Merge remote-tracking branch 'origin/master' into dev
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Resolve conflicts in the export pipeline where dev's job-queue refactor
met master's chapter-metadata and security work.

- Unify chapter support under ChaptersEnum (none / recording_segments /
  review_items); the realtime stream-copy export selects the per-segment
  or per-review-item builder by the camera's configured mode. Thread
  chapters through ExportRecordingsBody -> _build_export_job -> ExportJob
  -> RecordingExporter.
- Keep master's creation_time/comment export metadata and fix a
  video_path duplication the textual merge introduced in the preview
  command.
- Move the chapters request field to ExportRecordingsBody (the single
  export endpoint) where it is actually honored.

Restore security fixes the automatic merge would have reverted:
- frigate/util/services.py: restore the #23493 rename to the public
  is_go2rtc_arbitrary_exec_allowed so create_config.py's dynamic-source
  exec guard imports and runs (the merge otherwise left a broken import).
- Preserve the export image-path ".." traversal check inside
  _sanitize_existing_image, applied to single/custom/batch exports.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
This commit is contained in:
Blake Blackshear
2026-06-28 15:04:01 +02:00
co-authored by Claude Opus 4.8
18 changed files with 470 additions and 34 deletions
+23 -1
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@@ -7,6 +7,8 @@ import ConfigTabs from "@site/src/components/ConfigTabs";
import TabItem from "@theme/TabItem";
import NavPath from "@site/src/components/NavPath";
Frigate has two kinds of masks: motion masks and object filter masks. Both are narrow tools for fine-tuning, **not for hiding an area from Frigate**. Masks should be used sparingly; in most cases where users reach for one, a [zone](zones.md) with `required_zones` is the right tool instead. See [Which tool do I need?](#which-tool-do-i-need) and [Common mistakes](#common-mistakes) below if you're new to Frigate's mask behavior.
## Motion masks
Motion masks are used to prevent unwanted types of motion from triggering detection. Try watching the Debug feed (Settings --> Debug) with `Motion Boxes` enabled to see what may be regularly detected as motion. For example, you want to mask out your timestamp, the sky, rooftops, etc. Keep in mind that this mask only prevents motion from being detected and does not prevent objects from being detected if object detection was started due to motion in unmasked areas. Motion is also used during object tracking to refine the object detection area in the next frame. _Over-masking will make it more difficult for objects to be tracked._
@@ -21,7 +23,16 @@ Object filter masks can be used to filter out stubborn false positives in fixed
![object mask](/img/bottom-center-mask.jpg)
## Creating masks
## Which tool do I need?
| What you're trying to do | Recommended tool | How it works |
| ------------------------------------------------------------------------------------------------------------------------------ | ----------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Don't get alerts or recordings for activity in an area (e.g., the sidewalk in front of your house) | A [zone](zones.md) combined with `review.alerts.required_zones` (and/or `review.detections.required_zones`) | Frigate keeps detecting and tracking activity in the area, but a review item is only created once the bottom-center of an object's bounding box enters a required zone. |
| Stop a stubborn false positive at a specific fixed spot (e.g., a tree base that keeps being detected as a person) | An **object filter mask** for that object type | Any detection of that object type whose bounding-box bottom-center lands inside the mask is treated as a false positive and discarded. |
| Ignore motion in an area that obviously isn't an object of interest (e.g., the camera timestamp, sky, flags, treetops swaying) | A **motion mask** | Motion inside the mask is ignored when deciding whether to run object detection. Objects can still be detected in a motion masked area if motion elsewhere in the frame triggers detection. |
| Stop tracking an object type altogether on this camera (e.g., you never care about cats) | Remove the object from the camera's [`objects.track`](objects.md) list | Frigate skips this object type entirely on this camera, regardless of where it appears. |
## Using the mask creator
<ConfigTabs>
<TabItem value="ui">
@@ -124,3 +135,14 @@ This is what `required_zones` are for. You should define a zone (remember this i
> Maybe my specific situation just warrants this. I've just been having a hard time understanding the relevance of this information - it seems to be that it's exactly what would be expected when "masking out" an area of ANY image.
That may be the case for you. Frigate will definitely work harder tracking people on the sidewalk to make sure it doesn't miss anyone who steps foot on your stoop. The trade off with the way you have it now is slower recognition of objects and potential misses. That may be acceptable based on your needs. Also, if your resolution is low enough on the detect stream, your regions may already be so big that they grab the entire object anyway.
## Common mistakes
**"I added a motion mask to ignore my driveway/sidewalk."**
A motion mask doesn't hide an area from Frigate. Objects can still be detected and tracked inside a masked area. The mask only stops motion _in that area_ from triggering object detection. If you want activity on the sidewalk to never produce a review item, define a [zone](zones.md) over the area you DO care about (your stoop, your driveway) and add it to `review.alerts.required_zones`. Frigate will still see people on the sidewalk, but it won't create an alert until they cross into the zone.
**"I added an object filter mask because I don't care about cars in my yard."**
Object filter masks are for stubborn false positives at fixed locations, not for filtering whole areas or whole object types. If you only want alerts when a car enters the driveway, use a [zone](zones.md) with `required_zones`. If you don't care about a whole object type on this camera, remove it from [`objects.track`](objects.md).
**"I masked everything except a thin strip on my stoop."**
Heavy masking hurts tracking. Frigate uses motion near a tracked object's previous bounding box to decide where to look in the next frame; with most of the frame masked, an object walking from an unmasked area into a masked one effectively disappears and gets picked up as a "new" object when it reappears. For example: someone walks down your sidewalk, stops under a tree (masked area) to tie their shoe, then continues. Frigate sees that as two separate people and can create two separate review items. Because Frigate needs several consecutive frames above the confidence threshold to commit to a detection, each re-appearance can also delay or miss alerts. Use `required_zones` for "only alert me about this spot" and leave the surrounding area unmasked so tracking stays intact.
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@@ -124,3 +124,19 @@ cameras:
width: 1280
height: 720
```
### Why does Frigate keep creating new events for my parked car?
Stationary tracking is designed to _prevent_ this — a parked car should stay one tracked object and not generate new events. If you're getting repeated events for the same car, it's likely that Frigate is losing the tracked object and re-detecting it as a new one.
Open one of the events in Explore → **Tracking Details**. If the detection scores are low (< 70% or so), the model isn't confident the parked car is a car. This is common with the free [COCO-trained](https://cocodataset.org/#explore) object detection models on steep/top-down angles, partially occluded cars, foliage, or low-light footage. When detections fall below `min_score` for too many frames the tracker loses the object, and the next confident frame creates a brand new one.
What helps:
- **Improve the view** — even a small angle change that gets more of the car visible could lift scores enough to stabilize tracking.
- **Use a more accurate model** — switching from `mobiledet` to `yolov9`, or stepping up to a larger variant like `yolov9-s` over `yolov9-t`, can help (at the cost of inference time, and still on the COCO dataset). The biggest gains usually come from fine-tuning a model on images from your own cameras so it learns your specific scene. [Frigate+](https://frigate.video/plus) is a paid option that does this - models are trained on security-camera footage and can be fine-tuned on images you submit from your own setup.
- **Don't set `detect -> stationary -> max_frames` for `car`** — it artificially ends tracking and forces re-detection as a new object. See [Stationary Objects](../configuration/stationary_objects.md).
- **Restrict alerts to the areas you care about** with `required_zones` — see [Zones](../configuration/zones.md#restricting-alerts-and-detections-to-specific-zones). Make sure those zones use the default `loitering_time: 0` unless you specifically want the review item to stay open until the car leaves.
- **Filter impossible locations** with [object filter masks](../configuration/masks.md#object-filter-masks) if cars are being detected on rooftops, treetops, etc.
See [Object Filters](../configuration/object_filters.md) for more on tuning `min_score` and `threshold` — note that raising them too high will make this exact problem worse.
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@@ -7393,6 +7393,13 @@ components:
required:
- value
title: CameraSetBody
ChaptersEnum:
type: string
enum:
- none
- recording_segments
- review_items
title: ChaptersEnum
ChatCompletionRequest:
properties:
messages:
@@ -8119,6 +8126,13 @@ components:
- type: 'null'
title: Export case ID
description: ID of the export case to assign this export to
chapters:
anyOf:
- $ref: '#/components/schemas/ChaptersEnum'
- type: 'null'
title: Chapter mode
description: Optional chapter metadata to embed in the export. When
omitted, the camera's configured export chapter mode is used.
type: object
title: ExportRecordingsBody
ExportRecordingsCustomBody: