between the two events
const bottomOffset = Math.max( const timeBetween = nextTimestamp - currentTimestamp;
0, const timeElapsed = currentTime - currentTimestamp;
containerRect.height - centers[centers.length - 1], const interpolation = timeBetween > 0 ? timeElapsed / timeBetween : 0;
// Base position plus interpolated progress to next item
return Math.min(
100,
lastPassedIndex * itemPercentage + interpolation * itemPercentage,
); );
}, [eventSequence, effectiveTime, isWithinEventRange]);
setLineTopOffsetPx(Math.round(topOffset)); const blueLineHeight = calculateLineHeight();
setLineBottomOffsetPx(Math.round(bottomOffset));
const eff = effectiveTime ?? 0;
const timestamps = eventSequence.map((s) => s.timestamp ?? 0);
let pixelPos = centers[0];
if (eff <= timestamps[0]) {
pixelPos = centers[0];
} else if (eff >= timestamps[timestamps.length - 1]) {
pixelPos = centers[centers.length - 1];
} else {
for (let i = 0; i < timestamps.length - 1; i++) {
const t1 = timestamps[i];
const t2 = timestamps[i + 1];
if (eff >= t1 && eff <= t2) {
const ratio = t2 > t1 ? (eff - t1) / (t2 - t1) : 0;
pixelPos = centers[i] + ratio * (centers[i + 1] - centers[i]);
break;
}
}
}
const bluePx = Math.round(Math.max(0, pixelPos - topOffset));
setBlueLineHeightPx(bluePx);
}, [eventSequence, timelineSize.width, timelineSize.height, effectiveTime]);
const videoSource = useMemo(() => { const videoSource = useMemo(() => {
// event.start_time and event.end_time are in DETECT stream time // event.start_time and event.end_time are in DETECT stream time
@ -464,13 +312,14 @@ export function TrackingDetails({
const handleTimeUpdate = useCallback( const handleTimeUpdate = useCallback(
(time: number) => { (time: number) => {
// Convert video player time back to timeline timestamp // event.start_time is detect stream time, convert to record
// accounting for motion-only recording gaps const eventStartRecord = event.start_time + annotationOffset / 1000;
const absoluteTime = videoTimeToTimestamp(time); const videoStartTime = eventStartRecord - REVIEW_PADDING;
const absoluteTime = time + videoStartTime;
setCurrentTime(absoluteTime); setCurrentTime(absoluteTime);
}, },
[videoTimeToTimestamp], [event.start_time, annotationOffset],
); );
const [src, setSrc] = useState( const [src, setSrc] = useState(
@ -532,28 +381,22 @@ export function TrackingDetails({
)} )}
> >
{displaySource == "video" && ( {displaySource == "video" && (
<> <HlsVideoPlayer
<HlsVideoPlayer videoRef={videoRef}
videoRef={videoRef} containerRef={containerRef}
containerRef={containerRef} visible={true}
visible={true} currentSource={videoSource}
currentSource={videoSource} hotKeys={false}
hotKeys={false} supportsFullscreen={false}
supportsFullscreen={false} fullscreen={false}
fullscreen={false} frigateControls={true}
frigateControls={true} onTimeUpdate={handleTimeUpdate}
onTimeUpdate={handleTimeUpdate} onSeekToTime={handleSeekToTime}
onSeekToTime={handleSeekToTime} onUploadFrame={onUploadFrameToPlus}
onUploadFrame={onUploadFrameToPlus} isDetailMode={true}
onPlaying={() => setIsVideoLoading(false)} camera={event.camera}
isDetailMode={true} currentTimeOverride={currentTime}
camera={event.camera} />
currentTimeOverride={currentTime}
/>
{isVideoLoading && (
<ActivityIndicator className="absolute left-1/2 top-1/2 -translate-x-1/2 -translate-y-1/2" />
)}
</>
)} )}
{displaySource == "image" && ( {displaySource == "image" && (
<> <>
@ -660,16 +503,9 @@ export function TrackingDetails({
</div> </div>
<div className="flex items-center gap-2"> <div className="flex items-center gap-2">
<span className="capitalize">{label}</span> <span className="capitalize">{label}</span>
<div className="md:text-md flex items-center text-xs text-secondary-foreground"> <span className="md:text-md text-xs text-secondary-foreground">
{formattedStart ?? ""} {formattedStart ?? ""} - {formattedEnd ?? ""}
{event.end_time != null ? ( </span>
<> - {formattedEnd}</>
) : (
<div className="inline-block">
<ActivityIndicator className="ml-3 size-4" />
</div>
)}
</div>
{event.data?.recognized_license_plate && ( {event.data?.recognized_license_plate && (
<> <>
<span className="text-secondary-foreground">·</span> <span className="text-secondary-foreground">·</span>
@ -695,21 +531,12 @@ export function TrackingDetails({
{t("detail.noObjectDetailData", { ns: "views/events" })} {t("detail.noObjectDetailData", { ns: "views/events" })}
</div> </div>
) : ( ) : (
<div <div className="-pb-2 relative mx-0">
className="-pb-2 relative mx-0" <div className="absolute -top-2 bottom-8 left-6 z-0 w-0.5 -translate-x-1/2 bg-secondary-foreground" />
ref={timelineContainerRef}
>
<div
className="absolute -top-2 left-6 z-0 w-0.5 -translate-x-1/2 bg-secondary-foreground"
style={{ bottom: lineBottomOffsetPx }}
/>
{isWithinEventRange && ( {isWithinEventRange && (
<div <div
className="absolute left-6 z-[5] w-0.5 -translate-x-1/2 bg-selected transition-all duration-300" className="absolute left-6 top-2 z-[5] max-h-[calc(100%-3rem)] w-0.5 -translate-x-1/2 bg-selected transition-all duration-300"
style={{ style={{ height: `${blueLineHeight}%` }}
top: `${lineTopOffsetPx}px`,
height: `${blueLineHeightPx}px`,
}}
/> />
)} )}
<div className="space-y-2"> <div className="space-y-2">
@ -762,26 +589,20 @@ export function TrackingDetails({
: undefined; : undefined;
return ( return (
<div <LifecycleIconRow
key={`${item.timestamp}-${item.source_id ?? ""}-${idx}`} key={`${item.timestamp}-${item.source_id ?? ""}-${idx}`}
ref={(el) => { item={item}
rowRefs.current[idx] = el; isActive={isActive}
}} formattedEventTimestamp={formattedEventTimestamp}
> ratio={ratio}
<LifecycleIconRow areaPx={areaPx}
item={item} areaPct={areaPct}
isActive={isActive} onClick={() => handleLifecycleClick(item)}
formattedEventTimestamp={formattedEventTimestamp} setSelectedZone={setSelectedZone}
ratio={ratio} getZoneColor={getZoneColor}
areaPx={areaPx} effectiveTime={effectiveTime}
areaPct={areaPct} isTimelineActive={isWithinEventRange}
onClick={() => handleLifecycleClick(item)} />
setSelectedZone={setSelectedZone}
getZoneColor={getZoneColor}
effectiveTime={effectiveTime}
isTimelineActive={isWithinEventRange}
/>
</div>
); );
})} })}
</div> </div>

View File

@ -6,199 +6,51 @@ import {
DialogTitle, DialogTitle,
} from "@/components/ui/dialog"; } from "@/components/ui/dialog";
import { Event } from "@/types/event"; import { Event } from "@/types/event";
import { isDesktop, isMobile, isSafari } from "react-device-detect"; import { isDesktop, isMobile } from "react-device-detect";
import { ObjectSnapshotTab } from "../detail/SearchDetailDialog";
import { cn } from "@/lib/utils"; import { cn } from "@/lib/utils";
import { useCallback, useEffect, useState } from "react";
import axios from "axios";
import { useTranslation, Trans } from "react-i18next";
import { Button } from "@/components/ui/button";
import ActivityIndicator from "@/components/indicators/activity-indicator";
import { FaCheckCircle } from "react-icons/fa";
import { Card, CardContent } from "@/components/ui/card";
import { TransformComponent, TransformWrapper } from "react-zoom-pan-pinch";
import ImageLoadingIndicator from "@/components/indicators/ImageLoadingIndicator";
import { baseUrl } from "@/api/baseUrl";
import { getTranslatedLabel } from "@/utils/i18n";
import useImageLoaded from "@/hooks/use-image-loaded";
export type FrigatePlusDialogProps = { type FrigatePlusDialogProps = {
upload?: Event; upload?: Event;
dialog?: boolean; dialog?: boolean;
onClose: () => void; onClose: () => void;
onEventUploaded: () => void; onEventUploaded: () => void;
}; };
export function FrigatePlusDialog({ export function FrigatePlusDialog({
upload, upload,
dialog = true, dialog = true,
onClose, onClose,
onEventUploaded, onEventUploaded,
}: FrigatePlusDialogProps) { }: FrigatePlusDialogProps) {
const { t, i18n } = useTranslation(["components/dialog"]); if (!upload) {
return;
type SubmissionState = "reviewing" | "uploading" | "submitted"; }
const [state, setState] = useState<SubmissionState>( if (dialog) {
upload?.plus_id ? "submitted" : "reviewing", return (
); <Dialog
useEffect(() => { open={upload != undefined}
setState(upload?.plus_id ? "submitted" : "reviewing"); onOpenChange={(open) => (!open ? onClose() : null)}
}, [upload?.plus_id]);
const onSubmitToPlus = useCallback(
async (falsePositive: boolean) => {
if (!upload) return;
falsePositive
? axios.put(`events/${upload.id}/false_positive`)
: axios.post(`events/${upload.id}/plus`, { include_annotation: 1 });
setState("submitted");
onEventUploaded();
},
[upload, onEventUploaded],
);
const [imgRef, imgLoaded, onImgLoad] = useImageLoaded();
const showCard =
!!upload &&
upload.data.type === "object" &&
upload.plus_id !== "not_enabled" &&
upload.end_time &&
upload.label !== "on_demand";
if (!dialog || !upload) return null;
return (
<Dialog open={true} onOpenChange={(open) => (!open ? onClose() : null)}>
<DialogContent
className={cn(
"scrollbar-container overflow-y-auto",
isDesktop &&
"max-h-[95dvh] sm:max-w-xl md:max-w-4xl lg:max-w-4xl xl:max-w-7xl",
isMobile && "px-4",
)}
> >
<DialogHeader> <DialogContent
<DialogTitle className="sr-only">Submit to Frigate+</DialogTitle> className={cn(
<DialogDescription className="sr-only"> "scrollbar-container overflow-y-auto",
Submit this snapshot to Frigate+ isDesktop &&
</DialogDescription> "max-h-[95dvh] sm:max-w-xl md:max-w-4xl lg:max-w-4xl xl:max-w-7xl",
</DialogHeader> isMobile && "px-4",
)}
<div className="relative size-full"> >
<ImageLoadingIndicator <DialogHeader>
className="absolute inset-0 aspect-video min-h-[60dvh] w-full" <DialogTitle className="sr-only">Submit to Frigate+</DialogTitle>
imgLoaded={imgLoaded} <DialogDescription className="sr-only">
Submit this snapshot to Frigate+
</DialogDescription>
</DialogHeader>
<ObjectSnapshotTab
search={upload}
onEventUploaded={onEventUploaded}
/> />
<div className={imgLoaded ? "visible" : "invisible"}> </DialogContent>
<TransformWrapper minScale={1.0} wheel={{ smoothStep: 0.005 }}> </Dialog>
<div className="flex flex-col space-y-3"> );
<TransformComponent }
wrapperStyle={{ width: "100%", height: "100%" }}
contentStyle={{
position: "relative",
width: "100%",
height: "100%",
}}
>
{upload.id && (
<div className="relative mx-auto">
<img
ref={imgRef}
className="mx-auto max-h-[60dvh] rounded-lg bg-black object-contain"
src={`${baseUrl}api/events/${upload.id}/snapshot.jpg`}
alt={`${upload.label}`}
loading={isSafari ? "eager" : "lazy"}
onLoad={onImgLoad}
/>
</div>
)}
</TransformComponent>
{showCard && (
<Card className="p-1 text-sm md:p-2">
<CardContent className="flex flex-col items-center justify-between gap-3 p-2 md:flex-row">
<div className="flex flex-col space-y-3">
<div className="text-lg leading-none">
{t("explore.plus.submitToPlus.label")}
</div>
<div className="text-sm text-muted-foreground">
{t("explore.plus.submitToPlus.desc")}
</div>
</div>
<div className="flex w-full flex-1 flex-col justify-center gap-2 md:ml-8 md:w-auto md:justify-end">
{state === "reviewing" && (
<>
<div>
{i18n.language === "en" ? (
/^[aeiou]/i.test(upload.label || "") ? (
<Trans
ns="components/dialog"
values={{ label: upload.label }}
>
explore.plus.review.question.ask_an
</Trans>
) : (
<Trans
ns="components/dialog"
values={{ label: upload.label }}
>
explore.plus.review.question.ask_a
</Trans>
)
) : (
<Trans
ns="components/dialog"
values={{
untranslatedLabel: upload.label,
translatedLabel: getTranslatedLabel(
upload.label,
),
}}
>
explore.plus.review.question.ask_full
</Trans>
)}
</div>
<div className="flex w-full flex-row gap-2">
<Button
className="flex-1 bg-success"
aria-label={t("button.yes", { ns: "common" })}
onClick={() => {
setState("uploading");
onSubmitToPlus(false);
}}
>
{t("button.yes", { ns: "common" })}
</Button>
<Button
className="flex-1 text-white"
aria-label={t("button.no", { ns: "common" })}
variant="destructive"
onClick={() => {
setState("uploading");
onSubmitToPlus(true);
}}
>
{t("button.no", { ns: "common" })}
</Button>
</div>
</>
)}
{state === "uploading" && <ActivityIndicator />}
{state === "submitted" && (
<div className="flex flex-row items-center justify-center gap-2">
<FaCheckCircle className="size-4 text-success" />
{t("explore.plus.review.state.submitted")}
</div>
)}
</div>
</CardContent>
</Card>
)}
</div>
</TransformWrapper>
</div>
</div>
</DialogContent>
</Dialog>
);
} }

View File

@ -6,7 +6,7 @@ import {
useState, useState,
} from "react"; } from "react";
import Hls from "hls.js"; import Hls from "hls.js";
import { isDesktop, isMobile } from "react-device-detect"; import { isAndroid, isDesktop, isMobile } from "react-device-detect";
import { TransformComponent, TransformWrapper } from "react-zoom-pan-pinch"; import { TransformComponent, TransformWrapper } from "react-zoom-pan-pinch";
import VideoControls from "./VideoControls"; import VideoControls from "./VideoControls";
import { VideoResolutionType } from "@/types/live"; import { VideoResolutionType } from "@/types/live";
@ -22,7 +22,7 @@ import { useTranslation } from "react-i18next";
import ObjectTrackOverlay from "@/components/overlay/ObjectTrackOverlay"; import ObjectTrackOverlay from "@/components/overlay/ObjectTrackOverlay";
// Android native hls does not seek correctly // Android native hls does not seek correctly
const USE_NATIVE_HLS = false; const USE_NATIVE_HLS = !isAndroid;
const HLS_MIME_TYPE = "application/vnd.apple.mpegurl" as const; const HLS_MIME_TYPE = "application/vnd.apple.mpegurl" as const;
const unsupportedErrorCodes = [ const unsupportedErrorCodes = [
MediaError.MEDIA_ERR_SRC_NOT_SUPPORTED, MediaError.MEDIA_ERR_SRC_NOT_SUPPORTED,
@ -94,52 +94,24 @@ export default function HlsVideoPlayer({
const [loadedMetadata, setLoadedMetadata] = useState(false); const [loadedMetadata, setLoadedMetadata] = useState(false);
const [bufferTimeout, setBufferTimeout] = useState<NodeJS.Timeout>(); const [bufferTimeout, setBufferTimeout] = useState<NodeJS.Timeout>();
const applyVideoDimensions = useCallback(
(width: number, height: number) => {
if (setFullResolution) {
setFullResolution({ width, height });
}
setVideoDimensions({ width, height });
if (height > 0) {
setTallCamera(width / height < ASPECT_VERTICAL_LAYOUT);
}
},
[setFullResolution],
);
const handleLoadedMetadata = useCallback(() => { const handleLoadedMetadata = useCallback(() => {
setLoadedMetadata(true); setLoadedMetadata(true);
if (!videoRef.current) { if (videoRef.current) {
return; const width = videoRef.current.videoWidth;
} const height = videoRef.current.videoHeight;
const width = videoRef.current.videoWidth; if (setFullResolution) {
const height = videoRef.current.videoHeight; setFullResolution({
width,
// iOS Safari occasionally reports 0x0 for videoWidth/videoHeight height,
// Poll with requestAnimationFrame until dimensions become available (or timeout). });
if (width > 0 && height > 0) {
applyVideoDimensions(width, height);
return;
}
let attempts = 0;
const maxAttempts = 120; // ~2 seconds at 60fps
const tryGetDims = () => {
if (!videoRef.current) return;
const w = videoRef.current.videoWidth;
const h = videoRef.current.videoHeight;
if (w > 0 && h > 0) {
applyVideoDimensions(w, h);
return;
} }
if (attempts < maxAttempts) {
attempts += 1; setVideoDimensions({ width, height });
requestAnimationFrame(tryGetDims);
} setTallCamera(width / height < ASPECT_VERTICAL_LAYOUT);
}; }
requestAnimationFrame(tryGetDims); }, [videoRef, setFullResolution]);
}, [videoRef, applyVideoDimensions]);
useEffect(() => { useEffect(() => {
if (!videoRef.current) { if (!videoRef.current) {
@ -158,8 +130,6 @@ export default function HlsVideoPlayer({
return; return;
} }
setLoadedMetadata(false);
const currentPlaybackRate = videoRef.current.playbackRate; const currentPlaybackRate = videoRef.current.playbackRate;
if (!useHlsCompat) { if (!useHlsCompat) {
@ -348,7 +318,6 @@ export default function HlsVideoPlayer({
{isDetailMode && {isDetailMode &&
camera && camera &&
currentTime && currentTime &&
loadedMetadata &&
videoDimensions.width > 0 && videoDimensions.width > 0 &&
videoDimensions.height > 0 && ( videoDimensions.height > 0 && (
<div className="absolute z-50 size-full"> <div className="absolute z-50 size-full">

View File

@ -91,7 +91,7 @@ function MSEPlayer({
(error: LivePlayerError, description: string = "Unknown error") => { (error: LivePlayerError, description: string = "Unknown error") => {
// eslint-disable-next-line no-console // eslint-disable-next-line no-console
console.error( console.error(
`${camera} - MSE error '${error}': ${description} See the documentation: https://docs.frigate.video/configuration/live/#live-player-error-messages`, `${camera} - MSE error '${error}': ${description} See the documentation: https://docs.frigate.video/configuration/live/#live-view-faq`,
); );
onError?.(error); onError?.(error);
}, },

View File

@ -309,7 +309,6 @@ function PreviewVideoPlayer({
playsInline playsInline
muted muted
disableRemotePlayback disableRemotePlayback
disablePictureInPicture
onSeeked={onPreviewSeeked} onSeeked={onPreviewSeeked}
onLoadedData={() => { onLoadedData={() => {
if (firstLoad) { if (firstLoad) {

View File

@ -42,7 +42,7 @@ export default function WebRtcPlayer({
(error: LivePlayerError, description: string = "Unknown error") => { (error: LivePlayerError, description: string = "Unknown error") => {
// eslint-disable-next-line no-console // eslint-disable-next-line no-console
console.error( console.error(
`${camera} - WebRTC error '${error}': ${description} See the documentation: https://docs.frigate.video/configuration/live/#live-player-error-messages`, `${camera} - WebRTC error '${error}': ${description} See the documentation: https://docs.frigate.video/configuration/live/#live-view-faq`,
); );
onError?.(error); onError?.(error);
}, },

View File

@ -2,10 +2,7 @@ import { Recording } from "@/types/record";
import { DynamicPlayback } from "@/types/playback"; import { DynamicPlayback } from "@/types/playback";
import { PreviewController } from "../PreviewPlayer"; import { PreviewController } from "../PreviewPlayer";
import { TimeRange, TrackingDetailsSequence } from "@/types/timeline"; import { TimeRange, TrackingDetailsSequence } from "@/types/timeline";
import { import { calculateInpointOffset } from "@/utils/videoUtil";
calculateInpointOffset,
calculateSeekPosition,
} from "@/utils/videoUtil";
type PlayerMode = "playback" | "scrubbing"; type PlayerMode = "playback" | "scrubbing";
@ -75,20 +72,38 @@ export class DynamicVideoController {
return; return;
} }
if (
this.recordings.length == 0 ||
time < this.recordings[0].start_time ||
time > this.recordings[this.recordings.length - 1].end_time
) {
this.setNoRecording(true);
return;
}
if (this.playerMode != "playback") { if (this.playerMode != "playback") {
this.playerMode = "playback"; this.playerMode = "playback";
} }
const seekSeconds = calculateSeekPosition( let seekSeconds = 0;
time, (this.recordings || []).every((segment) => {
this.recordings, // if the next segment is past the desired time, stop calculating
this.inpointOffset, if (segment.start_time > time) {
); return false;
}
if (seekSeconds === undefined) { if (segment.end_time < time) {
this.setNoRecording(true); seekSeconds += segment.end_time - segment.start_time;
return; return true;
} }
seekSeconds +=
segment.end_time - segment.start_time - (segment.end_time - time);
return true;
});
// adjust for HLS inpoint offset
seekSeconds -= this.inpointOffset;
if (seekSeconds != 0) { if (seekSeconds != 0) {
this.playerController.currentTime = seekSeconds; this.playerController.currentTime = seekSeconds;

View File

@ -14,10 +14,7 @@ import { VideoResolutionType } from "@/types/live";
import axios from "axios"; import axios from "axios";
import { cn } from "@/lib/utils"; import { cn } from "@/lib/utils";
import { useTranslation } from "react-i18next"; import { useTranslation } from "react-i18next";
import { import { calculateInpointOffset } from "@/utils/videoUtil";
calculateInpointOffset,
calculateSeekPosition,
} from "@/utils/videoUtil";
import { isFirefox } from "react-device-detect"; import { isFirefox } from "react-device-detect";
/** /**
@ -112,10 +109,10 @@ export default function DynamicVideoPlayer({
const [isLoading, setIsLoading] = useState(false); const [isLoading, setIsLoading] = useState(false);
const [isBuffering, setIsBuffering] = useState(false); const [isBuffering, setIsBuffering] = useState(false);
const [loadingTimeout, setLoadingTimeout] = useState<NodeJS.Timeout>(); const [loadingTimeout, setLoadingTimeout] = useState<NodeJS.Timeout>();
const [source, setSource] = useState<HlsSource>({
// Don't set source until recordings load - we need accurate startPosition playlist: `${apiHost}vod/${camera}/start/${timeRange.after}/end/${timeRange.before}/master.m3u8`,
// to avoid hls.js clamping to video end when startPosition exceeds duration startPosition: startTimestamp ? timeRange.after - startTimestamp : 0,
const [source, setSource] = useState<HlsSource | undefined>(undefined); });
// start at correct time // start at correct time
@ -187,7 +184,7 @@ export default function DynamicVideoPlayer({
); );
useEffect(() => { useEffect(() => {
if (!recordings?.length) { if (!controller || !recordings?.length) {
if (recordings?.length == 0) { if (recordings?.length == 0) {
setNoRecording(true); setNoRecording(true);
} }
@ -195,6 +192,10 @@ export default function DynamicVideoPlayer({
return; return;
} }
if (playerRef.current) {
playerRef.current.autoplay = !isScrubbing;
}
let startPosition = undefined; let startPosition = undefined;
if (startTimestamp) { if (startTimestamp) {
@ -202,12 +203,14 @@ export default function DynamicVideoPlayer({
recordingParams.after, recordingParams.after,
(recordings || [])[0], (recordings || [])[0],
); );
const idealStartPosition = Math.max(
startPosition = calculateSeekPosition( 0,
startTimestamp, startTimestamp - timeRange.after - inpointOffset,
recordings,
inpointOffset,
); );
if (idealStartPosition >= recordings[0].start_time - timeRange.after) {
startPosition = idealStartPosition;
}
} }
setSource({ setSource({
@ -215,18 +218,6 @@ export default function DynamicVideoPlayer({
startPosition, startPosition,
}); });
// eslint-disable-next-line react-hooks/exhaustive-deps
}, [recordings]);
useEffect(() => {
if (!controller || !recordings?.length) {
return;
}
if (playerRef.current) {
playerRef.current.autoplay = !isScrubbing;
}
setLoadingTimeout(setTimeout(() => setIsLoading(true), 1000)); setLoadingTimeout(setTimeout(() => setIsLoading(true), 1000));
controller.newPlayback({ controller.newPlayback({
@ -234,7 +225,7 @@ export default function DynamicVideoPlayer({
timeRange, timeRange,
}); });
// we only want this to change when controller or recordings update // we only want this to change when recordings update
// eslint-disable-next-line react-hooks/exhaustive-deps // eslint-disable-next-line react-hooks/exhaustive-deps
}, [controller, recordings]); }, [controller, recordings]);
@ -272,48 +263,46 @@ export default function DynamicVideoPlayer({
return ( return (
<> <>
{source && ( <HlsVideoPlayer
<HlsVideoPlayer videoRef={playerRef}
videoRef={playerRef} containerRef={containerRef}
containerRef={containerRef} visible={!(isScrubbing || isLoading)}
visible={!(isScrubbing || isLoading)} currentSource={source}
currentSource={source} hotKeys={hotKeys}
hotKeys={hotKeys} supportsFullscreen={supportsFullscreen}
supportsFullscreen={supportsFullscreen} fullscreen={fullscreen}
fullscreen={fullscreen} inpointOffset={inpointOffset}
inpointOffset={inpointOffset} onTimeUpdate={onTimeUpdate}
onTimeUpdate={onTimeUpdate} onPlayerLoaded={onPlayerLoaded}
onPlayerLoaded={onPlayerLoaded} onClipEnded={onValidateClipEnd}
onClipEnded={onValidateClipEnd} onSeekToTime={(timestamp, play) => {
onSeekToTime={(timestamp, play) => { if (onSeekToTime) {
if (onSeekToTime) { onSeekToTime(timestamp, play);
onSeekToTime(timestamp, play); }
} }}
}} onPlaying={() => {
onPlaying={() => { if (isScrubbing) {
if (isScrubbing) { playerRef.current?.pause();
playerRef.current?.pause(); }
}
if (loadingTimeout) { if (loadingTimeout) {
clearTimeout(loadingTimeout); clearTimeout(loadingTimeout);
} }
setNoRecording(false); setNoRecording(false);
}} }}
setFullResolution={setFullResolution} setFullResolution={setFullResolution}
onUploadFrame={onUploadFrameToPlus} onUploadFrame={onUploadFrameToPlus}
toggleFullscreen={toggleFullscreen} toggleFullscreen={toggleFullscreen}
onError={(error) => { onError={(error) => {
if (error == "stalled" && !isScrubbing) { if (error == "stalled" && !isScrubbing) {
setIsBuffering(true); setIsBuffering(true);
} }
}} }}
isDetailMode={isDetailMode} isDetailMode={isDetailMode}
camera={contextCamera || camera} camera={contextCamera || camera}
currentTimeOverride={currentTime} currentTimeOverride={currentTime}
/> />
)}
<PreviewPlayer <PreviewPlayer
className={cn( className={cn(
className, className,

View File

@ -18,7 +18,7 @@ import { z } from "zod";
import axios from "axios"; import axios from "axios";
import { toast, Toaster } from "sonner"; import { toast, Toaster } from "sonner";
import { useTranslation } from "react-i18next"; import { useTranslation } from "react-i18next";
import { useState, useMemo, useEffect } from "react"; import { useState, useMemo } from "react";
import { LuTrash2, LuPlus } from "react-icons/lu"; import { LuTrash2, LuPlus } from "react-icons/lu";
import ActivityIndicator from "@/components/indicators/activity-indicator"; import ActivityIndicator from "@/components/indicators/activity-indicator";
import { FrigateConfig } from "@/types/frigateConfig"; import { FrigateConfig } from "@/types/frigateConfig";
@ -42,15 +42,7 @@ export default function CameraEditForm({
onCancel, onCancel,
}: CameraEditFormProps) { }: CameraEditFormProps) {
const { t } = useTranslation(["views/settings"]); const { t } = useTranslation(["views/settings"]);
const { data: config, mutate: mutateConfig } = const { data: config } = useSWR<FrigateConfig>("config");
useSWR<FrigateConfig>("config");
const { data: rawPaths, mutate: mutateRawPaths } = useSWR<{
cameras: Record<
string,
{ ffmpeg: { inputs: { path: string; roles: string[] }[] } }
>;
go2rtc: { streams: Record<string, string | string[]> };
}>(cameraName ? "config/raw_paths" : null);
const [isLoading, setIsLoading] = useState(false); const [isLoading, setIsLoading] = useState(false);
const formSchema = useMemo( const formSchema = useMemo(
@ -153,23 +145,14 @@ export default function CameraEditForm({
if (cameraName && config?.cameras[cameraName]) { if (cameraName && config?.cameras[cameraName]) {
const camera = config.cameras[cameraName]; const camera = config.cameras[cameraName];
defaultValues.enabled = camera.enabled ?? true; defaultValues.enabled = camera.enabled ?? true;
defaultValues.ffmpeg.inputs = camera.ffmpeg?.inputs?.length
// Use raw paths from the admin endpoint if available, otherwise fall back to masked paths ? camera.ffmpeg.inputs.map((input) => ({
const rawCameraData = rawPaths?.cameras?.[cameraName];
defaultValues.ffmpeg.inputs = rawCameraData?.ffmpeg?.inputs?.length
? rawCameraData.ffmpeg.inputs.map((input) => ({
path: input.path, path: input.path,
roles: input.roles as Role[], roles: input.roles as Role[],
})) }))
: camera.ffmpeg?.inputs?.length : defaultValues.ffmpeg.inputs;
? camera.ffmpeg.inputs.map((input) => ({
path: input.path,
roles: input.roles as Role[],
}))
: defaultValues.ffmpeg.inputs;
const go2rtcStreams = const go2rtcStreams = config.go2rtc?.streams || {};
rawPaths?.go2rtc?.streams || config.go2rtc?.streams || {};
const cameraStreams: Record<string, string[]> = {}; const cameraStreams: Record<string, string[]> = {};
// get candidate stream names for this camera. could be the camera's own name, // get candidate stream names for this camera. could be the camera's own name,
@ -213,60 +196,6 @@ export default function CameraEditForm({
mode: "onChange", mode: "onChange",
}); });
// Update form values when rawPaths loads
useEffect(() => {
if (
cameraName &&
config?.cameras[cameraName] &&
rawPaths?.cameras?.[cameraName]
) {
const camera = config.cameras[cameraName];
const rawCameraData = rawPaths.cameras[cameraName];
// Update ffmpeg inputs with raw paths
if (rawCameraData.ffmpeg?.inputs?.length) {
form.setValue(
"ffmpeg.inputs",
rawCameraData.ffmpeg.inputs.map((input) => ({
path: input.path,
roles: input.roles as Role[],
})),
);
}
// Update go2rtc streams with raw URLs
if (rawPaths.go2rtc?.streams) {
const validNames = new Set<string>();
validNames.add(cameraName);
camera.ffmpeg?.inputs?.forEach((input) => {
const restreamMatch = input.path.match(
/^rtsp:\/\/127\.0\.0\.1:8554\/([^?#/]+)(?:[?#].*)?$/,
);
if (restreamMatch) {
validNames.add(restreamMatch[1]);
}
});
const liveStreams = camera?.live?.streams;
if (liveStreams) {
Object.keys(liveStreams).forEach((key) => validNames.add(key));
}
const cameraStreams: Record<string, string[]> = {};
Object.entries(rawPaths.go2rtc.streams).forEach(([name, urls]) => {
if (validNames.has(name)) {
cameraStreams[name] = Array.isArray(urls) ? urls : [urls];
}
});
if (Object.keys(cameraStreams).length > 0) {
form.setValue("go2rtcStreams", cameraStreams);
}
}
}
}, [cameraName, config, rawPaths, form]);
const { fields, append, remove } = useFieldArray({ const { fields, append, remove } = useFieldArray({
control: form.control, control: form.control,
name: "ffmpeg.inputs", name: "ffmpeg.inputs",
@ -339,8 +268,6 @@ export default function CameraEditForm({
}), }),
{ position: "top-center" }, { position: "top-center" },
); );
mutateConfig();
mutateRawPaths();
if (onSave) onSave(); if (onSave) onSave();
}); });
} else { } else {
@ -350,8 +277,6 @@ export default function CameraEditForm({
}), }),
{ position: "top-center" }, { position: "top-center" },
); );
mutateConfig();
mutateRawPaths();
if (onSave) onSave(); if (onSave) onSave();
} }
} else { } else {

View File

@ -377,7 +377,7 @@ export default function Step1NameCamera({
); );
return selectedBrand && return selectedBrand &&
selectedBrand.value != "other" ? ( selectedBrand.value != "other" ? (
<Popover modal={true}> <Popover>
<PopoverTrigger asChild> <PopoverTrigger asChild>
<Button <Button
variant="ghost" variant="ghost"

View File

@ -600,7 +600,7 @@ export default function Step3StreamConfig({
<Label className="text-sm font-medium text-primary-variant"> <Label className="text-sm font-medium text-primary-variant">
{t("cameraWizard.step3.roles")} {t("cameraWizard.step3.roles")}
</Label> </Label>
<Popover modal={true}> <Popover>
<PopoverTrigger asChild> <PopoverTrigger asChild>
<Button variant="ghost" size="sm" className="h-4 w-4 p-0"> <Button variant="ghost" size="sm" className="h-4 w-4 p-0">
<LuInfo className="size-3" /> <LuInfo className="size-3" />
@ -670,7 +670,7 @@ export default function Step3StreamConfig({
<Label className="text-sm font-medium text-primary-variant"> <Label className="text-sm font-medium text-primary-variant">
{t("cameraWizard.step3.featuresTitle")} {t("cameraWizard.step3.featuresTitle")}
</Label> </Label>
<Popover modal={true}> <Popover>
<PopoverTrigger asChild> <PopoverTrigger asChild>
<Button variant="ghost" size="sm" className="h-4 w-4 p-0"> <Button variant="ghost" size="sm" className="h-4 w-4 p-0">
<LuInfo className="size-3" /> <LuInfo className="size-3" />

View File

@ -15,7 +15,6 @@ import {
ReviewSummary, ReviewSummary,
SegmentedReviewData, SegmentedReviewData,
} from "@/types/review"; } from "@/types/review";
import { TimelineType } from "@/types/timeline";
import { import {
getBeginningOfDayTimestamp, getBeginningOfDayTimestamp,
getEndOfDayTimestamp, getEndOfDayTimestamp,
@ -50,16 +49,6 @@ export default function Events() {
false, false,
); );
const [notificationTab, setNotificationTab] =
useState<TimelineType>("timeline");
useSearchEffect("tab", (tab: string) => {
if (tab === "timeline" || tab === "events" || tab === "detail") {
setNotificationTab(tab as TimelineType);
}
return true;
});
useSearchEffect("id", (reviewId: string) => { useSearchEffect("id", (reviewId: string) => {
axios axios
.get(`review/${reviewId}`) .get(`review/${reviewId}`)
@ -77,7 +66,7 @@ export default function Events() {
camera: resp.data.camera, camera: resp.data.camera,
startTime, startTime,
severity: resp.data.severity, severity: resp.data.severity,
timelineType: notificationTab, timelineType: "detail",
}, },
true, true,
); );

View File

@ -93,23 +93,19 @@ function Live() {
const allowedCameras = useAllowedCameras(); const allowedCameras = useAllowedCameras();
const includesBirdseye = useMemo(() => { const includesBirdseye = useMemo(() => {
// Restricted users should never have access to birdseye
if (isCustomRole) {
return false;
}
if ( if (
config && config &&
Object.keys(config.camera_groups).length && Object.keys(config.camera_groups).length &&
cameraGroup && cameraGroup &&
config.camera_groups[cameraGroup] && config.camera_groups[cameraGroup] &&
cameraGroup != "default" cameraGroup != "default" &&
(!isCustomRole || "birdseye" in allowedCameras)
) { ) {
return config.camera_groups[cameraGroup].cameras.includes("birdseye"); return config.camera_groups[cameraGroup].cameras.includes("birdseye");
} else { } else {
return false; return false;
} }
}, [config, cameraGroup, isCustomRole]); }, [config, cameraGroup, allowedCameras, isCustomRole]);
const cameras = useMemo(() => { const cameras = useMemo(() => {
if (!config) { if (!config) {

View File

@ -26,7 +26,7 @@ import useSWR from "swr";
import FilterSwitch from "@/components/filter/FilterSwitch"; import FilterSwitch from "@/components/filter/FilterSwitch";
import { ZoneMaskFilterButton } from "@/components/filter/ZoneMaskFilter"; import { ZoneMaskFilterButton } from "@/components/filter/ZoneMaskFilter";
import { PolygonType } from "@/types/canvas"; import { PolygonType } from "@/types/canvas";
import CameraReviewSettingsView from "@/views/settings/CameraReviewSettingsView"; import CameraSettingsView from "@/views/settings/CameraSettingsView";
import CameraManagementView from "@/views/settings/CameraManagementView"; import CameraManagementView from "@/views/settings/CameraManagementView";
import MotionTunerView from "@/views/settings/MotionTunerView"; import MotionTunerView from "@/views/settings/MotionTunerView";
import MasksAndZonesView from "@/views/settings/MasksAndZonesView"; import MasksAndZonesView from "@/views/settings/MasksAndZonesView";
@ -93,7 +93,7 @@ const settingsGroups = [
label: "cameras", label: "cameras",
items: [ items: [
{ key: "cameraManagement", component: CameraManagementView }, { key: "cameraManagement", component: CameraManagementView },
{ key: "cameraReview", component: CameraReviewSettingsView }, { key: "cameraReview", component: CameraSettingsView },
{ key: "masksAndZones", component: MasksAndZonesView }, { key: "masksAndZones", component: MasksAndZonesView },
{ key: "motionTuner", component: MotionTunerView }, { key: "motionTuner", component: MotionTunerView },
], ],

View File

@ -1,5 +1,4 @@
import { ReviewSeverity } from "./review"; import { ReviewSeverity } from "./review";
import { TimelineType } from "./timeline";
export type Recording = { export type Recording = {
id: string; id: string;
@ -38,7 +37,7 @@ export type RecordingStartingPoint = {
camera: string; camera: string;
startTime: number; startTime: number;
severity: ReviewSeverity; severity: ReviewSeverity;
timelineType?: TimelineType; timelineType?: "timeline" | "events" | "detail";
}; };
export type RecordingPlayerError = "stalled" | "startup"; export type RecordingPlayerError = "stalled" | "startup";

View File

@ -24,57 +24,3 @@ export function calculateInpointOffset(
return 0; return 0;
} }
/**
* Calculates the video player time (in seconds) for a given timestamp
* by iterating through recording segments and summing their durations.
* This accounts for the fact that the video is a concatenation of segments,
* not a single continuous stream.
*
* @param timestamp - The target timestamp to seek to
* @param recordings - Array of recording segments
* @param inpointOffset - HLS inpoint offset to subtract from the result
* @returns The calculated seek position in seconds, or undefined if timestamp is out of range
*/
export function calculateSeekPosition(
timestamp: number,
recordings: Recording[],
inpointOffset: number = 0,
): number | undefined {
if (!recordings || recordings.length === 0) {
return undefined;
}
// Check if timestamp is within the recordings range
if (
timestamp < recordings[0].start_time ||
timestamp > recordings[recordings.length - 1].end_time
) {
return undefined;
}
let seekSeconds = 0;
(recordings || []).every((segment) => {
// if the next segment is past the desired time, stop calculating
if (segment.start_time > timestamp) {
return false;
}
if (segment.end_time < timestamp) {
// Add the full duration of this segment
seekSeconds += segment.end_time - segment.start_time;
return true;
}
// We're in this segment - calculate position within it
seekSeconds +=
segment.end_time - segment.start_time - (segment.end_time - timestamp);
return true;
});
// Adjust for HLS inpoint offset
seekSeconds -= inpointOffset;
return seekSeconds >= 0 ? seekSeconds : undefined;
}

View File

@ -16,6 +16,7 @@ import { useCallback, useEffect, useMemo, useState } from "react";
import { useTranslation } from "react-i18next"; import { useTranslation } from "react-i18next";
import { FaFolderPlus } from "react-icons/fa"; import { FaFolderPlus } from "react-icons/fa";
import { MdModelTraining } from "react-icons/md"; import { MdModelTraining } from "react-icons/md";
import { LuPencil, LuTrash2 } from "react-icons/lu";
import { FiMoreVertical } from "react-icons/fi"; import { FiMoreVertical } from "react-icons/fi";
import useSWR from "swr"; import useSWR from "swr";
import Heading from "@/components/ui/heading"; import Heading from "@/components/ui/heading";
@ -39,7 +40,6 @@ import {
AlertDialogTitle, AlertDialogTitle,
} from "@/components/ui/alert-dialog"; } from "@/components/ui/alert-dialog";
import BlurredIconButton from "@/components/button/BlurredIconButton"; import BlurredIconButton from "@/components/button/BlurredIconButton";
import { Skeleton } from "@/components/ui/skeleton";
const allModelTypes = ["objects", "states"] as const; const allModelTypes = ["objects", "states"] as const;
type ModelType = (typeof allModelTypes)[number]; type ModelType = (typeof allModelTypes)[number];
@ -333,7 +333,9 @@ function ModelCard({ config, onClick, onUpdate, onDelete }: ModelCardProps) {
<ImageShadowOverlay lowerClassName="h-[30%] z-0" /> <ImageShadowOverlay lowerClassName="h-[30%] z-0" />
</> </>
) : ( ) : (
<Skeleton className="flex size-full items-center justify-center" /> <div className="flex size-full items-center justify-center bg-background_alt">
<MdModelTraining className="size-16 text-muted-foreground" />
</div>
)} )}
<div className="absolute bottom-2 left-3 text-lg text-white smart-capitalize"> <div className="absolute bottom-2 left-3 text-lg text-white smart-capitalize">
{config.name} {config.name}
@ -350,9 +352,11 @@ function ModelCard({ config, onClick, onUpdate, onDelete }: ModelCardProps) {
onClick={(e) => e.stopPropagation()} onClick={(e) => e.stopPropagation()}
> >
<DropdownMenuItem onClick={handleEditClick}> <DropdownMenuItem onClick={handleEditClick}>
<LuPencil className="mr-2 size-4" />
<span>{t("button.edit", { ns: "common" })}</span> <span>{t("button.edit", { ns: "common" })}</span>
</DropdownMenuItem> </DropdownMenuItem>
<DropdownMenuItem onClick={handleDeleteClick}> <DropdownMenuItem onClick={handleDeleteClick}>
<LuTrash2 className="mr-2 size-4" />
<span>{t("button.delete", { ns: "common" })}</span> <span>{t("button.delete", { ns: "common" })}</span>
</DropdownMenuItem> </DropdownMenuItem>
</DropdownMenuContent> </DropdownMenuContent>

View File

@ -799,7 +799,7 @@ function DetectionReview({
(itemsToReview ?? 0) > 0 && ( (itemsToReview ?? 0) > 0 && (
<div className="col-span-full flex items-center justify-center"> <div className="col-span-full flex items-center justify-center">
<Button <Button
className="text-balance text-white" className="text-white"
aria-label={t("markTheseItemsAsReviewed")} aria-label={t("markTheseItemsAsReviewed")}
variant="select" variant="select"
onClick={() => { onClick={() => {

View File

@ -16,6 +16,7 @@ import ImageLoadingIndicator from "@/components/indicators/ImageLoadingIndicator
import useImageLoaded from "@/hooks/use-image-loaded"; import useImageLoaded from "@/hooks/use-image-loaded";
import ActivityIndicator from "@/components/indicators/activity-indicator"; import ActivityIndicator from "@/components/indicators/activity-indicator";
import { useTrackedObjectUpdate } from "@/api/ws"; import { useTrackedObjectUpdate } from "@/api/ws";
import { isEqual } from "lodash";
import TimeAgo from "@/components/dynamic/TimeAgo"; import TimeAgo from "@/components/dynamic/TimeAgo";
import SearchResultActions from "@/components/menu/SearchResultActions"; import SearchResultActions from "@/components/menu/SearchResultActions";
import { SearchTab } from "@/components/overlay/detail/SearchDetailDialog"; import { SearchTab } from "@/components/overlay/detail/SearchDetailDialog";
@ -24,12 +25,14 @@ import { useTranslation } from "react-i18next";
import { getTranslatedLabel } from "@/utils/i18n"; import { getTranslatedLabel } from "@/utils/i18n";
type ExploreViewProps = { type ExploreViewProps = {
searchDetail: SearchResult | undefined;
setSearchDetail: (search: SearchResult | undefined) => void; setSearchDetail: (search: SearchResult | undefined) => void;
setSimilaritySearch: (search: SearchResult) => void; setSimilaritySearch: (search: SearchResult) => void;
onSelectSearch: (item: SearchResult, ctrl: boolean, page?: SearchTab) => void; onSelectSearch: (item: SearchResult, ctrl: boolean, page?: SearchTab) => void;
}; };
export default function ExploreView({ export default function ExploreView({
searchDetail,
setSearchDetail, setSearchDetail,
setSimilaritySearch, setSimilaritySearch,
onSelectSearch, onSelectSearch,
@ -80,6 +83,20 @@ export default function ExploreView({
} }
}, [wsUpdate, mutate]); }, [wsUpdate, mutate]);
// update search detail when results change
useEffect(() => {
if (searchDetail && events) {
const updatedSearchDetail = events.find(
(result) => result.id === searchDetail.id,
);
if (updatedSearchDetail && !isEqual(updatedSearchDetail, searchDetail)) {
setSearchDetail(updatedSearchDetail);
}
}
}, [events, searchDetail, setSearchDetail]);
if (isLoading) { if (isLoading) {
return ( return (
<ActivityIndicator className="absolute left-1/2 top-1/2 -translate-x-1/2 -translate-y-1/2" /> <ActivityIndicator className="absolute left-1/2 top-1/2 -translate-x-1/2 -translate-y-1/2" />

View File

@ -850,29 +850,6 @@ function FrigateCameraFeatures({
} }
}, [activeToastId, t]); }, [activeToastId, t]);
const endEventViaBeacon = useCallback(() => {
if (!recordingEventIdRef.current) return;
const url = `${window.location.origin}/api/events/${recordingEventIdRef.current}/end`;
const payload = JSON.stringify({
end_time: Math.ceil(Date.now() / 1000),
});
// this needs to be a synchronous XMLHttpRequest to guarantee the PUT
// reaches the server before the browser kills the page
const xhr = new XMLHttpRequest();
try {
xhr.open("PUT", url, false);
xhr.setRequestHeader("Content-Type", "application/json");
xhr.setRequestHeader("X-CSRF-TOKEN", "1");
xhr.setRequestHeader("X-CACHE-BYPASS", "1");
xhr.withCredentials = true;
xhr.send(payload);
} catch (e) {
// Silently ignore errors during unload
}
}, []);
const handleEventButtonClick = useCallback(() => { const handleEventButtonClick = useCallback(() => {
if (isRecording) { if (isRecording) {
endEvent(); endEvent();
@ -910,19 +887,8 @@ function FrigateCameraFeatures({
}, [camera.name, isRestreamed, preferredLiveMode, t]); }, [camera.name, isRestreamed, preferredLiveMode, t]);
useEffect(() => { useEffect(() => {
// Handle page unload/close (browser close, tab close, refresh, navigation to external site)
const handleBeforeUnload = () => {
if (recordingEventIdRef.current) {
endEventViaBeacon();
}
};
window.addEventListener("beforeunload", handleBeforeUnload);
// ensure manual event is stopped when component unmounts // ensure manual event is stopped when component unmounts
return () => { return () => {
window.removeEventListener("beforeunload", handleBeforeUnload);
if (recordingEventIdRef.current) { if (recordingEventIdRef.current) {
endEvent(); endEvent();
} }

View File

@ -20,14 +20,7 @@ import {
FrigateConfig, FrigateConfig,
} from "@/types/frigateConfig"; } from "@/types/frigateConfig";
import { ReviewSegment } from "@/types/review"; import { ReviewSegment } from "@/types/review";
import { import { useCallback, useEffect, useMemo, useRef, useState } from "react";
useCallback,
useContext,
useEffect,
useMemo,
useRef,
useState,
} from "react";
import { import {
isDesktop, isDesktop,
isMobile, isMobile,
@ -53,8 +46,6 @@ import { useStreamingSettings } from "@/context/streaming-settings-provider";
import { useTranslation } from "react-i18next"; import { useTranslation } from "react-i18next";
import { EmptyCard } from "@/components/card/EmptyCard"; import { EmptyCard } from "@/components/card/EmptyCard";
import { BsFillCameraVideoOffFill } from "react-icons/bs"; import { BsFillCameraVideoOffFill } from "react-icons/bs";
import { AuthContext } from "@/context/auth-context";
import { useIsCustomRole } from "@/hooks/use-is-custom-role";
type LiveDashboardViewProps = { type LiveDashboardViewProps = {
cameras: CameraConfig[]; cameras: CameraConfig[];
@ -383,6 +374,10 @@ export default function LiveDashboardView({
onSaveMuting(true); onSaveMuting(true);
}; };
if (cameras.length == 0 && !includeBirdseye) {
return <NoCameraView />;
}
return ( return (
<div <div
className="scrollbar-container size-full select-none overflow-y-auto px-1 pt-2 md:p-2" className="scrollbar-container size-full select-none overflow-y-auto px-1 pt-2 md:p-2"
@ -444,215 +439,198 @@ export default function LiveDashboardView({
</div> </div>
)} )}
{cameras.length == 0 && !includeBirdseye ? ( {!fullscreen && events && events.length > 0 && (
<NoCameraView /> <ScrollArea>
) : ( <TooltipProvider>
<div className="flex items-center gap-2 px-1">
{events.map((event) => {
return (
<AnimatedEventCard
key={event.id}
event={event}
selectedGroup={cameraGroup}
updateEvents={updateEvents}
/>
);
})}
</div>
</TooltipProvider>
<ScrollBar orientation="horizontal" />
</ScrollArea>
)}
{!cameraGroup || cameraGroup == "default" || isMobileOnly ? (
<> <>
{!fullscreen && events && events.length > 0 && ( <div
<ScrollArea> className={cn(
<TooltipProvider> "mt-2 grid grid-cols-1 gap-2 px-2 md:gap-4",
<div className="flex items-center gap-2 px-1"> mobileLayout == "grid" &&
{events.map((event) => { "grid-cols-2 xl:grid-cols-3 3xl:grid-cols-4",
return ( isMobile && "px-0",
<AnimatedEventCard )}
key={event.id} >
event={event} {includeBirdseye && birdseyeConfig?.enabled && (
selectedGroup={cameraGroup}
updateEvents={updateEvents}
/>
);
})}
</div>
</TooltipProvider>
<ScrollBar orientation="horizontal" />
</ScrollArea>
)}
{!cameraGroup || cameraGroup == "default" || isMobileOnly ? (
<>
<div <div
className={cn( className={(() => {
"mt-2 grid grid-cols-1 gap-2 px-2 md:gap-4",
mobileLayout == "grid" &&
"grid-cols-2 xl:grid-cols-3 3xl:grid-cols-4",
isMobile && "px-0",
)}
>
{includeBirdseye && birdseyeConfig?.enabled && (
<div
className={(() => {
const aspectRatio =
birdseyeConfig.width / birdseyeConfig.height;
if (aspectRatio > 2) {
return `${mobileLayout == "grid" && "col-span-2"} aspect-wide`;
} else if (aspectRatio < 1) {
return `${mobileLayout == "grid" && "row-span-2 h-full"} aspect-tall`;
} else {
return "aspect-video";
}
})()}
ref={birdseyeContainerRef}
>
<BirdseyeLivePlayer
birdseyeConfig={birdseyeConfig}
liveMode={birdseyeConfig.restream ? "mse" : "jsmpeg"}
onClick={() => onSelectCamera("birdseye")}
containerRef={birdseyeContainerRef}
/>
</div>
)}
{cameras.map((camera) => {
let grow;
const aspectRatio = const aspectRatio =
camera.detect.width / camera.detect.height; birdseyeConfig.width / birdseyeConfig.height;
if (aspectRatio > 2) { if (aspectRatio > 2) {
grow = `${mobileLayout == "grid" && "col-span-2"} aspect-wide`; return `${mobileLayout == "grid" && "col-span-2"} aspect-wide`;
} else if (aspectRatio < 1) { } else if (aspectRatio < 1) {
grow = `${mobileLayout == "grid" && "row-span-2 h-full"} aspect-tall`; return `${mobileLayout == "grid" && "row-span-2 h-full"} aspect-tall`;
} else { } else {
grow = "aspect-video"; return "aspect-video";
} }
const availableStreams = camera.live.streams || {}; })()}
const firstStreamEntry = ref={birdseyeContainerRef}
Object.values(availableStreams)[0] || ""; >
<BirdseyeLivePlayer
const streamNameFromSettings = birdseyeConfig={birdseyeConfig}
currentGroupStreamingSettings?.[camera.name]?.streamName || liveMode={birdseyeConfig.restream ? "mse" : "jsmpeg"}
""; onClick={() => onSelectCamera("birdseye")}
const streamExists = containerRef={birdseyeContainerRef}
streamNameFromSettings && />
Object.values(availableStreams).includes(
streamNameFromSettings,
);
const streamName = streamExists
? streamNameFromSettings
: firstStreamEntry;
const streamType =
currentGroupStreamingSettings?.[camera.name]?.streamType;
const autoLive =
streamType !== undefined
? streamType !== "no-streaming"
: undefined;
const showStillWithoutActivity =
currentGroupStreamingSettings?.[camera.name]?.streamType !==
"continuous";
const useWebGL =
currentGroupStreamingSettings?.[camera.name]
?.compatibilityMode || false;
return (
<LiveContextMenu
className={grow}
key={camera.name}
camera={camera.name}
cameraGroup={cameraGroup}
streamName={streamName}
preferredLiveMode={
preferredLiveModes[camera.name] ?? "mse"
}
isRestreamed={isRestreamedStates[camera.name]}
supportsAudio={
supportsAudioOutputStates[streamName]?.supportsAudio ??
false
}
audioState={audioStates[camera.name]}
toggleAudio={() => toggleAudio(camera.name)}
statsState={statsStates[camera.name]}
toggleStats={() => toggleStats(camera.name)}
volumeState={volumeStates[camera.name] ?? 1}
setVolumeState={(value) =>
setVolumeStates({
[camera.name]: value,
})
}
muteAll={muteAll}
unmuteAll={unmuteAll}
resetPreferredLiveMode={() =>
resetPreferredLiveMode(camera.name)
}
config={config}
>
<LivePlayer
cameraRef={cameraRef}
key={camera.name}
className={`${grow} rounded-lg bg-black md:rounded-2xl`}
windowVisible={
windowVisible && visibleCameras.includes(camera.name)
}
cameraConfig={camera}
preferredLiveMode={
preferredLiveModes[camera.name] ?? "mse"
}
autoLive={autoLive ?? globalAutoLive}
showStillWithoutActivity={
showStillWithoutActivity ?? true
}
alwaysShowCameraName={displayCameraNames}
useWebGL={useWebGL}
playInBackground={false}
showStats={statsStates[camera.name]}
streamName={streamName}
onClick={() => onSelectCamera(camera.name)}
onError={(e) => handleError(camera.name, e)}
onResetLiveMode={() =>
resetPreferredLiveMode(camera.name)
}
playAudio={audioStates[camera.name] ?? false}
volume={volumeStates[camera.name]}
/>
</LiveContextMenu>
);
})}
</div> </div>
{isDesktop && ( )}
<div {cameras.map((camera) => {
className={cn( let grow;
"fixed", const aspectRatio = camera.detect.width / camera.detect.height;
isDesktop && "bottom-12 lg:bottom-9", if (aspectRatio > 2) {
isMobile && "bottom-12 lg:bottom-16", grow = `${mobileLayout == "grid" && "col-span-2"} aspect-wide`;
hasScrollbar && isDesktop ? "right-6" : "right-3", } else if (aspectRatio < 1) {
"z-50 flex flex-row gap-2", grow = `${mobileLayout == "grid" && "row-span-2 h-full"} aspect-tall`;
)} } else {
grow = "aspect-video";
}
const availableStreams = camera.live.streams || {};
const firstStreamEntry = Object.values(availableStreams)[0] || "";
const streamNameFromSettings =
currentGroupStreamingSettings?.[camera.name]?.streamName || "";
const streamExists =
streamNameFromSettings &&
Object.values(availableStreams).includes(
streamNameFromSettings,
);
const streamName = streamExists
? streamNameFromSettings
: firstStreamEntry;
const streamType =
currentGroupStreamingSettings?.[camera.name]?.streamType;
const autoLive =
streamType !== undefined
? streamType !== "no-streaming"
: undefined;
const showStillWithoutActivity =
currentGroupStreamingSettings?.[camera.name]?.streamType !==
"continuous";
const useWebGL =
currentGroupStreamingSettings?.[camera.name]
?.compatibilityMode || false;
return (
<LiveContextMenu
className={grow}
key={camera.name}
camera={camera.name}
cameraGroup={cameraGroup}
streamName={streamName}
preferredLiveMode={preferredLiveModes[camera.name] ?? "mse"}
isRestreamed={isRestreamedStates[camera.name]}
supportsAudio={
supportsAudioOutputStates[streamName]?.supportsAudio ??
false
}
audioState={audioStates[camera.name]}
toggleAudio={() => toggleAudio(camera.name)}
statsState={statsStates[camera.name]}
toggleStats={() => toggleStats(camera.name)}
volumeState={volumeStates[camera.name] ?? 1}
setVolumeState={(value) =>
setVolumeStates({
[camera.name]: value,
})
}
muteAll={muteAll}
unmuteAll={unmuteAll}
resetPreferredLiveMode={() =>
resetPreferredLiveMode(camera.name)
}
config={config}
> >
<Tooltip> <LivePlayer
<TooltipTrigger asChild> cameraRef={cameraRef}
<div key={camera.name}
className="cursor-pointer rounded-lg bg-secondary text-secondary-foreground opacity-60 transition-all duration-300 hover:bg-muted hover:opacity-100" className={`${grow} rounded-lg bg-black md:rounded-2xl`}
onClick={toggleFullscreen} windowVisible={
> windowVisible && visibleCameras.includes(camera.name)
{fullscreen ? ( }
<FaCompress className="size-5 md:m-[6px]" /> cameraConfig={camera}
) : ( preferredLiveMode={preferredLiveModes[camera.name] ?? "mse"}
<FaExpand className="size-5 md:m-[6px]" /> autoLive={autoLive ?? globalAutoLive}
)} showStillWithoutActivity={showStillWithoutActivity ?? true}
</div> alwaysShowCameraName={displayCameraNames}
</TooltipTrigger> useWebGL={useWebGL}
<TooltipContent> playInBackground={false}
{fullscreen showStats={statsStates[camera.name]}
? t("button.exitFullscreen", { ns: "common" }) streamName={streamName}
: t("button.fullscreen", { ns: "common" })} onClick={() => onSelectCamera(camera.name)}
</TooltipContent> onError={(e) => handleError(camera.name, e)}
</Tooltip> onResetLiveMode={() => resetPreferredLiveMode(camera.name)}
</div> playAudio={audioStates[camera.name] ?? false}
volume={volumeStates[camera.name]}
/>
</LiveContextMenu>
);
})}
</div>
{isDesktop && (
<div
className={cn(
"fixed",
isDesktop && "bottom-12 lg:bottom-9",
isMobile && "bottom-12 lg:bottom-16",
hasScrollbar && isDesktop ? "right-6" : "right-3",
"z-50 flex flex-row gap-2",
)} )}
</> >
) : ( <Tooltip>
<DraggableGridLayout <TooltipTrigger asChild>
cameras={cameras} <div
cameraGroup={cameraGroup} className="cursor-pointer rounded-lg bg-secondary text-secondary-foreground opacity-60 transition-all duration-300 hover:bg-muted hover:opacity-100"
containerRef={containerRef} onClick={toggleFullscreen}
cameraRef={cameraRef} >
includeBirdseye={includeBirdseye} {fullscreen ? (
onSelectCamera={onSelectCamera} <FaCompress className="size-5 md:m-[6px]" />
windowVisible={windowVisible} ) : (
visibleCameras={visibleCameras} <FaExpand className="size-5 md:m-[6px]" />
isEditMode={isEditMode} )}
setIsEditMode={setIsEditMode} </div>
fullscreen={fullscreen} </TooltipTrigger>
toggleFullscreen={toggleFullscreen} <TooltipContent>
/> {fullscreen
? t("button.exitFullscreen", { ns: "common" })
: t("button.fullscreen", { ns: "common" })}
</TooltipContent>
</Tooltip>
</div>
)} )}
</> </>
) : (
<DraggableGridLayout
cameras={cameras}
cameraGroup={cameraGroup}
containerRef={containerRef}
cameraRef={cameraRef}
includeBirdseye={includeBirdseye}
onSelectCamera={onSelectCamera}
windowVisible={windowVisible}
visibleCameras={visibleCameras}
isEditMode={isEditMode}
setIsEditMode={setIsEditMode}
fullscreen={fullscreen}
toggleFullscreen={toggleFullscreen}
/>
)} )}
</div> </div>
); );
@ -660,26 +638,15 @@ export default function LiveDashboardView({
function NoCameraView() { function NoCameraView() {
const { t } = useTranslation(["views/live"]); const { t } = useTranslation(["views/live"]);
const { auth } = useContext(AuthContext);
const isCustomRole = useIsCustomRole();
// Check if this is a restricted user with no cameras in this group
const isRestricted = isCustomRole && auth.isAuthenticated;
return ( return (
<div className="flex size-full items-center justify-center"> <div className="flex size-full items-center justify-center">
<EmptyCard <EmptyCard
icon={<BsFillCameraVideoOffFill className="size-8" />} icon={<BsFillCameraVideoOffFill className="size-8" />}
title={ title={t("noCameras.title")}
isRestricted ? t("noCameras.restricted.title") : t("noCameras.title") description={t("noCameras.description")}
} buttonText={t("noCameras.buttonText")}
description={ link="/settings?page=cameraManagement"
isRestricted
? t("noCameras.restricted.description")
: t("noCameras.description")
}
buttonText={!isRestricted ? t("noCameras.buttonText") : undefined}
link={!isRestricted ? "/settings?page=cameraManagement" : undefined}
/> />
</div> </div>
); );

View File

@ -19,6 +19,7 @@ import useKeyboardListener, {
import scrollIntoView from "scroll-into-view-if-needed"; import scrollIntoView from "scroll-into-view-if-needed";
import InputWithTags from "@/components/input/InputWithTags"; import InputWithTags from "@/components/input/InputWithTags";
import { ScrollArea, ScrollBar } from "@/components/ui/scroll-area"; import { ScrollArea, ScrollBar } from "@/components/ui/scroll-area";
import { isEqual } from "lodash";
import { formatDateToLocaleString } from "@/utils/dateUtil"; import { formatDateToLocaleString } from "@/utils/dateUtil";
import SearchThumbnailFooter from "@/components/card/SearchThumbnailFooter"; import SearchThumbnailFooter from "@/components/card/SearchThumbnailFooter";
import ExploreSettings from "@/components/settings/SearchSettings"; import ExploreSettings from "@/components/settings/SearchSettings";
@ -212,7 +213,7 @@ export default function SearchView({
// detail // detail
const [selectedId, setSelectedId] = useState<string>(); const [searchDetail, setSearchDetail] = useState<SearchResult>();
const [page, setPage] = useState<SearchTab>("snapshot"); const [page, setPage] = useState<SearchTab>("snapshot");
// remove duplicate event ids // remove duplicate event ids
@ -228,16 +229,6 @@ export default function SearchView({
return results; return results;
}, [searchResults]); }, [searchResults]);
const searchDetail = useMemo(() => {
if (!selectedId) return undefined;
// summary view
if (defaultView === "summary" && exploreEvents) {
return exploreEvents.find((r) => r.id === selectedId);
}
// grid view
return uniqueResults.find((r) => r.id === selectedId);
}, [selectedId, uniqueResults, exploreEvents, defaultView]);
// search interaction // search interaction
const [selectedObjects, setSelectedObjects] = useState<string[]>([]); const [selectedObjects, setSelectedObjects] = useState<string[]>([]);
@ -265,7 +256,7 @@ export default function SearchView({
} }
} else { } else {
setPage(page); setPage(page);
setSelectedId(item.id); setSearchDetail(item);
} }
}, },
[selectedObjects], [selectedObjects],
@ -304,12 +295,26 @@ export default function SearchView({
} }
}; };
// clear selected item when search results clear // update search detail when results change
useEffect(() => { useEffect(() => {
if (!searchResults && !exploreEvents) { if (searchDetail) {
setSelectedId(undefined); const results =
defaultView === "summary" ? exploreEvents : searchResults?.flat();
if (results) {
const updatedSearchDetail = results.find(
(result) => result.id === searchDetail.id,
);
if (
updatedSearchDetail &&
!isEqual(updatedSearchDetail, searchDetail)
) {
setSearchDetail(updatedSearchDetail);
}
}
} }
}, [searchResults, exploreEvents]); }, [searchResults, exploreEvents, searchDetail, defaultView]);
const hasExistingSearch = useMemo( const hasExistingSearch = useMemo(
() => searchResults != undefined || searchFilter != undefined, () => searchResults != undefined || searchFilter != undefined,
@ -335,7 +340,7 @@ export default function SearchView({
? results.length - 1 ? results.length - 1
: (currentIndex - 1 + results.length) % results.length; : (currentIndex - 1 + results.length) % results.length;
setSelectedId(results[newIndex].id); setSearchDetail(results[newIndex]);
} }
}, [uniqueResults, exploreEvents, searchDetail, defaultView]); }, [uniqueResults, exploreEvents, searchDetail, defaultView]);
@ -352,7 +357,7 @@ export default function SearchView({
const newIndex = const newIndex =
currentIndex === -1 ? 0 : (currentIndex + 1) % results.length; currentIndex === -1 ? 0 : (currentIndex + 1) % results.length;
setSelectedId(results[newIndex].id); setSearchDetail(results[newIndex]);
} }
}, [uniqueResults, exploreEvents, searchDetail, defaultView]); }, [uniqueResults, exploreEvents, searchDetail, defaultView]);
@ -504,7 +509,7 @@ export default function SearchView({
<SearchDetailDialog <SearchDetailDialog
search={searchDetail} search={searchDetail}
page={page} page={page}
setSearch={(item) => setSelectedId(item?.id)} setSearch={setSearchDetail}
setSearchPage={setPage} setSearchPage={setPage}
setSimilarity={ setSimilarity={
searchDetail && (() => setSimilaritySearch(searchDetail)) searchDetail && (() => setSimilaritySearch(searchDetail))
@ -624,7 +629,7 @@ export default function SearchView({
detail: boolean, detail: boolean,
) => { ) => {
if (detail && selectedObjects.length == 0) { if (detail && selectedObjects.length == 0) {
setSelectedId(value.id); setSearchDetail(value);
} else { } else {
onSelectSearch( onSelectSearch(
value, value,
@ -719,7 +724,8 @@ export default function SearchView({
defaultView == "summary" && ( defaultView == "summary" && (
<div className="scrollbar-container flex size-full flex-col overflow-y-auto"> <div className="scrollbar-container flex size-full flex-col overflow-y-auto">
<ExploreView <ExploreView
setSearchDetail={(item) => setSelectedId(item?.id)} searchDetail={searchDetail}
setSearchDetail={setSearchDetail}
setSimilaritySearch={setSimilaritySearch} setSimilaritySearch={setSimilaritySearch}
onSelectSearch={onSelectSearch} onSelectSearch={onSelectSearch}
/> />

View File

@ -5,9 +5,17 @@ import { Button } from "@/components/ui/button";
import useSWR from "swr"; import useSWR from "swr";
import { FrigateConfig } from "@/types/frigateConfig"; import { FrigateConfig } from "@/types/frigateConfig";
import { useTranslation } from "react-i18next"; import { useTranslation } from "react-i18next";
import { Label } from "@/components/ui/label";
import CameraEditForm from "@/components/settings/CameraEditForm"; import CameraEditForm from "@/components/settings/CameraEditForm";
import CameraWizardDialog from "@/components/settings/CameraWizardDialog"; import CameraWizardDialog from "@/components/settings/CameraWizardDialog";
import { LuPlus } from "react-icons/lu"; import { LuPlus } from "react-icons/lu";
import {
Select,
SelectContent,
SelectItem,
SelectTrigger,
SelectValue,
} from "@/components/ui/select";
import { IoMdArrowRoundBack } from "react-icons/io"; import { IoMdArrowRoundBack } from "react-icons/io";
import { isDesktop } from "react-device-detect"; import { isDesktop } from "react-device-detect";
import { CameraNameLabel } from "@/components/camera/FriendlyNameLabel"; import { CameraNameLabel } from "@/components/camera/FriendlyNameLabel";
@ -82,6 +90,31 @@ export default function CameraManagementView({
</Button> </Button>
{cameras.length > 0 && ( {cameras.length > 0 && (
<> <>
<div className="my-4 flex flex-col gap-2">
<Label>{t("cameraManagement.editCamera")}</Label>
<Select
onValueChange={(value) => {
setEditCameraName(value);
setViewMode("edit");
}}
>
<SelectTrigger className="w-[180px]">
<SelectValue
placeholder={t("cameraManagement.selectCamera")}
/>
</SelectTrigger>
<SelectContent>
{cameras.map((camera) => {
return (
<SelectItem key={camera} value={camera}>
<CameraNameLabel camera={camera} />
</SelectItem>
);
})}
</SelectContent>
</Select>
</div>
<Separator className="my-2 flex bg-secondary" /> <Separator className="my-2 flex bg-secondary" />
<div className="max-w-7xl space-y-4"> <div className="max-w-7xl space-y-4">
<Heading as="h4" className="my-2"> <Heading as="h4" className="my-2">

View File

@ -1,738 +0,0 @@
import Heading from "@/components/ui/heading";
import { useCallback, useContext, useEffect, useMemo, useState } from "react";
import { Toaster, toast } from "sonner";
import {
Form,
FormControl,
FormDescription,
FormField,
FormItem,
FormLabel,
FormMessage,
} from "@/components/ui/form";
import { zodResolver } from "@hookform/resolvers/zod";
import { useForm } from "react-hook-form";
import { z } from "zod";
import { Separator } from "@/components/ui/separator";
import { Button } from "@/components/ui/button";
import useSWR from "swr";
import { FrigateConfig } from "@/types/frigateConfig";
import { Checkbox } from "@/components/ui/checkbox";
import ActivityIndicator from "@/components/indicators/activity-indicator";
import { StatusBarMessagesContext } from "@/context/statusbar-provider";
import axios from "axios";
import { Link } from "react-router-dom";
import { LuExternalLink } from "react-icons/lu";
import { MdCircle } from "react-icons/md";
import { cn } from "@/lib/utils";
import { Trans, useTranslation } from "react-i18next";
import { Switch } from "@/components/ui/switch";
import { Label } from "@/components/ui/label";
import { useDocDomain } from "@/hooks/use-doc-domain";
import { getTranslatedLabel } from "@/utils/i18n";
import {
useAlertsState,
useDetectionsState,
useObjectDescriptionState,
useReviewDescriptionState,
} from "@/api/ws";
import { useCameraFriendlyName } from "@/hooks/use-camera-friendly-name";
import { resolveZoneName } from "@/hooks/use-zone-friendly-name";
import { formatList } from "@/utils/stringUtil";
type CameraReviewSettingsViewProps = {
selectedCamera: string;
setUnsavedChanges: React.Dispatch<React.SetStateAction<boolean>>;
};
type CameraReviewSettingsValueType = {
alerts_zones: string[];
detections_zones: string[];
};
export default function CameraReviewSettingsView({
selectedCamera,
setUnsavedChanges,
}: CameraReviewSettingsViewProps) {
const { t } = useTranslation(["views/settings"]);
const { getLocaleDocUrl } = useDocDomain();
const { data: config, mutate: updateConfig } =
useSWR<FrigateConfig>("config");
const cameraConfig = useMemo(() => {
if (config && selectedCamera) {
return config.cameras[selectedCamera];
}
}, [config, selectedCamera]);
const [changedValue, setChangedValue] = useState(false);
const [isLoading, setIsLoading] = useState(false);
const [selectDetections, setSelectDetections] = useState(false);
const { addMessage, removeMessage } = useContext(StatusBarMessagesContext)!;
const selectCameraName = useCameraFriendlyName(selectedCamera);
// zones and labels
const getZoneName = useCallback(
(zoneId: string, cameraId?: string) =>
resolveZoneName(config, zoneId, cameraId),
[config],
);
const zones = useMemo(() => {
if (cameraConfig) {
return Object.entries(cameraConfig.zones).map(([name, zoneData]) => ({
camera: cameraConfig.name,
name,
friendly_name: cameraConfig.zones[name].friendly_name,
objects: zoneData.objects,
color: zoneData.color,
}));
}
}, [cameraConfig]);
const alertsLabels = useMemo(() => {
return cameraConfig?.review.alerts.labels
? formatList(
cameraConfig.review.alerts.labels.map((label) =>
getTranslatedLabel(
label,
cameraConfig?.audio?.listen?.includes(label) ? "audio" : "object",
),
),
)
: "";
}, [cameraConfig]);
const detectionsLabels = useMemo(() => {
return cameraConfig?.review.detections.labels
? formatList(
cameraConfig.review.detections.labels.map((label) =>
getTranslatedLabel(
label,
cameraConfig?.audio?.listen?.includes(label) ? "audio" : "object",
),
),
)
: "";
}, [cameraConfig]);
// form
const formSchema = z.object({
alerts_zones: z.array(z.string()),
detections_zones: z.array(z.string()),
});
const form = useForm<z.infer<typeof formSchema>>({
resolver: zodResolver(formSchema),
mode: "onChange",
defaultValues: {
alerts_zones: cameraConfig?.review.alerts.required_zones || [],
detections_zones: cameraConfig?.review.detections.required_zones || [],
},
});
const watchedAlertsZones = form.watch("alerts_zones");
const watchedDetectionsZones = form.watch("detections_zones");
const { payload: alertsState, send: sendAlerts } =
useAlertsState(selectedCamera);
const { payload: detectionsState, send: sendDetections } =
useDetectionsState(selectedCamera);
const { payload: objDescState, send: sendObjDesc } =
useObjectDescriptionState(selectedCamera);
const { payload: revDescState, send: sendRevDesc } =
useReviewDescriptionState(selectedCamera);
const handleCheckedChange = useCallback(
(isChecked: boolean) => {
if (!isChecked) {
form.reset({
alerts_zones: watchedAlertsZones,
detections_zones: [],
});
}
setChangedValue(true);
setSelectDetections(isChecked as boolean);
},
// we know that these deps are correct
// eslint-disable-next-line react-hooks/exhaustive-deps
[watchedAlertsZones],
);
const saveToConfig = useCallback(
async (
{ alerts_zones, detections_zones }: CameraReviewSettingsValueType, // values submitted via the form
) => {
const createQuery = (zones: string[], type: "alerts" | "detections") =>
zones.length
? zones
.map(
(zone) =>
`&cameras.${selectedCamera}.review.${type}.required_zones=${zone}`,
)
.join("")
: cameraConfig?.review[type]?.required_zones &&
cameraConfig?.review[type]?.required_zones.length > 0
? `&cameras.${selectedCamera}.review.${type}.required_zones`
: "";
const alertQueries = createQuery(alerts_zones, "alerts");
const detectionQueries = createQuery(detections_zones, "detections");
axios
.put(`config/set?${alertQueries}${detectionQueries}`, {
requires_restart: 0,
})
.then((res) => {
if (res.status === 200) {
toast.success(
t("cameraReview.reviewClassification.toast.success"),
{
position: "top-center",
},
);
updateConfig();
} else {
toast.error(
t("toast.save.error.title", {
errorMessage: res.statusText,
ns: "common",
}),
{
position: "top-center",
},
);
}
})
.catch((error) => {
const errorMessage =
error.response?.data?.message ||
error.response?.data?.detail ||
"Unknown error";
toast.error(
t("toast.save.error.title", {
errorMessage,
ns: "common",
}),
{
position: "top-center",
},
);
})
.finally(() => {
setIsLoading(false);
});
},
[updateConfig, setIsLoading, selectedCamera, cameraConfig, t],
);
const onCancel = useCallback(() => {
if (!cameraConfig) {
return;
}
setChangedValue(false);
setUnsavedChanges(false);
removeMessage(
"camera_settings",
`review_classification_settings_${selectedCamera}`,
);
form.reset({
alerts_zones: cameraConfig?.review.alerts.required_zones ?? [],
detections_zones: cameraConfig?.review.detections.required_zones || [],
});
setSelectDetections(
!!cameraConfig?.review.detections.required_zones?.length,
);
// we know that these deps are correct
// eslint-disable-next-line react-hooks/exhaustive-deps
}, [removeMessage, selectedCamera, setUnsavedChanges, cameraConfig]);
useEffect(() => {
onCancel();
// we know that these deps are correct
// eslint-disable-next-line react-hooks/exhaustive-deps
}, [selectedCamera]);
useEffect(() => {
if (changedValue) {
addMessage(
"camera_settings",
t("cameraReview.reviewClassification.unsavedChanges", {
camera: selectedCamera,
}),
undefined,
`review_classification_settings_${selectedCamera}`,
);
} else {
removeMessage(
"camera_settings",
`review_classification_settings_${selectedCamera}`,
);
}
// we know that these deps are correct
// eslint-disable-next-line react-hooks/exhaustive-deps
}, [changedValue, selectedCamera]);
function onSubmit(values: z.infer<typeof formSchema>) {
setIsLoading(true);
saveToConfig(values as CameraReviewSettingsValueType);
}
useEffect(() => {
document.title = t("documentTitle.cameraReview");
}, [t]);
if (!cameraConfig && !selectedCamera) {
return <ActivityIndicator />;
}
return (
<>
<div className="flex size-full flex-col md:flex-row">
<Toaster position="top-center" closeButton={true} />
<div className="scrollbar-container order-last mb-10 mt-2 flex h-full w-full flex-col overflow-y-auto pb-2 md:order-none">
<Heading as="h4" className="mb-2">
{t("cameraReview.title")}
</Heading>
<Heading as="h4" className="my-2">
<Trans ns="views/settings">cameraReview.review.title</Trans>
</Heading>
<div className="mb-5 mt-2 flex max-w-5xl flex-col gap-2 space-y-3 text-sm text-primary-variant">
<div className="flex flex-row items-center">
<Switch
id="alerts-enabled"
className="mr-3"
checked={alertsState == "ON"}
onCheckedChange={(isChecked) => {
sendAlerts(isChecked ? "ON" : "OFF");
}}
/>
<div className="space-y-0.5">
<Label htmlFor="alerts-enabled">
<Trans ns="views/settings">cameraReview.review.alerts</Trans>
</Label>
</div>
</div>
<div className="flex flex-col">
<div className="flex flex-row items-center">
<Switch
id="detections-enabled"
className="mr-3"
checked={detectionsState == "ON"}
onCheckedChange={(isChecked) => {
sendDetections(isChecked ? "ON" : "OFF");
}}
/>
<div className="space-y-0.5">
<Label htmlFor="detections-enabled">
<Trans ns="views/settings">camera.review.detections</Trans>
</Label>
</div>
</div>
<div className="mt-3 text-sm text-muted-foreground">
<Trans ns="views/settings">cameraReview.review.desc</Trans>
</div>
</div>
</div>
{cameraConfig?.objects?.genai?.enabled_in_config && (
<>
<Separator className="my-2 flex bg-secondary" />
<Heading as="h4" className="my-2">
<Trans ns="views/settings">
cameraReview.object_descriptions.title
</Trans>
</Heading>
<div className="mb-5 mt-2 flex max-w-5xl flex-col gap-2 space-y-3 text-sm text-primary-variant">
<div className="flex flex-row items-center">
<Switch
id="alerts-enabled"
className="mr-3"
checked={objDescState == "ON"}
onCheckedChange={(isChecked) => {
sendObjDesc(isChecked ? "ON" : "OFF");
}}
/>
<div className="space-y-0.5">
<Label htmlFor="genai-enabled">
<Trans>button.enabled</Trans>
</Label>
</div>
</div>
<div className="mt-3 text-sm text-muted-foreground">
<Trans ns="views/settings">
cameraReview.object_descriptions.desc
</Trans>
</div>
</div>
</>
)}
{cameraConfig?.review?.genai?.enabled_in_config && (
<>
<Separator className="my-2 flex bg-secondary" />
<Heading as="h4" className="my-2">
<Trans ns="views/settings">
cameraReview.review_descriptions.title
</Trans>
</Heading>
<div className="mb-5 mt-2 flex max-w-5xl flex-col gap-2 space-y-3 text-sm text-primary-variant">
<div className="flex flex-row items-center">
<Switch
id="alerts-enabled"
className="mr-3"
checked={revDescState == "ON"}
onCheckedChange={(isChecked) => {
sendRevDesc(isChecked ? "ON" : "OFF");
}}
/>
<div className="space-y-0.5">
<Label htmlFor="genai-enabled">
<Trans>button.enabled</Trans>
</Label>
</div>
</div>
<div className="mt-3 text-sm text-muted-foreground">
<Trans ns="views/settings">
cameraReview.review_descriptions.desc
</Trans>
</div>
</div>
</>
)}
<Separator className="my-2 flex bg-secondary" />
<Heading as="h4" className="my-2">
<Trans ns="views/settings">
cameraReview.reviewClassification.title
</Trans>
</Heading>
<div className="max-w-6xl">
<div className="mb-5 mt-2 flex max-w-5xl flex-col gap-2 text-sm text-primary-variant">
<p>
<Trans ns="views/settings">
cameraReview.reviewClassification.desc
</Trans>
</p>
<div className="flex items-center text-primary">
<Link
to={getLocaleDocUrl("configuration/review")}
target="_blank"
rel="noopener noreferrer"
className="inline"
>
{t("readTheDocumentation", { ns: "common" })}
<LuExternalLink className="ml-2 inline-flex size-3" />
</Link>
</div>
</div>
</div>
<Form {...form}>
<form
onSubmit={form.handleSubmit(onSubmit)}
className="mt-2 space-y-6"
>
<div
className={cn(
"w-full max-w-5xl space-y-0",
zones &&
zones?.length > 0 &&
"grid items-start gap-5 md:grid-cols-2",
)}
>
<FormField
control={form.control}
name="alerts_zones"
render={() => (
<FormItem>
{zones && zones?.length > 0 ? (
<>
<div className="mb-2">
<FormLabel className="flex flex-row items-center text-base">
<Trans ns="views/settings">
camera.review.alerts
</Trans>
<MdCircle className="ml-3 size-2 text-severity_alert" />
</FormLabel>
<FormDescription>
<Trans ns="views/settings">
cameraReview.reviewClassification.selectAlertsZones
</Trans>
</FormDescription>
</div>
<div className="max-w-md rounded-lg bg-secondary p-4 md:max-w-full">
{zones?.map((zone) => (
<FormField
key={zone.name}
control={form.control}
name="alerts_zones"
render={({ field }) => (
<FormItem
key={zone.name}
className="mb-3 flex flex-row items-center space-x-3 space-y-0 last:mb-0"
>
<FormControl>
<Checkbox
className="size-5 text-white accent-white data-[state=checked]:bg-selected data-[state=checked]:text-white"
checked={field.value?.includes(
zone.name,
)}
onCheckedChange={(checked) => {
setChangedValue(true);
return checked
? field.onChange([
...field.value,
zone.name,
])
: field.onChange(
field.value?.filter(
(value) =>
value !== zone.name,
),
);
}}
/>
</FormControl>
<FormLabel
className={cn(
"font-normal",
!zone.friendly_name &&
"smart-capitalize",
)}
>
{zone.friendly_name || zone.name}
</FormLabel>
</FormItem>
)}
/>
))}
</div>
</>
) : (
<div className="font-normal text-destructive">
<Trans ns="views/settings">
cameraReview.reviewClassification.noDefinedZones
</Trans>
</div>
)}
<FormMessage />
<div className="text-sm">
{watchedAlertsZones && watchedAlertsZones.length > 0
? t(
"cameraReview.reviewClassification.zoneObjectAlertsTips",
{
alertsLabels,
zone: formatList(
watchedAlertsZones.map((zone) =>
getZoneName(zone),
),
),
cameraName: selectCameraName,
},
)
: t(
"cameraReview.reviewClassification.objectAlertsTips",
{
alertsLabels,
cameraName: selectCameraName,
},
)}
</div>
</FormItem>
)}
/>
<FormField
control={form.control}
name="detections_zones"
render={() => (
<FormItem>
{zones && zones?.length > 0 && (
<>
<div className="mb-2">
<FormLabel className="flex flex-row items-center text-base">
<Trans ns="views/settings">
camera.review.detections
</Trans>
<MdCircle className="ml-3 size-2 text-severity_detection" />
</FormLabel>
{selectDetections && (
<FormDescription>
<Trans ns="views/settings">
cameraReview.reviewClassification.selectDetectionsZones
</Trans>
</FormDescription>
)}
</div>
{selectDetections && (
<div className="max-w-md rounded-lg bg-secondary p-4 md:max-w-full">
{zones?.map((zone) => (
<FormField
key={zone.name}
control={form.control}
name="detections_zones"
render={({ field }) => (
<FormItem
key={zone.name}
className="mb-3 flex flex-row items-center space-x-3 space-y-0 last:mb-0"
>
<FormControl>
<Checkbox
className="size-5 text-white accent-white data-[state=checked]:bg-selected data-[state=checked]:text-white"
checked={field.value?.includes(
zone.name,
)}
onCheckedChange={(checked) => {
return checked
? field.onChange([
...field.value,
zone.name,
])
: field.onChange(
field.value?.filter(
(value) =>
value !== zone.name,
),
);
}}
/>
</FormControl>
<FormLabel
className={cn(
"font-normal",
!zone.friendly_name &&
"smart-capitalize",
)}
>
{zone.friendly_name || zone.name}
</FormLabel>
</FormItem>
)}
/>
))}
</div>
)}
<FormMessage />
<div className="mb-0 flex flex-row items-center gap-2">
<Checkbox
id="select-detections"
className="size-5 text-white accent-white data-[state=checked]:bg-selected data-[state=checked]:text-white"
checked={selectDetections}
onCheckedChange={handleCheckedChange}
/>
<div className="grid gap-1.5 leading-none">
<label
htmlFor="select-detections"
className="text-sm font-medium leading-none peer-disabled:cursor-not-allowed peer-disabled:opacity-70"
>
<Trans ns="views/settings">
cameraReview.reviewClassification.limitDetections
</Trans>
</label>
</div>
</div>
</>
)}
<div className="text-sm">
{watchedDetectionsZones &&
watchedDetectionsZones.length > 0 ? (
!selectDetections ? (
<Trans
i18nKey="cameraReview.reviewClassification.zoneObjectDetectionsTips.text"
values={{
detectionsLabels,
zone: formatList(
watchedDetectionsZones.map((zone) =>
getZoneName(zone),
),
),
cameraName: selectCameraName,
}}
ns="views/settings"
/>
) : (
<Trans
i18nKey="cameraReview.reviewClassification.zoneObjectDetectionsTips.notSelectDetections"
values={{
detectionsLabels,
zone: formatList(
watchedDetectionsZones.map((zone) =>
getZoneName(zone),
),
),
cameraName: selectCameraName,
}}
ns="views/settings"
/>
)
) : (
<Trans
i18nKey="cameraReview.reviewClassification.objectDetectionsTips"
values={{
detectionsLabels,
cameraName: selectCameraName,
}}
ns="views/settings"
/>
)}
</div>
</FormItem>
)}
/>
</div>
<Separator className="my-2 flex bg-secondary" />
<div className="flex w-full flex-row items-center gap-2 pt-2 md:w-[25%]">
<Button
className="flex flex-1"
aria-label={t("button.reset", { ns: "common" })}
onClick={onCancel}
type="button"
>
<Trans>button.reset</Trans>
</Button>
<Button
variant="select"
disabled={isLoading}
className="flex flex-1"
aria-label={t("button.save", { ns: "common" })}
type="submit"
>
{isLoading ? (
<div className="flex flex-row items-center gap-2">
<ActivityIndicator />
<span>
<Trans>button.saving</Trans>
</span>
</div>
) : (
<Trans>button.save</Trans>
)}
</Button>
</div>
</form>
</Form>
</div>
</div>
</>
);
}

View File

@ -0,0 +1,794 @@
import Heading from "@/components/ui/heading";
import { useCallback, useContext, useEffect, useMemo, useState } from "react";
import { Toaster, toast } from "sonner";
import {
Form,
FormControl,
FormDescription,
FormField,
FormItem,
FormLabel,
FormMessage,
} from "@/components/ui/form";
import { zodResolver } from "@hookform/resolvers/zod";
import { useForm } from "react-hook-form";
import { z } from "zod";
import { Separator } from "@/components/ui/separator";
import { Button } from "@/components/ui/button";
import useSWR from "swr";
import { FrigateConfig } from "@/types/frigateConfig";
import { Checkbox } from "@/components/ui/checkbox";
import ActivityIndicator from "@/components/indicators/activity-indicator";
import { StatusBarMessagesContext } from "@/context/statusbar-provider";
import axios from "axios";
import { Link } from "react-router-dom";
import { LuExternalLink } from "react-icons/lu";
import { MdCircle } from "react-icons/md";
import { cn } from "@/lib/utils";
import { Trans, useTranslation } from "react-i18next";
import { Switch } from "@/components/ui/switch";
import { Label } from "@/components/ui/label";
import { useDocDomain } from "@/hooks/use-doc-domain";
import { getTranslatedLabel } from "@/utils/i18n";
import {
useAlertsState,
useDetectionsState,
useObjectDescriptionState,
useReviewDescriptionState,
} from "@/api/ws";
import CameraEditForm from "@/components/settings/CameraEditForm";
import CameraWizardDialog from "@/components/settings/CameraWizardDialog";
import { IoMdArrowRoundBack } from "react-icons/io";
import { isDesktop } from "react-device-detect";
import { useCameraFriendlyName } from "@/hooks/use-camera-friendly-name";
import { resolveZoneName } from "@/hooks/use-zone-friendly-name";
import { formatList } from "@/utils/stringUtil";
type CameraSettingsViewProps = {
selectedCamera: string;
setUnsavedChanges: React.Dispatch<React.SetStateAction<boolean>>;
};
type CameraReviewSettingsValueType = {
alerts_zones: string[];
detections_zones: string[];
};
export default function CameraSettingsView({
selectedCamera,
setUnsavedChanges,
}: CameraSettingsViewProps) {
const { t } = useTranslation(["views/settings"]);
const { getLocaleDocUrl } = useDocDomain();
const { data: config, mutate: updateConfig } =
useSWR<FrigateConfig>("config");
const cameraConfig = useMemo(() => {
if (config && selectedCamera) {
return config.cameras[selectedCamera];
}
}, [config, selectedCamera]);
const [changedValue, setChangedValue] = useState(false);
const [isLoading, setIsLoading] = useState(false);
const [selectDetections, setSelectDetections] = useState(false);
const [viewMode, setViewMode] = useState<"settings" | "add" | "edit">(
"settings",
); // Control view state
const [editCameraName, setEditCameraName] = useState<string | undefined>(
undefined,
); // Track camera being edited
const [showWizard, setShowWizard] = useState(false);
const { addMessage, removeMessage } = useContext(StatusBarMessagesContext)!;
const selectCameraName = useCameraFriendlyName(selectedCamera);
// zones and labels
const getZoneName = useCallback(
(zoneId: string, cameraId?: string) =>
resolveZoneName(config, zoneId, cameraId),
[config],
);
const zones = useMemo(() => {
if (cameraConfig) {
return Object.entries(cameraConfig.zones).map(([name, zoneData]) => ({
camera: cameraConfig.name,
name,
friendly_name: cameraConfig.zones[name].friendly_name,
objects: zoneData.objects,
color: zoneData.color,
}));
}
}, [cameraConfig]);
const alertsLabels = useMemo(() => {
return cameraConfig?.review.alerts.labels
? formatList(
cameraConfig.review.alerts.labels.map((label) =>
getTranslatedLabel(
label,
cameraConfig?.audio?.listen?.includes(label) ? "audio" : "object",
),
),
)
: "";
}, [cameraConfig]);
const detectionsLabels = useMemo(() => {
return cameraConfig?.review.detections.labels
? formatList(
cameraConfig.review.detections.labels.map((label) =>
getTranslatedLabel(
label,
cameraConfig?.audio?.listen?.includes(label) ? "audio" : "object",
),
),
)
: "";
}, [cameraConfig]);
// form
const formSchema = z.object({
alerts_zones: z.array(z.string()),
detections_zones: z.array(z.string()),
});
const form = useForm<z.infer<typeof formSchema>>({
resolver: zodResolver(formSchema),
mode: "onChange",
defaultValues: {
alerts_zones: cameraConfig?.review.alerts.required_zones || [],
detections_zones: cameraConfig?.review.detections.required_zones || [],
},
});
const watchedAlertsZones = form.watch("alerts_zones");
const watchedDetectionsZones = form.watch("detections_zones");
const { payload: alertsState, send: sendAlerts } =
useAlertsState(selectedCamera);
const { payload: detectionsState, send: sendDetections } =
useDetectionsState(selectedCamera);
const { payload: objDescState, send: sendObjDesc } =
useObjectDescriptionState(selectedCamera);
const { payload: revDescState, send: sendRevDesc } =
useReviewDescriptionState(selectedCamera);
const handleCheckedChange = useCallback(
(isChecked: boolean) => {
if (!isChecked) {
form.reset({
alerts_zones: watchedAlertsZones,
detections_zones: [],
});
}
setChangedValue(true);
setSelectDetections(isChecked as boolean);
},
// we know that these deps are correct
// eslint-disable-next-line react-hooks/exhaustive-deps
[watchedAlertsZones],
);
const saveToConfig = useCallback(
async (
{ alerts_zones, detections_zones }: CameraReviewSettingsValueType, // values submitted via the form
) => {
const createQuery = (zones: string[], type: "alerts" | "detections") =>
zones.length
? zones
.map(
(zone) =>
`&cameras.${selectedCamera}.review.${type}.required_zones=${zone}`,
)
.join("")
: cameraConfig?.review[type]?.required_zones &&
cameraConfig?.review[type]?.required_zones.length > 0
? `&cameras.${selectedCamera}.review.${type}.required_zones`
: "";
const alertQueries = createQuery(alerts_zones, "alerts");
const detectionQueries = createQuery(detections_zones, "detections");
axios
.put(`config/set?${alertQueries}${detectionQueries}`, {
requires_restart: 0,
})
.then((res) => {
if (res.status === 200) {
toast.success(
t("cameraReview.reviewClassification.toast.success"),
{
position: "top-center",
},
);
updateConfig();
} else {
toast.error(
t("toast.save.error.title", {
errorMessage: res.statusText,
ns: "common",
}),
{
position: "top-center",
},
);
}
})
.catch((error) => {
const errorMessage =
error.response?.data?.message ||
error.response?.data?.detail ||
"Unknown error";
toast.error(
t("toast.save.error.title", {
errorMessage,
ns: "common",
}),
{
position: "top-center",
},
);
})
.finally(() => {
setIsLoading(false);
});
},
[updateConfig, setIsLoading, selectedCamera, cameraConfig, t],
);
const onCancel = useCallback(() => {
if (!cameraConfig) {
return;
}
setChangedValue(false);
setUnsavedChanges(false);
removeMessage(
"camera_settings",
`review_classification_settings_${selectedCamera}`,
);
form.reset({
alerts_zones: cameraConfig?.review.alerts.required_zones ?? [],
detections_zones: cameraConfig?.review.detections.required_zones || [],
});
setSelectDetections(
!!cameraConfig?.review.detections.required_zones?.length,
);
// we know that these deps are correct
// eslint-disable-next-line react-hooks/exhaustive-deps
}, [removeMessage, selectedCamera, setUnsavedChanges, cameraConfig]);
useEffect(() => {
onCancel();
// we know that these deps are correct
// eslint-disable-next-line react-hooks/exhaustive-deps
}, [selectedCamera]);
useEffect(() => {
if (changedValue) {
addMessage(
"camera_settings",
t("cameraReview.reviewClassification.unsavedChanges", {
camera: selectedCamera,
}),
undefined,
`review_classification_settings_${selectedCamera}`,
);
} else {
removeMessage(
"camera_settings",
`review_classification_settings_${selectedCamera}`,
);
}
// we know that these deps are correct
// eslint-disable-next-line react-hooks/exhaustive-deps
}, [changedValue, selectedCamera]);
function onSubmit(values: z.infer<typeof formSchema>) {
setIsLoading(true);
saveToConfig(values as CameraReviewSettingsValueType);
}
useEffect(() => {
document.title = t("documentTitle.cameraReview");
}, [t]);
// Handle back navigation from add/edit form
const handleBack = useCallback(() => {
setViewMode("settings");
setEditCameraName(undefined);
updateConfig();
}, [updateConfig]);
if (!cameraConfig && !selectedCamera && viewMode === "settings") {
return <ActivityIndicator />;
}
return (
<>
<div className="flex size-full flex-col md:flex-row">
<Toaster position="top-center" closeButton={true} />
<div className="scrollbar-container order-last mb-10 mt-2 flex h-full w-full flex-col overflow-y-auto pb-2 md:order-none">
{viewMode === "settings" ? (
<>
<Heading as="h4" className="mb-2">
{t("cameraReview.title")}
</Heading>
<Heading as="h4" className="my-2">
<Trans ns="views/settings">cameraReview.review.title</Trans>
</Heading>
<div className="mb-5 mt-2 flex max-w-5xl flex-col gap-2 space-y-3 text-sm text-primary-variant">
<div className="flex flex-row items-center">
<Switch
id="alerts-enabled"
className="mr-3"
checked={alertsState == "ON"}
onCheckedChange={(isChecked) => {
sendAlerts(isChecked ? "ON" : "OFF");
}}
/>
<div className="space-y-0.5">
<Label htmlFor="alerts-enabled">
<Trans ns="views/settings">
cameraReview.review.alerts
</Trans>
</Label>
</div>
</div>
<div className="flex flex-col">
<div className="flex flex-row items-center">
<Switch
id="detections-enabled"
className="mr-3"
checked={detectionsState == "ON"}
onCheckedChange={(isChecked) => {
sendDetections(isChecked ? "ON" : "OFF");
}}
/>
<div className="space-y-0.5">
<Label htmlFor="detections-enabled">
<Trans ns="views/settings">
camera.review.detections
</Trans>
</Label>
</div>
</div>
<div className="mt-3 text-sm text-muted-foreground">
<Trans ns="views/settings">cameraReview.review.desc</Trans>
</div>
</div>
</div>
{cameraConfig?.objects?.genai?.enabled_in_config && (
<>
<Separator className="my-2 flex bg-secondary" />
<Heading as="h4" className="my-2">
<Trans ns="views/settings">
cameraReview.object_descriptions.title
</Trans>
</Heading>
<div className="mb-5 mt-2 flex max-w-5xl flex-col gap-2 space-y-3 text-sm text-primary-variant">
<div className="flex flex-row items-center">
<Switch
id="alerts-enabled"
className="mr-3"
checked={objDescState == "ON"}
onCheckedChange={(isChecked) => {
sendObjDesc(isChecked ? "ON" : "OFF");
}}
/>
<div className="space-y-0.5">
<Label htmlFor="genai-enabled">
<Trans>button.enabled</Trans>
</Label>
</div>
</div>
<div className="mt-3 text-sm text-muted-foreground">
<Trans ns="views/settings">
cameraReview.object_descriptions.desc
</Trans>
</div>
</div>
</>
)}
{cameraConfig?.review?.genai?.enabled_in_config && (
<>
<Separator className="my-2 flex bg-secondary" />
<Heading as="h4" className="my-2">
<Trans ns="views/settings">
cameraReview.review_descriptions.title
</Trans>
</Heading>
<div className="mb-5 mt-2 flex max-w-5xl flex-col gap-2 space-y-3 text-sm text-primary-variant">
<div className="flex flex-row items-center">
<Switch
id="alerts-enabled"
className="mr-3"
checked={revDescState == "ON"}
onCheckedChange={(isChecked) => {
sendRevDesc(isChecked ? "ON" : "OFF");
}}
/>
<div className="space-y-0.5">
<Label htmlFor="genai-enabled">
<Trans>button.enabled</Trans>
</Label>
</div>
</div>
<div className="mt-3 text-sm text-muted-foreground">
<Trans ns="views/settings">
cameraReview.review_descriptions.desc
</Trans>
</div>
</div>
</>
)}
<Separator className="my-2 flex bg-secondary" />
<Heading as="h4" className="my-2">
<Trans ns="views/settings">
cameraReview.reviewClassification.title
</Trans>
</Heading>
<div className="max-w-6xl">
<div className="mb-5 mt-2 flex max-w-5xl flex-col gap-2 text-sm text-primary-variant">
<p>
<Trans ns="views/settings">
cameraReview.reviewClassification.desc
</Trans>
</p>
<div className="flex items-center text-primary">
<Link
to={getLocaleDocUrl("configuration/review")}
target="_blank"
rel="noopener noreferrer"
className="inline"
>
{t("readTheDocumentation", { ns: "common" })}
<LuExternalLink className="ml-2 inline-flex size-3" />
</Link>
</div>
</div>
</div>
<Form {...form}>
<form
onSubmit={form.handleSubmit(onSubmit)}
className="mt-2 space-y-6"
>
<div
className={cn(
"w-full max-w-5xl space-y-0",
zones &&
zones?.length > 0 &&
"grid items-start gap-5 md:grid-cols-2",
)}
>
<FormField
control={form.control}
name="alerts_zones"
render={() => (
<FormItem>
{zones && zones?.length > 0 ? (
<>
<div className="mb-2">
<FormLabel className="flex flex-row items-center text-base">
<Trans ns="views/settings">
camera.review.alerts
</Trans>
<MdCircle className="ml-3 size-2 text-severity_alert" />
</FormLabel>
<FormDescription>
<Trans ns="views/settings">
cameraReview.reviewClassification.selectAlertsZones
</Trans>
</FormDescription>
</div>
<div className="max-w-md rounded-lg bg-secondary p-4 md:max-w-full">
{zones?.map((zone) => (
<FormField
key={zone.name}
control={form.control}
name="alerts_zones"
render={({ field }) => (
<FormItem
key={zone.name}
className="mb-3 flex flex-row items-center space-x-3 space-y-0 last:mb-0"
>
<FormControl>
<Checkbox
className="size-5 text-white accent-white data-[state=checked]:bg-selected data-[state=checked]:text-white"
checked={field.value?.includes(
zone.name,
)}
onCheckedChange={(checked) => {
setChangedValue(true);
return checked
? field.onChange([
...field.value,
zone.name,
])
: field.onChange(
field.value?.filter(
(value) =>
value !== zone.name,
),
);
}}
/>
</FormControl>
<FormLabel
className={cn(
"font-normal",
!zone.friendly_name &&
"smart-capitalize",
)}
>
{zone.friendly_name || zone.name}
</FormLabel>
</FormItem>
)}
/>
))}
</div>
</>
) : (
<div className="font-normal text-destructive">
<Trans ns="views/settings">
cameraReview.reviewClassification.noDefinedZones
</Trans>
</div>
)}
<FormMessage />
<div className="text-sm">
{watchedAlertsZones && watchedAlertsZones.length > 0
? t(
"cameraReview.reviewClassification.zoneObjectAlertsTips",
{
alertsLabels,
zone: formatList(
watchedAlertsZones.map((zone) =>
getZoneName(zone),
),
),
cameraName: selectCameraName,
},
)
: t(
"cameraReview.reviewClassification.objectAlertsTips",
{
alertsLabels,
cameraName: selectCameraName,
},
)}
</div>
</FormItem>
)}
/>
<FormField
control={form.control}
name="detections_zones"
render={() => (
<FormItem>
{zones && zones?.length > 0 && (
<>
<div className="mb-2">
<FormLabel className="flex flex-row items-center text-base">
<Trans ns="views/settings">
camera.review.detections
</Trans>
<MdCircle className="ml-3 size-2 text-severity_detection" />
</FormLabel>
{selectDetections && (
<FormDescription>
<Trans ns="views/settings">
cameraReview.reviewClassification.selectDetectionsZones
</Trans>
</FormDescription>
)}
</div>
{selectDetections && (
<div className="max-w-md rounded-lg bg-secondary p-4 md:max-w-full">
{zones?.map((zone) => (
<FormField
key={zone.name}
control={form.control}
name="detections_zones"
render={({ field }) => (
<FormItem
key={zone.name}
className="mb-3 flex flex-row items-center space-x-3 space-y-0 last:mb-0"
>
<FormControl>
<Checkbox
className="size-5 text-white accent-white data-[state=checked]:bg-selected data-[state=checked]:text-white"
checked={field.value?.includes(
zone.name,
)}
onCheckedChange={(checked) => {
return checked
? field.onChange([
...field.value,
zone.name,
])
: field.onChange(
field.value?.filter(
(value) =>
value !== zone.name,
),
);
}}
/>
</FormControl>
<FormLabel
className={cn(
"font-normal",
!zone.friendly_name &&
"smart-capitalize",
)}
>
{zone.friendly_name || zone.name}
</FormLabel>
</FormItem>
)}
/>
))}
</div>
)}
<FormMessage />
<div className="mb-0 flex flex-row items-center gap-2">
<Checkbox
id="select-detections"
className="size-5 text-white accent-white data-[state=checked]:bg-selected data-[state=checked]:text-white"
checked={selectDetections}
onCheckedChange={handleCheckedChange}
/>
<div className="grid gap-1.5 leading-none">
<label
htmlFor="select-detections"
className="text-sm font-medium leading-none peer-disabled:cursor-not-allowed peer-disabled:opacity-70"
>
<Trans ns="views/settings">
cameraReview.reviewClassification.limitDetections
</Trans>
</label>
</div>
</div>
</>
)}
<div className="text-sm">
{watchedDetectionsZones &&
watchedDetectionsZones.length > 0 ? (
!selectDetections ? (
<Trans
i18nKey="cameraReview.reviewClassification.zoneObjectDetectionsTips.text"
values={{
detectionsLabels,
zone: formatList(
watchedDetectionsZones.map((zone) =>
getZoneName(zone),
),
),
cameraName: selectCameraName,
}}
ns="views/settings"
/>
) : (
<Trans
i18nKey="cameraReview.reviewClassification.zoneObjectDetectionsTips.notSelectDetections"
values={{
detectionsLabels,
zone: formatList(
watchedDetectionsZones.map((zone) =>
getZoneName(zone),
),
),
cameraName: selectCameraName,
}}
ns="views/settings"
/>
)
) : (
<Trans
i18nKey="cameraReview.reviewClassification.objectDetectionsTips"
values={{
detectionsLabels,
cameraName: selectCameraName,
}}
ns="views/settings"
/>
)}
</div>
</FormItem>
)}
/>
</div>
<Separator className="my-2 flex bg-secondary" />
<div className="flex w-full flex-row items-center gap-2 pt-2 md:w-[25%]">
<Button
className="flex flex-1"
aria-label={t("button.reset", { ns: "common" })}
onClick={onCancel}
type="button"
>
<Trans>button.reset</Trans>
</Button>
<Button
variant="select"
disabled={isLoading}
className="flex flex-1"
aria-label={t("button.save", { ns: "common" })}
type="submit"
>
{isLoading ? (
<div className="flex flex-row items-center gap-2">
<ActivityIndicator />
<span>
<Trans>button.saving</Trans>
</span>
</div>
) : (
<Trans>button.save</Trans>
)}
</Button>
</div>
</form>
</Form>
</>
) : (
<>
<div className="mb-4 flex items-center gap-2">
<Button
className={`flex items-center gap-2.5 rounded-lg`}
aria-label={t("label.back", { ns: "common" })}
size="sm"
onClick={handleBack}
>
<IoMdArrowRoundBack className="size-5 text-secondary-foreground" />
{isDesktop && (
<div className="text-primary">
{t("button.back", { ns: "common" })}
</div>
)}
</Button>
</div>
<div className="md:max-w-5xl">
<CameraEditForm
cameraName={viewMode === "edit" ? editCameraName : undefined}
onSave={handleBack}
onCancel={handleBack}
/>
</div>
</>
)}
</div>
</div>
<CameraWizardDialog
open={showWizard}
onClose={() => setShowWizard(false)}
/>
</>
);
}

View File

@ -198,20 +198,15 @@ export default function TriggerView({
return axios return axios
.put("config/set", configBody) .put("config/set", configBody)
.then(async (configResponse) => { .then((configResponse) => {
if (configResponse.status === 200) { if (configResponse.status === 200) {
await updateConfig(); updateConfig();
const displayName =
friendly_name && friendly_name !== ""
? `${friendly_name} (${name})`
: name;
toast.success( toast.success(
t( t(
isEdit isEdit
? "triggers.toast.success.updateTrigger" ? "triggers.toast.success.updateTrigger"
: "triggers.toast.success.createTrigger", : "triggers.toast.success.createTrigger",
{ name: displayName }, { name },
), ),
{ position: "top-center" }, { position: "top-center" },
); );
@ -353,22 +348,11 @@ export default function TriggerView({
return axios return axios
.put("config/set", configBody) .put("config/set", configBody)
.then(async (configResponse) => { .then((configResponse) => {
if (configResponse.status === 200) { if (configResponse.status === 200) {
await updateConfig(); updateConfig();
const friendly =
config?.cameras?.[selectedCamera]?.semantic_search
?.triggers?.[name]?.friendly_name;
const displayName =
friendly && friendly !== ""
? `${friendly} (${name})`
: name;
toast.success( toast.success(
t("triggers.toast.success.deleteTrigger", { t("triggers.toast.success.deleteTrigger", { name }),
name: displayName,
}),
{ {
position: "top-center", position: "top-center",
}, },
@ -397,7 +381,7 @@ export default function TriggerView({
setIsLoading(false); setIsLoading(false);
}); });
}, },
[t, updateConfig, selectedCamera, setUnsavedChanges, config], [t, updateConfig, selectedCamera, setUnsavedChanges],
); );
useEffect(() => { useEffect(() => {
@ -859,14 +843,7 @@ export default function TriggerView({
/> />
<DeleteTriggerDialog <DeleteTriggerDialog
show={showDelete} show={showDelete}
triggerName={ triggerName={selectedTrigger?.name ?? ""}
selectedTrigger
? selectedTrigger.friendly_name &&
selectedTrigger.friendly_name !== ""
? `${selectedTrigger.friendly_name} (${selectedTrigger.name})`
: selectedTrigger.name
: ""
}
isLoading={isLoading} isLoading={isLoading}
onCancel={() => { onCancel={() => {
setShowDelete(false); setShowDelete(false);

View File

@ -67,14 +67,13 @@ export default function EnrichmentMetrics({
// features stats // features stats
const groupedEnrichmentMetrics = useMemo(() => { const embeddingInferenceTimeSeries = useMemo(() => {
if (!statsHistory) { if (!statsHistory) {
return []; return [];
} }
const series: { const series: {
[key: string]: { [key: string]: {
rawKey: string;
name: string; name: string;
metrics: Threshold; metrics: Threshold;
data: { x: number; y: number }[]; data: { x: number; y: number }[];
@ -91,7 +90,6 @@ export default function EnrichmentMetrics({
if (!(key in series)) { if (!(key in series)) {
series[key] = { series[key] = {
rawKey,
name: t("enrichments.embeddings." + rawKey), name: t("enrichments.embeddings." + rawKey),
metrics: getThreshold(rawKey), metrics: getThreshold(rawKey),
data: [], data: [],
@ -101,57 +99,7 @@ export default function EnrichmentMetrics({
series[key].data.push({ x: statsIdx + 1, y: stat }); series[key].data.push({ x: statsIdx + 1, y: stat });
}); });
}); });
return Object.values(series);
// Group series by category (extract base name from raw key)
const grouped: {
[category: string]: {
categoryName: string;
speedSeries?: {
name: string;
metrics: Threshold;
data: { x: number; y: number }[];
};
eventsSeries?: {
name: string;
metrics: Threshold;
data: { x: number; y: number }[];
};
};
} = {};
Object.values(series).forEach((s) => {
// Extract base category name from raw key
// All metrics follow the pattern: {base}_speed and {base}_events_per_second
let categoryKey = s.rawKey;
let isSpeed = false;
if (s.rawKey.endsWith("_speed")) {
categoryKey = s.rawKey.replace("_speed", "");
isSpeed = true;
} else if (s.rawKey.endsWith("_events_per_second")) {
categoryKey = s.rawKey.replace("_events_per_second", "");
isSpeed = false;
}
// Get translated category name
const categoryName = t("enrichments.embeddings." + categoryKey);
if (!(categoryKey in grouped)) {
grouped[categoryKey] = {
categoryName,
speedSeries: undefined,
eventsSeries: undefined,
};
}
if (isSpeed) {
grouped[categoryKey].speedSeries = s;
} else {
grouped[categoryKey].eventsSeries = s;
}
});
return Object.values(grouped);
}, [statsHistory, t, getThreshold]); }, [statsHistory, t, getThreshold]);
return ( return (
@ -162,42 +110,35 @@ export default function EnrichmentMetrics({
</div> </div>
<div <div
className={cn( className={cn(
"mt-4 grid w-full grid-cols-1 gap-2 sm:grid-cols-2 md:grid-cols-4", "mt-4 grid w-full grid-cols-1 gap-2 sm:grid-cols-3",
embeddingInferenceTimeSeries && "sm:grid-cols-4",
)} )}
> >
{statsHistory.length != 0 ? ( {statsHistory.length != 0 ? (
<> <>
{groupedEnrichmentMetrics.map((group) => ( {embeddingInferenceTimeSeries.map((series) => (
<div <div className="rounded-lg bg-background_alt p-2.5 md:rounded-2xl">
key={group.categoryName} <div className="mb-5 smart-capitalize">{series.name}</div>
className="rounded-lg bg-background_alt p-2.5 md:rounded-2xl" {series.name.endsWith("Speed") ? (
> <ThresholdBarGraph
<div className="mb-5 smart-capitalize"> key={series.name}
{group.categoryName} graphId={`${series.name}-inference`}
</div> name={series.name}
<div className="space-y-4"> unit="ms"
{group.speedSeries && ( threshold={series.metrics}
<ThresholdBarGraph updateTimes={updateTimes}
key={`${group.categoryName}-speed`} data={[series]}
graphId={`${group.categoryName}-inference`} />
name={t("enrichments.averageInf")} ) : (
unit="ms" <EventsPerSecondsLineGraph
threshold={group.speedSeries.metrics} key={series.name}
updateTimes={updateTimes} graphId={`${series.name}-fps`}
data={[group.speedSeries]} unit=""
/> name={t("enrichments.infPerSecond")}
)} updateTimes={updateTimes}
{group.eventsSeries && ( data={[series]}
<EventsPerSecondsLineGraph />
key={`${group.categoryName}-events`} )}
graphId={`${group.categoryName}-fps`}
unit=""
name={t("enrichments.infPerSecond")}
updateTimes={updateTimes}
data={[group.eventsSeries]}
/>
)}
</div>
</div> </div>
))} ))}
</> </>

View File

@ -375,50 +375,6 @@ export default function GeneralMetrics({
return Object.keys(series).length > 0 ? Object.values(series) : undefined; return Object.keys(series).length > 0 ? Object.values(series) : undefined;
}, [statsHistory]); }, [statsHistory]);
// Check if Intel GPU has all 0% usage values (known bug)
const showIntelGpuWarning = useMemo(() => {
if (!statsHistory || statsHistory.length < 3) {
return false;
}
const gpuKeys = Object.keys(statsHistory[0]?.gpu_usages ?? {});
const hasIntelGpu = gpuKeys.some(
(key) => key === "intel-vaapi" || key === "intel-qsv",
);
if (!hasIntelGpu) {
return false;
}
// Check if all GPU usage values are 0% across all stats
let allZero = true;
let hasDataPoints = false;
for (const stats of statsHistory) {
if (!stats) {
continue;
}
Object.entries(stats.gpu_usages || {}).forEach(([key, gpuStats]) => {
if (key === "intel-vaapi" || key === "intel-qsv") {
if (gpuStats.gpu) {
hasDataPoints = true;
const gpuValue = parseFloat(gpuStats.gpu.slice(0, -1));
if (!isNaN(gpuValue) && gpuValue > 0) {
allZero = false;
}
}
}
});
if (!allZero) {
break;
}
}
return hasDataPoints && allZero;
}, [statsHistory]);
// npu stats // npu stats
const npuSeries = useMemo(() => { const npuSeries = useMemo(() => {
@ -683,46 +639,8 @@ export default function GeneralMetrics({
<> <>
{statsHistory.length != 0 ? ( {statsHistory.length != 0 ? (
<div className="rounded-lg bg-background_alt p-2.5 md:rounded-2xl"> <div className="rounded-lg bg-background_alt p-2.5 md:rounded-2xl">
<div className="mb-5 flex flex-row items-center justify-between"> <div className="mb-5">
{t("general.hardwareInfo.gpuUsage")} {t("general.hardwareInfo.gpuUsage")}
{showIntelGpuWarning && (
<Popover>
<PopoverTrigger asChild>
<button
className="flex flex-row items-center gap-1.5 text-yellow-600 focus:outline-none dark:text-yellow-500"
aria-label={t(
"general.hardwareInfo.intelGpuWarning.title",
)}
>
<CiCircleAlert
className="size-5"
aria-label={t(
"general.hardwareInfo.intelGpuWarning.title",
)}
/>
<span className="text-sm">
{t(
"general.hardwareInfo.intelGpuWarning.message",
)}
</span>
</button>
</PopoverTrigger>
<PopoverContent className="w-80">
<div className="space-y-2">
<div className="font-semibold">
{t(
"general.hardwareInfo.intelGpuWarning.title",
)}
</div>
<div>
{t(
"general.hardwareInfo.intelGpuWarning.description",
)}
</div>
</div>
</PopoverContent>
</Popover>
)}
</div> </div>
{gpuSeries.map((series) => ( {gpuSeries.map((series) => (
<ThresholdBarGraph <ThresholdBarGraph
@ -811,33 +729,34 @@ export default function GeneralMetrics({
) : ( ) : (
<Skeleton className="aspect-video w-full" /> <Skeleton className="aspect-video w-full" />
)} )}
{statsHistory[0]?.npu_usages && (
<>
{statsHistory.length != 0 ? (
<div className="rounded-lg bg-background_alt p-2.5 md:rounded-2xl">
<div className="mb-5">
{t("general.hardwareInfo.npuUsage")}
</div>
{npuSeries.map((series) => (
<ThresholdBarGraph
key={series.name}
graphId={`${series.name}-npu`}
name={series.name}
unit="%"
threshold={GPUUsageThreshold}
updateTimes={updateTimes}
data={[series]}
/>
))}
</div>
) : (
<Skeleton className="aspect-video w-full" />
)}
</>
)}
</> </>
)} )}
{statsHistory[0]?.npu_usages && (
<div
className={cn("mt-4 grid grid-cols-1 gap-2 sm:grid-cols-2")}
>
{statsHistory.length != 0 ? (
<div className="rounded-lg bg-background_alt p-2.5 md:rounded-2xl">
<div className="mb-5">
{t("general.hardwareInfo.npuUsage")}
</div>
{npuSeries.map((series) => (
<ThresholdBarGraph
key={series.name}
graphId={`${series.name}-npu`}
name={series.name}
unit="%"
threshold={GPUUsageThreshold}
updateTimes={updateTimes}
data={[series]}
/>
))}
</div>
) : (
<Skeleton className="aspect-video w-full" />
)}
</div>
)}
</div> </div>
</> </>
)} )}

View File

@ -72,7 +72,8 @@ export default function StorageMetrics({
const earliestDate = useMemo(() => { const earliestDate = useMemo(() => {
const keys = Object.keys(recordingsSummary || {}); const keys = Object.keys(recordingsSummary || {});
return keys.length return keys.length
? new TZDate(keys[0] + "T00:00:00", timezone).getTime() / 1000 ? new TZDate(keys[keys.length - 1] + "T00:00:00", timezone).getTime() /
1000
: null; : null;
}, [recordingsSummary, timezone]); }, [recordingsSummary, timezone]);