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Docs refactor (#22703)
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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
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@@ -3,6 +3,10 @@ id: face_recognition
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title: Face Recognition
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---
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import ConfigTabs from "@site/src/components/ConfigTabs";
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import TabItem from "@theme/TabItem";
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import NavPath from "@site/src/components/NavPath";
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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.
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## Model Requirements
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@@ -40,50 +44,101 @@ The `large` model is optimized for accuracy, an integrated or discrete GPU / NPU
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## Configuration
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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.
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Face recognition is disabled by default and must be enabled before it can be used. Face recognition is a global configuration setting.
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<ConfigTabs>
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<TabItem value="ui">
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Navigate to <NavPath path="Settings > Enrichments > Face recognition" />.
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- Set **Enable face recognition** to on
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</TabItem>
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<TabItem value="yaml">
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```yaml
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face_recognition:
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enabled: true
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```
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</TabItem>
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</ConfigTabs>
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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.
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## Advanced Configuration
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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`.
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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`.
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### Detection
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- `detection_threshold`: Face detection confidence score required before recognition runs:
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<ConfigTabs>
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<TabItem value="ui">
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Navigate to <NavPath path="Settings > Enrichments > Face recognition" />.
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- **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.
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- Default: `0.7`
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- 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.
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- `min_area`: Defines the minimum size (in pixels) a face must be before recognition runs.
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- Default: `500` pixels.
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- Depending on the resolution of your camera's `detect` stream, you can increase this value to ignore small or distant faces.
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- **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.
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- Default: `500` pixels
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</TabItem>
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<TabItem value="yaml">
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```yaml
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face_recognition:
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enabled: true
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detection_threshold: 0.7
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min_area: 500
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```
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</TabItem>
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</ConfigTabs>
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### Recognition
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- `model_size`: Which model size to use, options are `small` or `large`
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- `unknown_score`: Min score to mark a person as a potential match, matches at or below this will be marked as unknown.
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- Default: `0.8`.
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- `recognition_threshold`: Recognition confidence score required to add the face to the object as a sub label.
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- Default: `0.9`.
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- `min_faces`: Min face recognitions for the sub label to be applied to the person object.
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<ConfigTabs>
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<TabItem value="ui">
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Navigate to <NavPath path="Settings > Enrichments > Face recognition" />.
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- **Model size**: Which model size to use, options are `small` or `large`.
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- **Unknown score threshold**: Min score to mark a person as a potential match; matches at or below this will be marked as unknown.
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- Default: `0.8`
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- **Recognition threshold**: Recognition confidence score required to add the face to the object as a sub label.
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- Default: `0.9`
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- **Minimum faces**: Min face recognitions for the sub label to be applied to the person object.
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- Default: `1`
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- `save_attempts`: Number of images of recognized faces to save for training.
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- Default: `200`.
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- `blur_confidence_filter`: Enables a filter that calculates how blurry the face is and adjusts the confidence based on this.
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- Default: `True`.
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- `device`: Target a specific device to run the face recognition model on (multi-GPU installation).
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- Default: `None`.
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- Note: This setting is only applicable when using the `large` model. See [onnxruntime's provider options](https://onnxruntime.ai/docs/execution-providers/)
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- **Save attempts**: Number of images of recognized faces to save for training.
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- Default: `200`
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- **Blur confidence filter**: Enables a filter that calculates how blurry the face is and adjusts the confidence based on this.
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- Default: `True`
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- **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/).
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- Default: `None`
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</TabItem>
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<TabItem value="yaml">
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```yaml
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face_recognition:
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enabled: true
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model_size: small
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unknown_score: 0.8
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recognition_threshold: 0.9
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min_faces: 1
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save_attempts: 200
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blur_confidence_filter: true
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device: None
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```
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</TabItem>
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</ConfigTabs>
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## Usage
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Follow these steps to begin:
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1. **Enable face recognition** in your configuration file and restart Frigate.
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1. **Enable face recognition** in your configuration and restart Frigate.
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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.
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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.
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4. From the **Train** tab, you can **assign the face** to a new or existing person to improve recognition accuracy for the future.
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