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frigate/docs/docs/configuration/objects.md
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---
id: objects
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title: Available Objects
---
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import ConfigTabs from "@site/src/components/ConfigTabs";
import TabItem from "@theme/TabItem";
import NavPath from "@site/src/components/NavPath";
import labels from "../../../labelmap.txt";
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Frigate includes the object labels listed below from the Google Coral test data.
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Please note:
- `car` is listed twice because `truck` has been renamed to `car` by default. These object types are frequently confused.
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- `person` is the only tracked object by default. To track additional objects, configure them in the objects settings.
<ul>
{labels.split("\n").map((label) => (
<li>{label.replace(/^\d+\s+/, "")}</li>
))}
</ul>
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## Configuring Tracked Objects
By default, Frigate only tracks `person`. To track additional object types, add them to the tracked objects list.
<ConfigTabs>
<TabItem value="ui">
1. Navigate to <NavPath path="Settings > Global configuration > Objects" />.
- Add the desired object types to the **Objects to track** list (e.g., `person`, `car`, `dog`)
To override the tracked objects list for a specific camera:
1. Navigate to <NavPath path="Settings > Camera configuration > Objects" />.
- Add the desired object types to the **Objects to track** list
</TabItem>
<TabItem value="yaml">
```yaml
objects:
track:
- person
- car
- dog
```
To override at the camera level:
```yaml
cameras:
front_door:
objects:
track:
- person
- car
```
</TabItem>
</ConfigTabs>
## Filtering Objects
Object filters help reduce false positives by constraining the size, shape, and confidence thresholds for each object type. Filters can be configured globally or per camera.
<ConfigTabs>
<TabItem value="ui">
Navigate to <NavPath path="Settings > Global configuration > Objects" />.
| Field | Description |
| --------------------------------------- | ------------------------------------------------------------------------ |
| **Object filters > Person > Min Area** | Minimum bounding box area in pixels (or decimal for percentage of frame) |
| **Object filters > Person > Max Area** | Maximum bounding box area in pixels (or decimal for percentage of frame) |
| **Object filters > Person > Min Ratio** | Minimum width/height ratio of the bounding box |
| **Object filters > Person > Max Ratio** | Maximum width/height ratio of the bounding box |
| **Object filters > Person > Min Score** | Minimum score for the object to initiate tracking |
| **Object filters > Person > Threshold** | Minimum computed score to be considered a true positive |
To override filters for a specific camera, navigate to <NavPath path="Settings > Camera configuration > Objects" />.
</TabItem>
<TabItem value="yaml">
```yaml
objects:
filters:
person:
min_area: 5000
max_area: 100000
min_ratio: 0.5
max_ratio: 2.0
min_score: 0.5
threshold: 0.7
```
To override at the camera level:
```yaml
cameras:
front_door:
objects:
filters:
person:
min_area: 5000
threshold: 0.7
```
</TabItem>
</ConfigTabs>
## Object Filter Masks
Object filter masks prevent specific object types from being detected in certain areas of the camera frame. These masks check the bottom center of the bounding box. A global mask applies to all object types, while per-object masks apply only to the specified type.
<ConfigTabs>
<TabItem value="ui">
Navigate to <NavPath path="Settings > Camera configuration > Masks / Zones" /> and select a camera. Use the mask editor to draw object filter masks directly on the camera feed. Global object masks and per-object masks can both be configured from this view.
</TabItem>
<TabItem value="yaml">
```yaml
objects:
# Global mask applied to all object types
mask:
mask1:
friendly_name: "Object filter mask area"
enabled: true
coordinates: "0.000,0.000,0.781,0.000,0.781,0.278,0.000,0.278"
# Per-object mask
filters:
person:
mask:
mask1:
friendly_name: "Person filter mask"
enabled: true
coordinates: "0.000,0.000,0.781,0.000,0.781,0.278,0.000,0.278"
```
</TabItem>
</ConfigTabs>
:::note
The global mask is combined with any object-specific mask. Both are checked based on the bottom center of the bounding box.
:::
## Custom Models
Models for both CPU and EdgeTPU (Coral) are bundled in the image. You can use your own models with volume mounts:
- CPU Model: `/cpu_model.tflite`
- EdgeTPU Model: `/edgetpu_model.tflite`
- Labels: `/labelmap.txt`
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You also need to update the [model config](advanced/system.md#model) if they differ from the defaults.