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* add generation script

a script to read yaml code blocks from docs markdown files and generate corresponding "Frigate UI" tab instructions based on the json schema, i18n, section configs (hidden fields), and nav mappings

* first pass

* components

* add to gitignore

* second pass

* fix broken anchors

* fixes

* clean up tabs

* version bump

* tweaks

* remove role mapping config from ui
This commit is contained in:
Josh Hawkins
2026-03-30 10:36:45 -06:00
committed by GitHub
parent a5e3dfd107
commit 5a5d23b503
53 changed files with 5310 additions and 276 deletions
+76 -21
View File
@@ -3,6 +3,10 @@ id: face_recognition
title: Face Recognition
---
import ConfigTabs from "@site/src/components/ConfigTabs";
import TabItem from "@theme/TabItem";
import NavPath from "@site/src/components/NavPath";
Face recognition identifies known individuals by matching detected faces with previously learned facial data. When a known `person` is recognized, their name will be added as a `sub_label`. This information is included in the UI, filters, as well as in notifications.
## Model Requirements
@@ -40,50 +44,101 @@ The `large` model is optimized for accuracy, an integrated or discrete GPU / NPU
## Configuration
Face recognition is disabled by default, face recognition must be enabled in the UI or in your config file before it can be used. Face recognition is a global configuration setting.
Face recognition is disabled by default and must be enabled before it can be used. Face recognition is a global configuration setting.
<ConfigTabs>
<TabItem value="ui">
Navigate to <NavPath path="Settings > Enrichments > Face recognition" />.
- Set **Enable face recognition** to on
</TabItem>
<TabItem value="yaml">
```yaml
face_recognition:
enabled: true
```
</TabItem>
</ConfigTabs>
Like the other real-time processors in Frigate, face recognition runs on the camera stream defined by the `detect` role in your config. To ensure optimal performance, select a suitable resolution for this stream in your camera's firmware that fits your specific scene and requirements.
## Advanced Configuration
Fine-tune face recognition with these optional parameters at the global level of your config. The only optional parameters that can be set at the camera level are `enabled` and `min_area`.
Fine-tune face recognition with these optional parameters. The only optional parameters that can be set at the camera level are `enabled` and `min_area`.
### Detection
- `detection_threshold`: Face detection confidence score required before recognition runs:
<ConfigTabs>
<TabItem value="ui">
Navigate to <NavPath path="Settings > Enrichments > Face recognition" />.
- **Detection threshold**: Face detection confidence score required before recognition runs. This field only applies to the standalone face detection model; `min_score` should be used to filter for models that have face detection built in.
- Default: `0.7`
- Note: This is field only applies to the standalone face detection model, `min_score` should be used to filter for models that have face detection built in.
- `min_area`: Defines the minimum size (in pixels) a face must be before recognition runs.
- Default: `500` pixels.
- Depending on the resolution of your camera's `detect` stream, you can increase this value to ignore small or distant faces.
- **Minimum face area**: Minimum size (in pixels) a face must be before recognition runs. Depending on the resolution of your camera's `detect` stream, you can increase this value to ignore small or distant faces.
- Default: `500` pixels
</TabItem>
<TabItem value="yaml">
```yaml
face_recognition:
enabled: true
detection_threshold: 0.7
min_area: 500
```
</TabItem>
</ConfigTabs>
### Recognition
- `model_size`: Which model size to use, options are `small` or `large`
- `unknown_score`: Min score to mark a person as a potential match, matches at or below this will be marked as unknown.
- Default: `0.8`.
- `recognition_threshold`: Recognition confidence score required to add the face to the object as a sub label.
- Default: `0.9`.
- `min_faces`: Min face recognitions for the sub label to be applied to the person object.
<ConfigTabs>
<TabItem value="ui">
Navigate to <NavPath path="Settings > Enrichments > Face recognition" />.
- **Model size**: Which model size to use, options are `small` or `large`.
- **Unknown score threshold**: Min score to mark a person as a potential match; matches at or below this will be marked as unknown.
- Default: `0.8`
- **Recognition threshold**: Recognition confidence score required to add the face to the object as a sub label.
- Default: `0.9`
- **Minimum faces**: Min face recognitions for the sub label to be applied to the person object.
- Default: `1`
- `save_attempts`: Number of images of recognized faces to save for training.
- Default: `200`.
- `blur_confidence_filter`: Enables a filter that calculates how blurry the face is and adjusts the confidence based on this.
- Default: `True`.
- `device`: Target a specific device to run the face recognition model on (multi-GPU installation).
- Default: `None`.
- Note: This setting is only applicable when using the `large` model. See [onnxruntime's provider options](https://onnxruntime.ai/docs/execution-providers/)
- **Save attempts**: Number of images of recognized faces to save for training.
- Default: `200`
- **Blur confidence filter**: Enables a filter that calculates how blurry the face is and adjusts the confidence based on this.
- Default: `True`
- **Device**: Target a specific device to run the face recognition model on (multi-GPU installation). This setting is only applicable when using the `large` model. See [onnxruntime's provider options](https://onnxruntime.ai/docs/execution-providers/).
- Default: `None`
</TabItem>
<TabItem value="yaml">
```yaml
face_recognition:
enabled: true
model_size: small
unknown_score: 0.8
recognition_threshold: 0.9
min_faces: 1
save_attempts: 200
blur_confidence_filter: true
device: None
```
</TabItem>
</ConfigTabs>
## Usage
Follow these steps to begin:
1. **Enable face recognition** in your configuration file and restart Frigate.
1. **Enable face recognition** in your configuration and restart Frigate.
2. **Upload one face** using the **Add Face** button's wizard in the Face Library section of the Frigate UI. Read below for the best practices on expanding your training set.
3. When Frigate detects and attempts to recognize a face, it will appear in the **Train** tab of the Face Library, along with its associated recognition confidence.
4. From the **Train** tab, you can **assign the face** to a new or existing person to improve recognition accuracy for the future.