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Commits
| Author | SHA1 | Date | |
|---|---|---|---|
 Josh HawkinsandGitHub
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5f6043aa92 | ||
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Josh HawkinsandGitHub
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da4037eb52 | ||
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Martin WeineltandGitHub
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f3c09ae169 | ||
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Josh HawkinsandGitHub
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f6596ac7b0 |
@@ -339,7 +339,7 @@ detect:
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# especially when using separate streams for detect and record.
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# Use this setting to make the timeline bounding boxes more closely align
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# with the recording. The value can be positive or negative.
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# TIP: Imagine there is an tracked object clip with a person walking from left to right.
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# TIP: Imagine there is a tracked object clip with a person walking from left to right.
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# If the tracked object lifecycle bounding box is consistently to the left of the person
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# then the value should be decreased. Similarly, if a person is walking from
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# left to right and the bounding box is consistently ahead of the person
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@@ -72,10 +72,10 @@ Variables prefixed with `FRIGATE_` can be referenced in config fields that suppo
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|
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Navigate to <NavPath path="Settings > System > Environment variables" /> to add or edit environment variables.
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| Field | Description |
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| --------- | --------------------------------------------------------- |
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| **Key** | The environment variable name (e.g., `FRIGATE_MQTT_USER`) |
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| **Value** | The value for the variable |
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| Field | Description |
|
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| ----------------- | --------------------------------------------------------- |
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| **Variable name** | The environment variable name (e.g., `FRIGATE_MQTT_USER`) |
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| **Value** | The value for the variable |
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Variables defined here can be referenced elsewhere in your configuration using the `{FRIGATE_VARIABLE_NAME}` syntax.
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@@ -78,7 +78,7 @@ cameras:
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### Configuring Minimum Volume
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The audio detector uses volume levels in the same way that motion in a camera feed is used for object detection. This means that Frigate will not run audio detection unless the audio volume is above the configured level in order to reduce resource usage. Audio levels can vary widely between camera models so it is important to run tests to see what volume levels are. The [Debug view](/usage/live#the-single-camera-view) in the Frigate UI has an Audio tab for cameras that have the `audio` role assigned where a graph and the current levels are is displayed. The `min_volume` parameter should be set to the minimum the `RMS` level required to run audio detection.
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The audio detector uses volume levels in the same way that motion in a camera feed is used for object detection. This means that Frigate will not run audio detection unless the audio volume is above the configured level in order to reduce resource usage. Audio levels can vary widely between camera models so it is important to run tests to see what volume levels are. The [Debug view](/usage/live#the-single-camera-view) in the Frigate UI has an Audio tab for cameras that have the `audio` role assigned where a graph and the current levels are displayed. The `min_volume` parameter should be set to the minimum the `RMS` level required to run audio detection.
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:::tip
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@@ -6,6 +6,7 @@ title: Camera Autotracking
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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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import FaqItem from "@site/src/components/FaqItem";
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An ONVIF-capable, PTZ (pan-tilt-zoom) camera that supports relative movement within the field of view (FOV) can be configured to automatically track moving objects and keep them in the center of the frame.
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@@ -187,30 +188,96 @@ In security and surveillance, it's common to use "spotter" cameras in combinatio
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## Troubleshooting and FAQ
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### The autotracker loses track of my object. Why?
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### Camera Compatibility
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<FaqItem id="which-ptz-camera-should-i-use-for-autotracking" question="Which PTZ camera should I use for autotracking?">
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See the community-maintained list of [ONVIF PTZ camera recommendations](cameras.md#onvif-ptz-camera-recommendations) for cameras and brands reported to work (and not work) with autotracking. This is not an exhaustive list that is frequently updated, so other cameras not listed may also work well. Frigate's autotracking was developed with a Dahua SD1A404XB-GNR (now sold as the EmpireTech PTZ1A4M-4X-S2), and Dahua / EmpireTech PTZs are the most consistently reported as working well.
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When comparing models:
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- Verify ONVIF support first. See [Checking ONVIF camera support](#checking-onvif-camera-support) above.
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- Favor a camera with a fast PTZ motor. Cameras with slow motors may fail [calibration](#calibration) and will struggle to keep up with objects that move across the field of view quickly.
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|
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</FaqItem>
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<FaqItem id="does-autotracking-work-with-reolink-ptz-cameras" question="Does autotracking work with Reolink PTZ cameras?">
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|
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No. Reolink cameras (including the TrackMix series) lack the ONVIF FOV RelativeMove firmware support that Frigate's autotracker requires, so autotracking will not work with any current Reolink PTZ. Their video streams and basic PTZ controls still work in Frigate. If you want object tracking on a Reolink PTZ, you will need to use the tracking feature built into the camera's firmware, which is proprietary and operates independently of Frigate.
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|
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</FaqItem>
|
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<FaqItem id="im-seeing-an-error-in-the-logs-that-my-camera-is-still-in-onvif-moving-status-what-does-this-mean" question={"I'm seeing an error in the logs that my camera \"is still in ONVIF 'MOVING' status.\" What does this mean?"}>
|
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|
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There are two possible known reasons for this (and perhaps others yet unknown): a slow PTZ motor or buggy camera firmware. Frigate uses an ONVIF parameter provided by the camera, `MoveStatus`, to determine when the PTZ's motor is moving or idle. According to some users, Hikvision PTZs (even with the latest firmware), are not updating this value after PTZ movement. Unfortunately there is no workaround to this bug in Hikvision firmware, so autotracking will not function correctly and should be disabled in your config. This may also be the case with other non-Hikvision cameras utilizing Hikvision firmware, such as some Annke models. In rare cases the vendor may provide fixed firmware on request; for example, Annke has supplied firmware that resolves this for the CZ504 (see the [camera recommendations list](cameras.md#onvif-ptz-camera-recommendations)).
|
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|
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</FaqItem>
|
||||
|
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<FaqItem id="calibration-seems-to-have-completed-but-the-camera-is-not-actually-moving-to-track-my-object-why" question="Calibration seems to have completed, but the camera is not actually moving to track my object. Why?">
|
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|
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Some cameras have firmware that reports that FOV RelativeMove, the ONVIF command that Frigate uses for autotracking, is supported. However, if the camera does not pan or tilt when an object comes into the required zone, your camera's firmware does not actually support FOV RelativeMove. One such camera is the Uniview IPC672LR-AX4DUPK. It actually moves its zoom motor instead of panning and tilting and does not follow the ONVIF standard whatsoever.
|
||||
|
||||
</FaqItem>
|
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|
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### Calibration Issues
|
||||
|
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<FaqItem id="i-tried-calibrating-my-camera-but-the-logs-show-that-it-is-stuck-at-0-and-frigate-is-not-starting-up" question="I tried calibrating my camera, but the logs show that it is stuck at 0% and Frigate is not starting up.">
|
||||
|
||||
This is often caused by the same reason as the "MOVING" status error above - the `MoveStatus` ONVIF parameter is not changing due to a bug in your camera's firmware. Also, see the note above: Frigate's web UI and all other cameras will be unresponsive while calibration is in progress. This is expected and normal. But if you don't see log entries every few seconds for calibration progress, your camera is not compatible with autotracking.
|
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|
||||
</FaqItem>
|
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|
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<FaqItem id="frigate-reports-an-error-saying-that-calibration-has-failed-why" question="Frigate reports an error saying that calibration has failed. Why?">
|
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|
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Calibration measures the amount of time it takes for Frigate to make a series of movements with your PTZ. This error message is recorded in the log if these values are too high for Frigate to support calibrated autotracking. This is often the case when your camera's motor or network connection is too slow or your camera's firmware doesn't report the motor status in a timely manner.
|
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|
||||
Some things to try:
|
||||
|
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- If your camera's firmware has a PTZ or motor speed setting, set it to the fastest available speed and calibrate again.
|
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- Run without calibration: remove the `movement_weights` line from your config, set `calibrate_on_startup` to `False`, and restart.
|
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|
||||
If calibration consistently fails, this often means your camera's motor is too slow and autotracking will behave unpredictably or won't be able to keep up with moving objects.
|
||||
|
||||
</FaqItem>
|
||||
|
||||
<FaqItem id="autotracking-is-erratic-or-moves-the-camera-in-the-wrong-direction" question="Autotracking is erratic, moves the camera in the wrong direction, or zooms past my object. Why?">
|
||||
|
||||
Frigate uses the `movement_weights` measured during calibration to predict how far the camera needs to move to keep an object centered, so inaccurate values produce movements that don't seem to make sense: overshooting, moving the opposite direction, or zooming in on an object's last known position and losing it entirely. This is almost always a calibration issue.
|
||||
|
||||
- Remove the `movement_weights` entry from your config and restart Frigate to run without calibration. If tracking improves, try recalibrating.
|
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- Recalibrate several times. The `movement_weights` values should be close to each other after each run. If they vary significantly between runs, your camera may not be reporting its motor status reliably, and you may get better results without calibration.
|
||||
- If you are using zooming, a high `zoom_factor` can cause the camera to zoom in too far and lose the object. Try a lower value.
|
||||
|
||||
Remember to recalibrate whenever you change your `return_preset`, change your camera's detect `fps`, or enable zooming after calibrating with it disabled.
|
||||
|
||||
</FaqItem>
|
||||
|
||||
### Tracking Behavior
|
||||
|
||||
<FaqItem id="the-autotracker-loses-track-of-my-object-why" question="The autotracker loses track of my object. Why?">
|
||||
|
||||
There are many reasons this could be the case. If you are using experimental zooming, your `zoom_factor` value might be too high, the object might be traveling too quickly, the scene might be too dark, there are not enough details in the scene (for example, a PTZ looking down on a driveway or other monotone background without a sufficient number of hard edges or corners), or the scene is otherwise less than optimal for Frigate to maintain tracking.
|
||||
|
||||
Your camera's shutter speed may also be set too low so that blurring occurs with motion. Check your camera's firmware to see if you can increase the shutter speed.
|
||||
|
||||
Watching Frigate's debug view can help to determine a possible cause. The autotracked object will have a thicker colored box around it.
|
||||
Watching Frigate's debug view can help to determine a possible cause. The autotracked object will have a thicker colored box around it. If the camera consistently zooms in on the object and then loses it, see [Autotracking is erratic, moves the camera in the wrong direction, or zooms past my object. Why?](#autotracking-is-erratic-or-moves-the-camera-in-the-wrong-direction) above.
|
||||
|
||||
### I'm seeing an error in the logs that my camera "is still in ONVIF 'MOVING' status." What does this mean?
|
||||
</FaqItem>
|
||||
|
||||
There are two possible known reasons for this (and perhaps others yet unknown): a slow PTZ motor or buggy camera firmware. Frigate uses an ONVIF parameter provided by the camera, `MoveStatus`, to determine when the PTZ's motor is moving or idle. According to some users, Hikvision PTZs (even with the latest firmware), are not updating this value after PTZ movement. Unfortunately there is no workaround to this bug in Hikvision firmware, so autotracking will not function correctly and should be disabled in your config. This may also be the case with other non-Hikvision cameras utilizing Hikvision firmware.
|
||||
|
||||
### I tried calibrating my camera, but the logs show that it is stuck at 0% and Frigate is not starting up.
|
||||
|
||||
This is often caused by the same reason as above - the `MoveStatus` ONVIF parameter is not changing due to a bug in your camera's firmware. Also, see the note above: Frigate's web UI and all other cameras will be unresponsive while calibration is in progress. This is expected and normal. But if you don't see log entries every few seconds for calibration progress, your camera is not compatible with autotracking.
|
||||
|
||||
### I'm seeing this error in the logs: "Autotracker: motion estimator couldn't get transformations". What does this mean?
|
||||
<FaqItem id="im-seeing-this-error-in-the-logs-autotracker-motion-estimator-couldnt-get-transformations-what-does-this-mean" question={"I'm seeing this error in the logs: \"Autotracker: motion estimator couldn't get transformations\". What does this mean?"}>
|
||||
|
||||
To maintain object tracking during PTZ moves, Frigate tracks the motion of your camera based on the details of the frame. If you are seeing this message, it could mean that your `zoom_factor` may be set too high, the scene around your detected object does not have enough details (like hard edges or color variations), or your camera's shutter speed is too slow and motion blur is occurring. Try reducing `zoom_factor`, finding a way to alter the scene around your object, or changing your camera's shutter speed.
|
||||
|
||||
### Calibration seems to have completed, but the camera is not actually moving to track my object. Why?
|
||||
</FaqItem>
|
||||
|
||||
Some cameras have firmware that reports that FOV RelativeMove, the ONVIF command that Frigate uses for autotracking, is supported. However, if the camera does not pan or tilt when an object comes into the required zone, your camera's firmware does not actually support FOV RelativeMove. One such camera is the Uniview IPC672LR-AX4DUPK. It actually moves its zoom motor instead of panning and tilting and does not follow the ONVIF standard whatsoever.
|
||||
<FaqItem id="why-does-object-detection-pause-briefly-when-the-camera-moves" question="Why does object detection pause briefly when the camera moves?">
|
||||
|
||||
### Frigate reports an error saying that calibration has failed. Why?
|
||||
When the PTZ moves, the entire frame changes at once. Frigate's motion detection treats sudden scene-wide changes (like a lightning flash, an infrared mode switch, or a camera move) specially and pauses detection momentarily until the scene stabilizes. This is expected and normal, and detection resumes shortly after the camera stops moving. If detection does not resume once the camera is stationary, use the [debug view](/usage/live#the-single-camera-view) to see what is happening.
|
||||
|
||||
Calibration measures the amount of time it takes for Frigate to make a series of movements with your PTZ. This error message is recorded in the log if these values are too high for Frigate to support calibrated autotracking. This is often the case when your camera's motor or network connection is too slow or your camera's firmware doesn't report the motor status in a timely manner. You can try running without calibration (just remove the `movement_weights` line from your config and restart), but if calibration fails, this often means that autotracking will behave unpredictably.
|
||||
</FaqItem>
|
||||
|
||||
<FaqItem id="can-i-turn-autotracking-on-and-off-automatically" question="Can I turn autotracking on and off automatically?">
|
||||
|
||||
Yes. Autotracking can be toggled per camera at runtime over MQTT with the [`frigate/<camera_name>/ptz_autotracker/set`](../integrations/mqtt.md#frigatecamera_nameptz_autotrackerset) topic, and the [Home Assistant integration](../integrations/home-assistant.md) exposes a switch for it. This pairs well with the "spotter" camera automations described in [Usage applications](#usage-applications) above, for example only enabling autotracking at night or when nobody is home.
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||||
|
||||
</FaqItem>
|
||||
|
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@@ -204,7 +204,7 @@ go2rtc:
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- "ffmpeg:http://reolink_ip/flv?port=1935&app=bcs&stream=channel0_main.bcs&user=username&password=password#video=copy#audio=copy#audio=opus"
|
||||
your_reolink_camera_sub:
|
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- "ffmpeg:http://reolink_ip/flv?port=1935&app=bcs&stream=channel0_ext.bcs&user=username&password=password"
|
||||
# example for connectin to a Reolink camera that supports two way talk
|
||||
# example for connecting to a Reolink camera that supports two way talk
|
||||
your_reolink_camera_twt:
|
||||
- "ffmpeg:http://reolink_ip/flv?port=1935&app=bcs&stream=channel0_main.bcs&user=username&password=password#video=copy#audio=copy#audio=opus"
|
||||
- "rtsp://username:password@reolink_ip/Preview_01_sub"
|
||||
@@ -249,7 +249,7 @@ cameras:
|
||||
|
||||
:::note
|
||||
|
||||
Unifi G5s cameras and newer need a Unifi Protect server to enable rtsps stream, it's not posible to enable it in standalone mode.
|
||||
Unifi G5s cameras and newer need a Unifi Protect server to enable rtsps stream, it's not possible to enable it in standalone mode.
|
||||
|
||||
:::
|
||||
|
||||
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@@ -262,7 +262,7 @@ Face recognition does not run on the recording stream, this would be suboptimal
|
||||
|
||||
<FaqItem id="detection-does-not-work-well-with-blurry-images" question="Detection does not work well with blurry images?">
|
||||
|
||||
Accuracy is definitely a going to be improved with higher quality cameras / streams. It is important to look at the DORI (Detection Observation Recognition Identification) range of your camera, if that specification is posted. This specification explains the distance from the camera that a person can be detected, observed, recognized, and identified. The identification range is the most relevant here, and the distance listed by the camera is the furthest that face recognition will realistically work.
|
||||
Accuracy is definitely going to be improved with higher quality cameras / streams. It is important to look at the DORI (Detection Observation Recognition Identification) range of your camera, if that specification is posted. This specification explains the distance from the camera that a person can be detected, observed, recognized, and identified. The identification range is the most relevant here, and the distance listed by the camera is the furthest that face recognition will realistically work.
|
||||
|
||||
Some users have also noted that setting the stream in camera firmware to a constant bit rate (CBR) leads to better image clarity than with a variable bit rate (VBR).
|
||||
|
||||
@@ -324,7 +324,7 @@ This also applies to a stranger who is repeatedly matched to a known person (for
|
||||
|
||||
<FaqItem id="i-see-scores-above-the-threshold-in-the-recent-recognitions-tab-but-a-sub-label-wasnt-assigned" question="I see scores above the threshold in the Recent Recognitions tab, but a sub label wasn't assigned?">
|
||||
|
||||
The Frigate considers the recognition scores across all recognition attempts for each person object. The scores are continually weighted based on the area of the face, and a sub label will only be assigned to person if a person is confidently recognized consistently. This avoids cases where a single high confidence recognition would throw off the results.
|
||||
Frigate considers the recognition scores across all recognition attempts for each person object. The scores are continually weighted based on the area of the face, and a sub label will only be assigned to person if a person is confidently recognized consistently. This avoids cases where a single high confidence recognition would throw off the results.
|
||||
|
||||
</FaqItem>
|
||||
|
||||
|
||||
@@ -67,4 +67,4 @@ If your stream won't play, has no audio, uses excessive CPU, or otherwise misbeh
|
||||
|
||||
## Homekit Configuration
|
||||
|
||||
To add camera streams to Homekit Frigate must be configured in docker to use `host` networking mode. Once that is done, you can use the go2rtc WebUI (accessed via port 1984, which is disabled by default) to share export a camera to Homekit. Any changes made will automatically be saved to `/config/go2rtc_homekit.yml`.
|
||||
To add camera streams to Homekit Frigate must be configured in docker to use `host` networking mode. Once that is done, you can use the go2rtc WebUI (accessed via port 1984, which is disabled by default) to export a camera to Homekit. Any changes made will automatically be saved to `/config/go2rtc_homekit.yml`.
|
||||
|
||||
@@ -477,7 +477,7 @@ Error marking filters as finished
|
||||
Restarting ffmpeg...
|
||||
```
|
||||
|
||||
you should try to uprade to FFmpeg 7. This can be done using this config option:
|
||||
you should try to upgrade to FFmpeg 7. This can be done using this config option:
|
||||
|
||||
```yaml
|
||||
ffmpeg:
|
||||
|
||||
@@ -66,7 +66,7 @@ motion:
|
||||
</TabItem>
|
||||
</ConfigTabs>
|
||||
|
||||
Lower values mean motion detection is more sensitive to changes in color, making it more likely for example to detect motion when a brown dogs blends in with a brown fence or a person wearing a red shirt blends in with a red car. If the threshold is too low however, it may detect things like grass blowing in the wind, shadows, etc. to be detected as motion.
|
||||
Lower values mean motion detection is more sensitive to changes in color, making it more likely for example to detect motion when a brown dog blends in with a brown fence or a person wearing a red shirt blends in with a red car. If the threshold is too low however, it may detect things like grass blowing in the wind, shadows, etc. to be detected as motion.
|
||||
|
||||
Watching the motion boxes in the debug view, increase the threshold until you only see motion that is visible to the eye. Once this is done, it is important to test and ensure that desired motion is still detected.
|
||||
|
||||
|
||||
@@ -725,7 +725,7 @@ The inference time was determined on a rk3588 with 3 NPU cores.
|
||||
|
||||
To convert a onnx model to the rknn format using the [rknn-toolkit2](https://github.com/airockchip/rknn-toolkit2/) you have to:
|
||||
|
||||
- Place one ore more models in onnx format in the directory `config/model_cache/rknn_cache/onnx` on your docker host (this might require `sudo` privileges).
|
||||
- Place one or more models in onnx format in the directory `config/model_cache/rknn_cache/onnx` on your docker host (this might require `sudo` privileges).
|
||||
- Save the configuration file under `config/conv2rknn.yaml` (see below for details).
|
||||
- Run `docker exec <frigate_container_id> python3 /opt/conv2rknn.py`. If the conversion was successful, the rknn models will be placed in `config/model_cache/rknn_cache`.
|
||||
|
||||
@@ -743,13 +743,13 @@ config:
|
||||
quant_img_RGB2BGR: true
|
||||
```
|
||||
|
||||
Explanation of the paramters:
|
||||
Explanation of the parameters:
|
||||
|
||||
- `soc`: A list of all SoCs you want to build the rknn model for. If you don't specify this parameter, the script tries to find out your SoC and builds the rknn model for this one.
|
||||
- `quantization`: true: 8 bit integer (i8) quantization, false: 16 bit float (fp16). Default: false.
|
||||
- `output_name`: The output name of the model. The following variables are available:
|
||||
- `quant`: "i8" or "fp16" depending on the config
|
||||
- `input_basename`: the basename of the input model (e.g. "my_model" if the input model is calles "my_model.onnx")
|
||||
- `input_basename`: the basename of the input model (e.g. "my_model" if the input model is called "my_model.onnx")
|
||||
- `soc`: the SoC this model was build for (e.g. "rk3588")
|
||||
- `tk_version`: Version of `rknn-toolkit2` (e.g. "2.3.0")
|
||||
- **example**: Specifying `output_name = "frigate-{quant}-{input_basename}-{soc}-v{tk_version}"` could result in a model called `frigate-i8-my_model-rk3588-v2.3.0.rknn`.
|
||||
|
||||
@@ -36,7 +36,7 @@ Any detection below `min_score` will be immediately thrown out and never tracked
|
||||
|
||||
### Threshold
|
||||
|
||||
`threshold` is used to determine that the object is a true positive. Once an object is detected with a score >= `threshold` object is considered a true positive. If `threshold` is too low then some higher scoring false positives may create an tracked object. If `threshold` is too high then true positive tracked objects may be missed due to the object never scoring high enough.
|
||||
`threshold` is used to determine that the object is a true positive. Once an object is detected with a score >= `threshold` object is considered a true positive. If `threshold` is too low then some higher scoring false positives may create a tracked object. If `threshold` is too high then true positive tracked objects may be missed due to the object never scoring high enough.
|
||||
|
||||
## Configuring Object Scores
|
||||
|
||||
|
||||
@@ -226,7 +226,7 @@ For tips on getting the best results from Semantic Search (choosing between thum
|
||||
|
||||
## Triggers
|
||||
|
||||
Triggers utilize Semantic Search to automate actions when a tracked object matches a specified image or description. Triggers can be configured so that Frigate executes a specific actions when a tracked object's image or description matches a predefined image or text, based on a similarity threshold. Triggers are managed per camera and can be configured via the Frigate UI in the Settings page under the Triggers tab.
|
||||
Triggers utilize Semantic Search to automate actions when a tracked object matches a specified image or description. Triggers can be configured so that Frigate executes specific actions when a tracked object's image or description matches a predefined image or text, based on a similarity threshold. Triggers are managed per camera and can be configured via the Frigate UI in the Settings page under the Triggers tab.
|
||||
|
||||
:::note
|
||||
|
||||
|
||||
@@ -43,7 +43,7 @@ Let's look at an example use case: I want to record any cars that enter my drive
|
||||
|
||||
One might simply think "Why not just run object detection any time there is motion around the driveway area and notify if the bounding box is in that zone?"
|
||||
|
||||
With that approach, what video is related to the car that entered the driveway? Did it come from the left or right? Was it parked across the street for an hour before turning into the driveway? One approach is to just record 24/7 or for motion (on any changed changed pixels) and not attempt to do that at all. This is what most other NVRs do. Just don't even try to identify a start and end for that object since it's hard and you will be wrong some portion of the time.
|
||||
With that approach, what video is related to the car that entered the driveway? Did it come from the left or right? Was it parked across the street for an hour before turning into the driveway? One approach is to just record 24/7 or for motion (on any changed pixels) and not attempt to do that at all. This is what most other NVRs do. Just don't even try to identify a start and end for that object since it's hard and you will be wrong some portion of the time.
|
||||
|
||||
Couldn't you just look at when motion stopped and started? Motion for a video feed is nothing more than looking for pixels that are different than they were in previous frames. If the car entered the driveway while someone was mowing the grass, how would you know which motion was for the car and which was for the person when they mow along the driveway or street? What if another car was driving the other direction on the street? Or what if its a windy day and the bush by your mailbox is blowing around?
|
||||
|
||||
@@ -61,4 +61,4 @@ Now you have to determine which of the bounding boxes in this frame should be ma
|
||||
|
||||
Now let's assume that those other 3 cars were already being tracked as stationary objects, so the car driving down the street is a new 4th car. The object tracker knows we have had 3 cars and we now have 4. As the new car approaches the parked cars, the bounding boxes for all 4 cars is predicted based on the previous frames. The predicted boxes for the parked cars is pretty much a 100% overlap with the bounding boxes in the new frame. The parked cars are slam dunk matches to the tracking ids they had before and the only one left is the remaining bounding box which gets assigned to the new car. This results in a much lower error rate. Not perfect, but better.
|
||||
|
||||
The most difficult scenario that causes IDs to be assigned incorrectly is when an object completely occludes another object. When a car drives in front of another car and its no longer visible, a bounding box disappeared and it's a bit of a toss up when assigning the id since it's difficult to know which one is in front of the other. This happens for cars passing in front of other cars fairly often. It's something that we want to improve in the future.
|
||||
The most difficult scenario that causes IDs to be assigned incorrectly is when an object completely occludes another object. When a car drives in front of another car and it's no longer visible, a bounding box disappeared and it's a bit of a toss up when assigning the id since it's difficult to know which one is in front of the other. This happens for cars passing in front of other cars fairly often. It's something that we want to improve in the future.
|
||||
|
||||
@@ -94,7 +94,7 @@ The following sections contain additional setup steps that are only required if
|
||||
|
||||
By default, the Raspberry Pi limits the amount of memory available to the GPU. In order to use ffmpeg hardware acceleration, you must increase the available memory by setting `gpu_mem` to the maximum recommended value in `config.txt` as described in the [official docs](https://www.raspberrypi.org/documentation/computers/config_txt.html#memory-options).
|
||||
|
||||
Additionally, the USB Coral draws a considerable amount of power. If using any other USB devices such as an SSD, you will experience instability due to the Pi not providing enough power to USB devices. You will need to purchase an external USB hub with it's own power supply. Some have reported success with <a href="https://amzn.to/3a2mH0P" target="_blank" rel="nofollow noopener sponsored">this</a> (affiliate link).
|
||||
Additionally, the USB Coral draws a considerable amount of power. If using any other USB devices such as an SSD, you will experience instability due to the Pi not providing enough power to USB devices. You will need to purchase an external USB hub with its own power supply. Some have reported success with <a href="https://amzn.to/3a2mH0P" target="_blank" rel="nofollow noopener sponsored">this</a> (affiliate link).
|
||||
|
||||
### Hailo-8
|
||||
|
||||
|
||||
@@ -122,7 +122,7 @@ Use `http://<frigate_device_ip>:8971` as the URL for the integration so that aut
|
||||
|
||||
The above URL assumes you have [disabled TLS](../configuration/tls).
|
||||
By default, TLS is enabled and Frigate will be using a self-signed certificate. HomeAssistant will fail to connect HTTPS to port 8971 since it fails to verify the self-signed certificate.
|
||||
Either disable TLS and use HTTP from HomeAssistant, or configure Frigate to be acessible with a valid certificate.
|
||||
Either disable TLS and use HTTP from HomeAssistant, or configure Frigate to be accessible with a valid certificate.
|
||||
|
||||
:::
|
||||
|
||||
|
||||
@@ -280,7 +280,7 @@ Same data available at `/api/stats` published at a configurable interval.
|
||||
|
||||
### `frigate/camera_activity`
|
||||
|
||||
Returns data about each camera, its current features, and if it is detecting motion, objects, etc. Can be triggered by publising to `frigate/onConnect`
|
||||
Returns data about each camera, its current features, and if it is detecting motion, objects, etc. Can be triggered by publishing to `frigate/onConnect`
|
||||
|
||||
### `frigate/profile/set`
|
||||
|
||||
|
||||
@@ -23,7 +23,7 @@ The [Advanced Camera Card](https://card.camera/#/README) is a Home Assistant das
|
||||
|
||||
## [Double Take](https://github.com/skrashevich/double-take)
|
||||
|
||||
[Double Take](https://github.com/skrashevich/double-take) provides an unified UI and API for processing and training images for facial recognition.
|
||||
[Double Take](https://github.com/skrashevich/double-take) provides a unified UI and API for processing and training images for facial recognition.
|
||||
It supports automatically setting the sub labels in Frigate for person objects that are detected and recognized.
|
||||
This is a fork (with fixed errors and new features) of [original Double Take](https://github.com/jakowenko/double-take) project which, unfortunately, isn't being maintained by author.
|
||||
|
||||
@@ -53,7 +53,7 @@ This is a fork (with fixed errors and new features) of [original Double Take](ht
|
||||
|
||||
## [Scrypted - Frigate bridge plugin](https://github.com/apocaliss92/scrypted-frigate-bridge)
|
||||
|
||||
[Scrypted - Frigate bridge](https://github.com/apocaliss92/scrypted-frigate-bridge) is an plugin that allows to ingest Frigate detections, motion, videoclips on Scrypted as well as provide templates to export rebroadcast configurations on Frigate.
|
||||
[Scrypted - Frigate bridge](https://github.com/apocaliss92/scrypted-frigate-bridge) is a plugin that allows you to ingest Frigate detections, motion, videoclips on Scrypted as well as provide templates to export rebroadcast configurations on Frigate.
|
||||
|
||||
## [Strix](https://github.com/eduard256/Strix)
|
||||
|
||||
|
||||
@@ -19,7 +19,7 @@ For the best results, follow these guidelines. You may also want to review the d
|
||||
|
||||
## AI suggested labels
|
||||
|
||||
If you have an active Frigate+ subscription, new uploads will be scanned for the objects configured for you camera and you will see suggested labels as light blue boxes when annotating in Frigate+. These suggestions are processed via a queue and typically complete within a minute after uploading, but processing times can be longer.
|
||||
If you have an active Frigate+ subscription, new uploads will be scanned for the objects configured for your camera and you will see suggested labels as light blue boxes when annotating in Frigate+. These suggestions are processed via a queue and typically complete within a minute after uploading, but processing times can be longer.
|
||||
|
||||
|
||||
|
||||
|
||||
@@ -12,7 +12,7 @@ There are many possible causes for a USB coral not being detected and some are O
|
||||
|
||||
:::tip
|
||||
|
||||
Using `lsusb` or checking the hardware page in HA OS will show as `1a6e:089a Global Unichip Corp.` until Frigate runs an inferance using the coral. So don't worry about the identification until after Frigate has attempted to detect the coral.
|
||||
Using `lsusb` or checking the hardware page in HA OS will show as `1a6e:089a Global Unichip Corp.` until Frigate runs an inference using the coral. So don't worry about the identification until after Frigate has attempted to detect the coral.
|
||||
|
||||
:::
|
||||
|
||||
@@ -43,13 +43,13 @@ Some users have reported that this older device runs an older kernel causing iss
|
||||
3. Start the docker container with Coral TPU enabled in the config
|
||||
4. The TPU would be detected but a few moments later it would disconnect.
|
||||
5. While leaving the TPU device plugged in, restart the NAS using the reboot command in the UI. Do NOT unplug the NAS/power it off etc.
|
||||
6. Open the control panel - info scree. The coral TPU will now be recognised as a USB Device - google inc
|
||||
6. Open the control panel - info screen. The coral TPU will now be recognized as a USB Device - google inc
|
||||
7. Start the frigate container. Everything should work now!
|
||||
|
||||
### QNAP NAS
|
||||
|
||||
QNAP NAS devices, such as the TS-253A, may use connected Coral TPU devices if [QuMagie](https://www.qnap.com/en/software/qumagie) is installed along with its QNAP AI Core extension. If any of the features (`facial recognition`, `object recognition`, or `similar photo recognition`) are enabled, Container Station applications such as `Frigate` or `CodeProject.AI Server` will be unable to initialize the TPU device in use.
|
||||
To allow the Coral TPU device to be discovered, the you must either:
|
||||
To allow the Coral TPU device to be discovered, you must either:
|
||||
|
||||
1. [Disable the AI recognition features in QuMagie](https://docs.qnap.com/application/qumagie/2.x/en-us/configuring-qnap-ai-core-settings-FB13CE03.html),
|
||||
2. Remove the QNAP AI Core extension or
|
||||
@@ -76,7 +76,7 @@ This is an issue due to outdated gasket driver when being used with new linux ke
|
||||
|
||||
### Not detected on Raspberry Pi5
|
||||
|
||||
A kernel update to the RPi5 means an upate to config.txt is required, see [the raspberry pi forum for more info](https://forums.raspberrypi.com/viewtopic.php?t=363682&sid=cb59b026a412f0dc041595951273a9ca&start=25)
|
||||
A kernel update to the RPi5 means an update to config.txt is required, see [the raspberry pi forum for more info](https://forums.raspberrypi.com/viewtopic.php?t=363682&sid=cb59b026a412f0dc041595951273a9ca&start=25)
|
||||
|
||||
Specifically, add the following to config.txt
|
||||
|
||||
@@ -87,7 +87,7 @@ dtoverlay=pcie-32bit-dma-pi5
|
||||
|
||||
## Only One PCIe Coral Is Detected With Coral Dual EdgeTPU
|
||||
|
||||
Coral Dual EdgeTPU is one card with two identical TPU cores. Each core has it's own PCIe interface and motherboard needs to have two PCIe busses on the m.2 slot to make them both work.
|
||||
Coral Dual EdgeTPU is one card with two identical TPU cores. Each core has its own PCIe interface and motherboard needs to have two PCIe busses on the m.2 slot to make them both work.
|
||||
|
||||
E-key slot implemented to full m.2 electromechanical specification has two PCIe busses. Most motherboard manufacturers implement only one PCIe bus in m.2 E-key connector (this is why only one TPU is working). Some SBCs can have only USB bus on m.2 connector, ie none of TPUs will work.
|
||||
|
||||
|
||||
@@ -29,7 +29,7 @@ You can open `chrome://media-internals/` in another tab and then try to playback
|
||||
|
||||
### What do I do if my cameras sub stream is not good enough?
|
||||
|
||||
Frigate generally [recommends cameras with configurable sub streams](/frigate/hardware.md). However, if your camera does not have a sub stream that a suitable resolution, the main stream can be resized.
|
||||
Frigate generally [recommends cameras with configurable sub streams](/frigate/hardware.md). However, if your camera does not have a sub stream that is a suitable resolution, the main stream can be resized.
|
||||
|
||||
To do this efficiently the following setup is required:
|
||||
|
||||
|
||||
@@ -91,7 +91,7 @@ To act on many objects at once, Ctrl/Cmd-click or right-click to start a selecti
|
||||
|
||||
1. Semantic Search is used in conjunction with the other filters available on the Explore page. Use a combination of traditional filtering and Semantic Search for the best results.
|
||||
2. Use the thumbnail search type when searching for particular objects in the scene. Use the description search type when attempting to discern the intent of your object.
|
||||
3. Because of how the AI models Frigate uses have been trained, the comparison between text and image embedding distances generally means that with multi-modal (`thumbnail` and `description`) searches, results matching `description` will appear first, even if a `thumbnail` embedding may be a better match. Play with the "Search Type" setting to help find what you are looking for. Note that if you are generating descriptions for specific objects or zones only, this may cause search results to prioritize the objects with descriptions even if the the ones without them are more relevant.
|
||||
3. Because of how the AI models Frigate uses have been trained, the comparison between text and image embedding distances generally means that with multi-modal (`thumbnail` and `description`) searches, results matching `description` will appear first, even if a `thumbnail` embedding may be a better match. Play with the "Search Type" setting to help find what you are looking for. Note that if you are generating descriptions for specific objects or zones only, this may cause search results to prioritize the objects with descriptions even if the ones without them are more relevant.
|
||||
4. Make your search language and tone closely match exactly what you're looking for. If you are using thumbnail search, **phrase your query as an image caption**. Searching for "red car" may not work as well as "red sedan driving down a residential street on a sunny day".
|
||||
5. Semantic search on thumbnails tends to return better results when matching large subjects that take up most of the frame. Small things like "cat" tend to not work well.
|
||||
6. Experiment! Find a tracked object you want to test and start typing keywords and phrases to see what works for you.
|
||||
|
||||
@@ -60,7 +60,7 @@ You can optionally overlay live streaming statistics (stream type, bandwidth, la
|
||||
|
||||
Right-clicking (or long-pressing) a camera tile opens a context menu with quick controls: an **audio volume** control for streams that support audio, **Mute / Unmute all cameras**, **show or hide streaming statistics**, the **debug view**, **notification** options, and, for admins, turning the camera on or off. If the audio control doesn't appear, see [Audio Support](/configuration/live#audio-support). Audio requires go2rtc configured with a compatible codec.
|
||||
|
||||
A **Low-bandwidth mode** notice may also appear in the context menu with a **Reset** option appears when Frigate has fallen back to the lower-quality jsmpeg stream. See the [Live view FAQ](/configuration/live#live-view-faq) for why this happens.
|
||||
A **Low-bandwidth mode** notice may also appear in the context menu with a **Reset** option when Frigate has fallen back to the lower-quality jsmpeg stream. See the [Live view FAQ](/configuration/live#live-view-faq) for why this happens.
|
||||
|
||||
For non-default groups, the context menu also exposes **Streaming Settings** for that camera, which let you choose:
|
||||
|
||||
|
||||
@@ -200,6 +200,9 @@ class EmbeddingMaintainer(threading.Thread):
|
||||
)
|
||||
|
||||
for model_config in self.config.classification.custom.values():
|
||||
if not model_config.enabled:
|
||||
continue
|
||||
|
||||
self.realtime_processors.append(
|
||||
CustomStateClassificationProcessor(
|
||||
self.config, model_config, self.requestor, self.metrics
|
||||
@@ -332,6 +335,25 @@ class EmbeddingMaintainer(threading.Thread):
|
||||
for processor in self.post_processors:
|
||||
processor.update_config(topic, payload)
|
||||
|
||||
def _remove_custom_classification_processor(self, model_name: str) -> None:
|
||||
"""Shut down and drop any running processor for a custom model."""
|
||||
remaining = []
|
||||
for processor in self.realtime_processors:
|
||||
if (
|
||||
isinstance(
|
||||
processor,
|
||||
(
|
||||
CustomStateClassificationProcessor,
|
||||
CustomObjectClassificationProcessor,
|
||||
),
|
||||
)
|
||||
and processor.model_config.name == model_name
|
||||
):
|
||||
processor.shutdown()
|
||||
else:
|
||||
remaining.append(processor)
|
||||
self.realtime_processors = remaining
|
||||
|
||||
def _handle_custom_classification_update(
|
||||
self, topic: str, model_config: Any
|
||||
) -> None:
|
||||
@@ -339,23 +361,7 @@ class EmbeddingMaintainer(threading.Thread):
|
||||
model_name = topic.split("/")[-1]
|
||||
|
||||
if model_config is None:
|
||||
remaining = []
|
||||
for processor in self.realtime_processors:
|
||||
if (
|
||||
isinstance(
|
||||
processor,
|
||||
(
|
||||
CustomStateClassificationProcessor,
|
||||
CustomObjectClassificationProcessor,
|
||||
),
|
||||
)
|
||||
and processor.model_config.name == model_name
|
||||
):
|
||||
processor.shutdown()
|
||||
else:
|
||||
remaining.append(processor)
|
||||
self.realtime_processors = remaining
|
||||
|
||||
self._remove_custom_classification_processor(model_name)
|
||||
logger.info(
|
||||
f"Successfully removed classification processor for model: {model_name}"
|
||||
)
|
||||
@@ -363,6 +369,13 @@ class EmbeddingMaintainer(threading.Thread):
|
||||
|
||||
self.config.classification.custom[model_name] = model_config
|
||||
|
||||
# A disabled model must not run; tear down any existing processor and
|
||||
# do not register a new one.
|
||||
if not model_config.enabled:
|
||||
self._remove_custom_classification_processor(model_name)
|
||||
logger.info(f"Disabled classification processor for model: {model_name}")
|
||||
return
|
||||
|
||||
# Check if processor already exists
|
||||
for processor in self.realtime_processors:
|
||||
if isinstance(
|
||||
@@ -702,7 +715,11 @@ class EmbeddingMaintainer(threading.Thread):
|
||||
and "license_plate" not in camera_config.objects.track
|
||||
)
|
||||
|
||||
if not dedicated_lpr_enabled and len(self.config.classification.custom) == 0:
|
||||
has_enabled_custom = any(
|
||||
c.enabled for c in self.config.classification.custom.values()
|
||||
)
|
||||
|
||||
if not dedicated_lpr_enabled and not has_enabled_custom:
|
||||
# no active features that use this data
|
||||
return
|
||||
|
||||
|
||||
@@ -0,0 +1,106 @@
|
||||
"""Tests that disabled custom classification models are not registered or run."""
|
||||
|
||||
import sys
|
||||
import unittest
|
||||
from unittest.mock import MagicMock
|
||||
|
||||
# Mock TFLite before importing the maintainer / classification modules
|
||||
_MOCK_MODULES = [
|
||||
"tflite_runtime",
|
||||
"tflite_runtime.interpreter",
|
||||
"ai_edge_litert",
|
||||
"ai_edge_litert.interpreter",
|
||||
]
|
||||
for mod in _MOCK_MODULES:
|
||||
if mod not in sys.modules:
|
||||
sys.modules[mod] = MagicMock()
|
||||
|
||||
from frigate.data_processing.real_time.custom_classification import ( # noqa: E402
|
||||
CustomObjectClassificationProcessor,
|
||||
)
|
||||
from frigate.embeddings.maintainer import EmbeddingMaintainer # noqa: E402
|
||||
|
||||
|
||||
class TestCustomClassificationEnabledGating(unittest.TestCase):
|
||||
"""A model with enabled: false must not keep a processor registered."""
|
||||
|
||||
def _make_maintainer(self) -> EmbeddingMaintainer:
|
||||
# Bypass the heavy __init__; only the attributes touched by the
|
||||
# config update path are needed for these tests.
|
||||
maintainer = EmbeddingMaintainer.__new__(EmbeddingMaintainer)
|
||||
maintainer.realtime_processors = []
|
||||
maintainer.config = MagicMock()
|
||||
maintainer.config.classification.custom = {}
|
||||
maintainer.requestor = MagicMock()
|
||||
maintainer.metrics = MagicMock()
|
||||
maintainer.event_metadata_publisher = MagicMock()
|
||||
return maintainer
|
||||
|
||||
def _make_model_config(self, name: str, enabled: bool) -> MagicMock:
|
||||
model_config = MagicMock()
|
||||
model_config.name = name
|
||||
model_config.enabled = enabled
|
||||
model_config.state_config = None
|
||||
return model_config
|
||||
|
||||
def _make_processor(self, name: str) -> MagicMock:
|
||||
processor = MagicMock(spec=CustomObjectClassificationProcessor)
|
||||
processor.model_config = MagicMock()
|
||||
processor.model_config.name = name
|
||||
return processor
|
||||
|
||||
def test_disabled_update_tears_down_existing_processor(self):
|
||||
"""Toggling a running model to disabled shuts down and drops its processor."""
|
||||
maintainer = self._make_maintainer()
|
||||
processor = self._make_processor("atli")
|
||||
maintainer.realtime_processors = [processor]
|
||||
|
||||
maintainer._handle_custom_classification_update(
|
||||
"config/classification/custom/atli",
|
||||
self._make_model_config("atli", enabled=False),
|
||||
)
|
||||
|
||||
processor.shutdown.assert_called_once()
|
||||
self.assertEqual(maintainer.realtime_processors, [])
|
||||
|
||||
def test_disabled_update_does_not_register_processor(self):
|
||||
"""A disabled model that has no processor is never registered."""
|
||||
maintainer = self._make_maintainer()
|
||||
|
||||
maintainer._handle_custom_classification_update(
|
||||
"config/classification/custom/atli",
|
||||
self._make_model_config("atli", enabled=False),
|
||||
)
|
||||
|
||||
self.assertEqual(maintainer.realtime_processors, [])
|
||||
|
||||
def test_disabled_update_leaves_other_processors_untouched(self):
|
||||
"""Disabling one model must not affect other running processors."""
|
||||
maintainer = self._make_maintainer()
|
||||
other = self._make_processor("simbi")
|
||||
maintainer.realtime_processors = [other]
|
||||
|
||||
maintainer._handle_custom_classification_update(
|
||||
"config/classification/custom/atli",
|
||||
self._make_model_config("atli", enabled=False),
|
||||
)
|
||||
|
||||
other.shutdown.assert_not_called()
|
||||
self.assertEqual(maintainer.realtime_processors, [other])
|
||||
|
||||
def test_removed_model_tears_down_processor(self):
|
||||
"""A None payload (model deleted) still shuts down its processor."""
|
||||
maintainer = self._make_maintainer()
|
||||
processor = self._make_processor("atli")
|
||||
maintainer.realtime_processors = [processor]
|
||||
|
||||
maintainer._handle_custom_classification_update(
|
||||
"config/classification/custom/atli", None
|
||||
)
|
||||
|
||||
processor.shutdown.assert_called_once()
|
||||
self.assertEqual(maintainer.realtime_processors, [])
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
unittest.main()
|
||||
@@ -123,7 +123,7 @@
|
||||
"error": {
|
||||
"failed": "Failed to queue export: {{error}}",
|
||||
"endTimeMustAfterStartTime": "End time must be after start time",
|
||||
"noVaildTimeSelected": "No valid time range selected"
|
||||
"noValidTimeSelected": "No valid time range selected"
|
||||
}
|
||||
},
|
||||
"fromTimeline": {
|
||||
|
||||
@@ -76,7 +76,7 @@
|
||||
},
|
||||
"offset": {
|
||||
"label": "Annotation Offset",
|
||||
"desc": "This data comes from your camera's detect feed but is overlayed on images from the the record feed. It is unlikely that the two streams are perfectly in sync. As a result, the bounding box and the footage will not line up perfectly. You can use this setting to offset the annotations forward or backward in time to better align them with the recorded footage.",
|
||||
"desc": "This data comes from your camera's detect feed but is overlaid on images from the record feed. It is unlikely that the two streams are perfectly in sync. As a result, the bounding box and the footage will not line up perfectly. You can use this setting to offset the annotations forward or backward in time to better align them with the recorded footage.",
|
||||
"millisecondsToOffset": "Milliseconds to offset detect annotations by. <em>Default: 0</em>",
|
||||
"tips": "Lower the value if the video playback is ahead of the boxes and path points, and increase the value if the video playback is behind them. This value can be negative.",
|
||||
"toast": {
|
||||
|
||||
@@ -1053,7 +1053,7 @@
|
||||
},
|
||||
"createUser": {
|
||||
"title": "Create New User",
|
||||
"desc": "Add a new user account and specify an role for access to areas of the Frigate UI.",
|
||||
"desc": "Add a new user account and specify a role for access to areas of the Frigate UI.",
|
||||
"usernameOnlyInclude": "Username may only include letters, numbers, . or _",
|
||||
"confirmPassword": "Please confirm your password"
|
||||
},
|
||||
@@ -1490,7 +1490,14 @@
|
||||
"keyLabel": "Key",
|
||||
"valueLabel": "Value",
|
||||
"keyPlaceholder": "New key",
|
||||
"remove": "Remove"
|
||||
"remove": "Remove",
|
||||
"providerNameLabel": "Provider name",
|
||||
"providerNamePlaceholder": "e.g., openai",
|
||||
"variableNameLabel": "Variable name",
|
||||
"variableNamePlaceholder": "e.g., MY_VARIABLE",
|
||||
"loggerNameLabel": "Logger name",
|
||||
"loggerNamePlaceholder": "e.g., frigate.record",
|
||||
"keyPatternError": "Use only letters, numbers, hyphens, and underscores (no spaces)"
|
||||
},
|
||||
"knownPlates": {
|
||||
"namePlaceholder": "e.g., Wife's Car",
|
||||
|
||||
@@ -7,7 +7,13 @@ const environmentVars: SectionConfigOverrides = {
|
||||
advancedFields: [],
|
||||
uiSchema: {
|
||||
additionalProperties: {
|
||||
"ui:options": { size: "lg" },
|
||||
"ui:options": {
|
||||
size: "lg",
|
||||
additionalPropertyKeyLabel:
|
||||
"configForm.additionalProperties.variableNameLabel",
|
||||
additionalPropertyKeyPlaceholder:
|
||||
"configForm.additionalProperties.variableNamePlaceholder",
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
|
||||
@@ -9,7 +9,15 @@ const genai: SectionConfigOverrides = {
|
||||
uiSchema: {
|
||||
"ui:options": { disableNestedCard: true },
|
||||
"*": {
|
||||
"ui:options": { disableNestedCard: true },
|
||||
"ui:options": {
|
||||
disableNestedCard: true,
|
||||
additionalPropertyKeyLabel:
|
||||
"configForm.additionalProperties.providerNameLabel",
|
||||
additionalPropertyKeyPlaceholder:
|
||||
"configForm.additionalProperties.providerNamePlaceholder",
|
||||
additionalPropertyKeyPattern: "^[a-zA-Z0-9_-]+$",
|
||||
preventKeyRename: true,
|
||||
},
|
||||
"ui:order": [
|
||||
"provider",
|
||||
"api_key",
|
||||
|
||||
@@ -12,7 +12,13 @@ const logger: SectionConfigOverrides = {
|
||||
},
|
||||
logs: {
|
||||
additionalProperties: {
|
||||
"ui:options": { enumI18nPrefix: "logger.logLevel" },
|
||||
"ui:options": {
|
||||
enumI18nPrefix: "logger.logLevel",
|
||||
additionalPropertyKeyLabel:
|
||||
"configForm.additionalProperties.loggerNameLabel",
|
||||
additionalPropertyKeyPlaceholder:
|
||||
"configForm.additionalProperties.loggerNamePlaceholder",
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
|
||||
@@ -6,12 +6,14 @@ import {
|
||||
StrictRJSFSchema,
|
||||
WrapIfAdditionalTemplateProps,
|
||||
} from "@rjsf/utils";
|
||||
import { useEffect, useMemo, useState, type FocusEvent } from "react";
|
||||
import { Input } from "@/components/ui/input";
|
||||
import { Button } from "@/components/ui/button";
|
||||
import { Label } from "@/components/ui/label";
|
||||
import { cn } from "@/lib/utils";
|
||||
import { useTranslation } from "react-i18next";
|
||||
import { LuTrash2 } from "react-icons/lu";
|
||||
import type { ConfigFormContext } from "@/types/configForm";
|
||||
|
||||
export function WrapIfAdditionalTemplate<
|
||||
T = unknown,
|
||||
@@ -30,6 +32,7 @@ export function WrapIfAdditionalTemplate<
|
||||
onKeyRenameBlur,
|
||||
readonly,
|
||||
required,
|
||||
registry,
|
||||
schema,
|
||||
uiSchema,
|
||||
} = props;
|
||||
@@ -38,6 +41,55 @@ export function WrapIfAdditionalTemplate<
|
||||
|
||||
const additional = ADDITIONAL_PROPERTY_FLAG in schema;
|
||||
|
||||
const uiOptions = getUiOptions(uiSchema);
|
||||
const keyIsReadonly = uiOptions.additionalPropertyKeyReadonly === true;
|
||||
|
||||
const keyLabelKey =
|
||||
typeof uiOptions.additionalPropertyKeyLabel === "string"
|
||||
? uiOptions.additionalPropertyKeyLabel
|
||||
: undefined;
|
||||
const keyPlaceholderKey =
|
||||
typeof uiOptions.additionalPropertyKeyPlaceholder === "string"
|
||||
? uiOptions.additionalPropertyKeyPlaceholder
|
||||
: undefined;
|
||||
const keyPattern =
|
||||
typeof uiOptions.additionalPropertyKeyPattern === "string"
|
||||
? uiOptions.additionalPropertyKeyPattern
|
||||
: undefined;
|
||||
const preventKeyRename = uiOptions.preventKeyRename === true;
|
||||
|
||||
const formContext = registry?.formContext as ConfigFormContext | undefined;
|
||||
|
||||
// optionally, lock the key once it's been saved
|
||||
const baseline = formContext?.baselineFormData;
|
||||
const keyLocked =
|
||||
preventKeyRename &&
|
||||
typeof label === "string" &&
|
||||
!!baseline &&
|
||||
Object.prototype.hasOwnProperty.call(baseline, label);
|
||||
|
||||
// controlled key value so we can validate live and block invalid renames.
|
||||
const [keyValue, setKeyValue] = useState<string>(label ?? "");
|
||||
useEffect(() => {
|
||||
setKeyValue(label ?? "");
|
||||
}, [label]);
|
||||
|
||||
const keyRegex = useMemo(
|
||||
() => (keyPattern ? new RegExp(keyPattern) : undefined),
|
||||
[keyPattern],
|
||||
);
|
||||
const keyError = useMemo(() => {
|
||||
if (!keyRegex || keyLocked) return null;
|
||||
if (!keyRegex.test(keyValue)) {
|
||||
return t("configForm.additionalProperties.keyPatternError", {
|
||||
ns: "views/settings",
|
||||
defaultValue:
|
||||
"Use only letters, numbers, hyphens, and underscores (no spaces)",
|
||||
});
|
||||
}
|
||||
return null;
|
||||
}, [keyRegex, keyLocked, keyValue, t]);
|
||||
|
||||
if (!additional) {
|
||||
return (
|
||||
<div className={classNames} style={style}>
|
||||
@@ -47,20 +99,26 @@ export function WrapIfAdditionalTemplate<
|
||||
}
|
||||
|
||||
const keyId = `${id}-key`;
|
||||
const keyLabel = t("configForm.additionalProperties.keyLabel", {
|
||||
ns: "views/settings",
|
||||
});
|
||||
const keyLabel = keyLabelKey
|
||||
? t(keyLabelKey, { ns: "views/settings" })
|
||||
: t("configForm.additionalProperties.keyLabel", { ns: "views/settings" });
|
||||
const valueLabel = t("configForm.additionalProperties.valueLabel", {
|
||||
ns: "views/settings",
|
||||
});
|
||||
const keyPlaceholder = t("configForm.additionalProperties.keyPlaceholder", {
|
||||
ns: "views/settings",
|
||||
});
|
||||
const keyPlaceholder = keyPlaceholderKey
|
||||
? t(keyPlaceholderKey, { ns: "views/settings" })
|
||||
: t("configForm.additionalProperties.keyPlaceholder", {
|
||||
ns: "views/settings",
|
||||
});
|
||||
const removeLabel = t("configForm.additionalProperties.remove", {
|
||||
ns: "views/settings",
|
||||
});
|
||||
const uiOptions = getUiOptions(uiSchema);
|
||||
const keyIsReadonly = uiOptions.additionalPropertyKeyReadonly === true;
|
||||
|
||||
const commitKeyRename = (e: FocusEvent<HTMLInputElement>) => {
|
||||
if (readonly) return;
|
||||
if (keyError) return;
|
||||
onKeyRenameBlur?.(e);
|
||||
};
|
||||
|
||||
return (
|
||||
<div
|
||||
@@ -70,23 +128,30 @@ export function WrapIfAdditionalTemplate<
|
||||
{!keyIsReadonly && (
|
||||
<div className="col-span-12 space-y-2 md:col-span-2">
|
||||
{displayLabel && <Label htmlFor={keyId}>{keyLabel}</Label>}
|
||||
{keyIsReadonly ? (
|
||||
{keyLocked ? (
|
||||
<div
|
||||
id={keyId}
|
||||
className="flex items-center text-sm text-muted-foreground"
|
||||
className="flex items-center break-all text-sm text-primary-variant"
|
||||
>
|
||||
{label}
|
||||
</div>
|
||||
) : (
|
||||
<Input
|
||||
id={keyId}
|
||||
name={keyId}
|
||||
required={required}
|
||||
defaultValue={label}
|
||||
placeholder={keyPlaceholder}
|
||||
disabled={disabled || readonly}
|
||||
onBlur={!readonly ? onKeyRenameBlur : undefined}
|
||||
/>
|
||||
<>
|
||||
<Input
|
||||
id={keyId}
|
||||
name={keyId}
|
||||
required={required}
|
||||
value={keyValue}
|
||||
placeholder={keyPlaceholder}
|
||||
disabled={disabled || readonly}
|
||||
onChange={(e) => setKeyValue(e.target.value)}
|
||||
onBlur={!readonly ? commitKeyRename : undefined}
|
||||
aria-invalid={keyError ? true : undefined}
|
||||
/>
|
||||
{keyError && (
|
||||
<p className="text-xs text-destructive">{keyError}</p>
|
||||
)}
|
||||
</>
|
||||
)}
|
||||
</div>
|
||||
)}
|
||||
|
||||
@@ -134,7 +134,7 @@ export default function ExportDialog({
|
||||
}
|
||||
|
||||
if (!range) {
|
||||
toast.error(t("export.toast.error.noVaildTimeSelected"), {
|
||||
toast.error(t("export.toast.error.noValidTimeSelected"), {
|
||||
position: "top-center",
|
||||
});
|
||||
return false;
|
||||
@@ -665,7 +665,7 @@ export function ExportContent({
|
||||
}
|
||||
|
||||
if (!range) {
|
||||
toast.error(t("export.toast.error.noVaildTimeSelected"), {
|
||||
toast.error(t("export.toast.error.noValidTimeSelected"), {
|
||||
position: "top-center",
|
||||
});
|
||||
return;
|
||||
|
||||
@@ -149,7 +149,7 @@ export default function MobileReviewSettingsDrawer({
|
||||
|
||||
if (!range) {
|
||||
toast.error(
|
||||
t("export.toast.error.noVaildTimeSelected", {
|
||||
t("export.toast.error.noValidTimeSelected", {
|
||||
ns: "components/dialog",
|
||||
}),
|
||||
{
|
||||
|
||||
@@ -305,7 +305,7 @@ export default function MotionSearchView({
|
||||
const handleExportPreview = useCallback(() => {
|
||||
if (!exportRange) {
|
||||
toast.error(
|
||||
t("export.toast.error.noVaildTimeSelected", {
|
||||
t("export.toast.error.noValidTimeSelected", {
|
||||
ns: "components/dialog",
|
||||
}),
|
||||
{
|
||||
@@ -351,7 +351,7 @@ export default function MotionSearchView({
|
||||
const handleExportSave = useCallback(() => {
|
||||
if (!exportRange || !selectedCamera) {
|
||||
toast.error(
|
||||
t("export.toast.error.noVaildTimeSelected", {
|
||||
t("export.toast.error.noValidTimeSelected", {
|
||||
ns: "components/dialog",
|
||||
}),
|
||||
{
|
||||
|
||||
Reference in New Issue
Block a user