disable disk sync on startup

* allow for ".yaml"

* remove unused import

.dockerignore

@@ -7,4 +7,5 @@ config/
 .git
 core
 *.mp4
-*.db
+*.db
+*.ts

.github/ISSUE_TEMPLATE/bug_report.md

@@ -1,56 +0,0 @@
----
-name: Bug report or Support request
-about: Bug report or Support request
-title: ''
-labels: ''
-assignees: ''
-
----
-
-**Describe the bug**
-A clear and concise description of what your issue is.
-
-**Version of frigate**
-Output from `/api/version`
-
-**Config file**
-Include your full config file wrapped in triple back ticks.
-```yaml
-config here
-```
-
-**Frigate container logs**
-```
-Include relevant log output here
-```
-
-**Frigate stats**
-```json
-Output from frigate's /api/stats endpoint
-```
-
-**FFprobe from your camera**
-
-Run the following command and paste output below
-```
-ffprobe <stream_url>
-```
-
-**Screenshots**
-If applicable, add screenshots to help explain your problem.
-
-**Computer Hardware**
- - OS: [e.g. Ubuntu, Windows]
- - Install method: [e.g. Addon, Docker Compose, Docker Command]
- - Virtualization: [e.g. Proxmox, Virtualbox]
- - Coral Version: [e.g. USB, PCIe, None]
- - Network Setup: [e.g. Wired, WiFi]
-
-**Camera Info:**
- - Manufacturer: [e.g. Dahua]
- - Model: [e.g. IPC-HDW5231R-ZE]
- - Resolution: [e.g. 720p]
- - FPS: [e.g. 5]
-
-**Additional context**
-Add any other context about the problem here.

.github/ISSUE_TEMPLATE/config.yml

@@ -0,0 +1 @@
+blank_issues_enabled: false

.github/ISSUE_TEMPLATE/support_request.yml

@@ -0,0 +1,107 @@
+name: Support Request
+description: Support for Frigate setup or configuration
+title: "[Support]: "
+labels: ["support", "triage"]
+assignees: []
+body:
+  - type: textarea
+    id: description
+    attributes:
+      label: Describe the problem you are having
+    validations:
+      required: true
+  - type: input
+    id: version
+    attributes:
+      label: Version
+      description: Visible on the Debug page in the Web UI
+    validations:
+      required: true
+  - type: textarea
+    id: config
+    attributes:
+      label: Frigate config file
+      description: This will be automatically formatted into code, so no need for backticks.
+      render: yaml
+    validations:
+      required: true
+  - type: textarea
+    id: logs
+    attributes:
+      label: Relevant log output
+      description: Please copy and paste any relevant log output. This will be automatically formatted into code, so no need for backticks.
+      render: shell
+    validations:
+      required: true
+  - type: textarea
+    id: ffprobe
+    attributes:
+      label: FFprobe output from your camera
+      description: Run `ffprobe <camera_url>` and provide output below
+      render: shell
+    validations:
+      required: true
+  - type: textarea
+    id: stats
+    attributes:
+      label: Frigate stats
+      description: Output from frigate's /api/stats endpoint
+      render: json
+  - type: dropdown
+    id: os
+    attributes:
+      label: Operating system
+      options:
+        - HassOS
+        - Debian
+        - Other Linux
+        - Proxmox
+        - UNRAID
+        - Windows
+        - Other
+    validations:
+      required: true
+  - type: dropdown
+    id: install-method
+    attributes:
+      label: Install method
+      options:
+        - HassOS Addon
+        - Docker Compose
+        - Docker CLI
+    validations:
+      required: true
+  - type: dropdown
+    id: coral
+    attributes:
+      label: Coral version
+      options:
+        - USB
+        - PCIe
+        - M.2
+        - Dev Board
+        - Other
+        - CPU (no coral)
+    validations:
+      required: true
+  - type: dropdown
+    id: network
+    attributes:
+      label: Network connection
+      options:
+        - Wired
+        - Wireless
+        - Mixed
+    validations:
+      required: true
+  - type: input
+    id: camera
+    attributes:
+      label: Camera make and model
+      description: Dahua, hikvision, amcrest, reolink, etc and model number
+    validations:
+      required: true
+  - type: textarea
+    id: other
+    attributes:
+      label: Any other information that may be helpful

.github/workflows/push.yml

@@ -1,28 +0,0 @@
-name: On push
-
-on:
-  push:
-    branches:
-      - master
-      - release-0.8.0
-
-jobs:
-  deploy-docs:
-    name: Deploy docs
-    runs-on: ubuntu-latest
-    defaults:
-      run:
-        working-directory: ./docs
-    steps:
-      - uses: actions/checkout@master
-      - uses: actions/setup-node@master
-        with:
-          node-version: 12.x
-      - run: npm install
-      - name: Build docs
-        run: npm run build
-      - name: Deploy documentation
-        uses: peaceiris/actions-gh-pages@v3
-        with:
-          github_token: ${{ secrets.GITHUB_TOKEN }}
-          publish_dir: ./docs/build

.gitignore

@@ -6,7 +6,9 @@ debug
 config/config.yml
 models
 *.mp4
+*.ts
 *.db
+*.csv
 frigate/version.py
 web/build
 web/node_modules

Makefile

@@ -3,7 +3,7 @@ default_target: amd64_frigate
 COMMIT_HASH := $(shell git log -1 --pretty=format:"%h"|tail -1)
 
 version:
-	echo "VERSION='0.9.0-$(COMMIT_HASH)'" > frigate/version.py
+	echo "VERSION='0.10.0-$(COMMIT_HASH)'" > frigate/version.py
 
 web:
 	docker build --tag frigate-web --file docker/Dockerfile.web web/
@@ -42,7 +42,7 @@ aarch64_ffmpeg:
 	docker build --no-cache --pull --tag blakeblackshear/frigate-ffmpeg:1.3.0-aarch64 --file docker/Dockerfile.ffmpeg.aarch64 .
 
 aarch64_frigate: version web
-	docker build --no-cache --tag frigate-base --build-arg ARCH=aarch64 --build-arg FFMPEG_VERSION=1.3.0 --build-arg WHEELS_VERSION=1.0.3 --build-arg NGINX_VERSION=1.0.2 --file docker/Dockerfile.base .
+	docker build --no-cache --tag frigate-base --build-arg ARCH=aarch64 --build-arg FFMPEG_VERSION=1.0.0 --build-arg WHEELS_VERSION=1.0.3 --build-arg NGINX_VERSION=1.0.2 --file docker/Dockerfile.base .
 	docker build --no-cache --tag frigate --file docker/Dockerfile.aarch64 .
 
 aarch64_all: aarch64_wheels aarch64_ffmpeg aarch64_frigate

README.md

@@ -20,7 +20,7 @@ Use of a [Google Coral Accelerator](https://coral.ai/products/) is optional, but
 
 ## Documentation
 
-View the documentation at https://blakeblackshear.github.io/frigate
+View the documentation at https://docs.frigate.video
 
 ## Donations
 

docker/rootfs/usr/local/nginx/conf/nginx.conf

@@ -58,7 +58,7 @@ http {
 
         # vod caches
         vod_metadata_cache metadata_cache 512m;
-        vod_mapping_cache mapping_cache 5m;
+        vod_mapping_cache mapping_cache 5m 10m;
 
         # gzip manifests
         gzip on;

docs/docs/configuration/advanced.md

@@ -48,3 +48,17 @@ This may need to be in a custom location if network storage is used for the medi
 If using a custom model, the width and height will need to be specified.
 
 The labelmap can be customized to your needs. A common reason to do this is to combine multiple object types that are easily confused when you don't need to be as granular such as car/truck. By default, truck is renamed to car because they are often confused. You cannot add new object types, but you can change the names of existing objects in the model.
+
+```yaml
+model:
+  labelmap:
+    2: vehicle
+    3: vehicle
+    5: vehicle
+    7: vehicle
+    15: animal
+    16: animal
+    17: animal
+```
+
+Note that if you rename objects in the labelmap, you will also need to update your `objects -> track` list as well.

docs/docs/configuration/camera_specific.md

@@ -19,7 +19,7 @@ output_args:
   rtmp: -c:v libx264 -an -f flv
 ```
 
-### RTMP Cameras (Reolink 410/520 and possibly others)
+### RTMP Cameras
 
 The input parameters need to be adjusted for RTMP cameras
 
@@ -28,6 +28,46 @@ ffmpeg:
   input_args: -avoid_negative_ts make_zero -fflags nobuffer -flags low_delay -strict experimental -fflags +genpts+discardcorrupt -rw_timeout 5000000 -use_wallclock_as_timestamps 1 -f live_flv
 ```
 
+### Reolink 410/520 (possibly others)
+
+According to [this discussion](https://github.com/blakeblackshear/frigate/issues/1713#issuecomment-932976305), the http video streams seem to be the most reliable for Reolink.
+
+```yaml
+cameras:
+  reolink:
+    ffmpeg:
+      hwaccel_args:
+      input_args:
+        - -avoid_negative_ts
+        - make_zero
+        - -fflags
+        - nobuffer+genpts+discardcorrupt
+        - -flags
+        - low_delay
+        - -strict
+        - experimental
+        - -analyzeduration
+        - 1000M
+        - -probesize
+        - 1000M
+        - -rw_timeout
+        - "5000000"
+      inputs:
+        - path: http://reolink_ip/flv?port=1935&app=bcs&stream=channel0_main.bcs&user=username&password=password
+          roles:
+            - record
+            - rtmp
+        - path: http://reolink_ip/flv?port=1935&app=bcs&stream=channel0_ext.bcs&user=username&password=password
+          roles:
+            - detect
+    detect:
+      width: 640
+      height: 480
+      fps: 7
+```
+
+![Resolutions](/img/reolink-settings.png)
+
 ### Blue Iris RTSP Cameras
 
 You will need to remove `nobuffer` flag for Blue Iris RTSP cameras

docs/docs/configuration/detectors.md

@@ -31,6 +31,7 @@ detectors:
 ```
 
 ### Native Coral (Dev Board)
+_warning: may have [compatibility issues](https://github.com/blakeblackshear/frigate/issues/1706) after `v0.9.x`_
 
 ```yaml
 detectors:

docs/docs/configuration/index.md

@@ -48,8 +48,8 @@ mqtt:
   # Optional: user
   user: mqtt_user
   # Optional: password
-  # NOTE: Environment variables that begin with 'FRIGATE_' may be referenced in {}.
-  #       eg. password: '{FRIGATE_MQTT_PASSWORD}'
+  # NOTE: MQTT password can be specified with an environment variables that must begin with 'FRIGATE_'.
+  #       e.g. password: '{FRIGATE_MQTT_PASSWORD}'
   password: password
   # Optional: tls_ca_certs for enabling TLS using self-signed certs (default: None)
   tls_ca_certs: /path/to/ca.crt
@@ -159,6 +159,8 @@ detect:
   enabled: True
   # Optional: Number of frames without a detection before frigate considers an object to be gone. (default: 5x the frame rate)
   max_disappeared: 25
+  # Optional: Frequency for running detection on stationary objects (default: 10x the frame rate)
+  stationary_interval: 50
 
 # Optional: Object configuration
 # NOTE: Can be overridden at the camera level
@@ -192,10 +194,14 @@ motion:
   # Increasing this value will make motion detection less sensitive and decreasing it will make motion detection more sensitive.
   # The value should be between 1 and 255.
   threshold: 25
-  # Optional: Minimum size in pixels in the resized motion image that counts as motion (default: ~0.17% of the motion frame area)
-  # Increasing this value will prevent smaller areas of motion from being detected. Decreasing will make motion detection more sensitive to smaller
-  # moving objects.
-  contour_area: 100
+  # Optional: Minimum size in pixels in the resized motion image that counts as motion (default: 30)
+  # Increasing this value will prevent smaller areas of motion from being detected. Decreasing will
+  # make motion detection more sensitive to smaller moving objects.
+  # As a rule of thumb:
+  #  - 15 - high sensitivity
+  #  - 30 - medium sensitivity
+  #  - 50 - low sensitivity
+  contour_area: 30
   # Optional: Alpha value passed to cv2.accumulateWeighted when averaging the motion delta across multiple frames (default: shown below)
   # Higher values mean the current frame impacts the delta a lot, and a single raindrop may register as motion.
   # Too low and a fast moving person wont be detected as motion.
@@ -205,10 +211,10 @@ motion:
   # Low values will cause things like moving shadows to be detected as motion for longer.
   # https://www.geeksforgeeks.org/background-subtraction-in-an-image-using-concept-of-running-average/
   frame_alpha: 0.2
-  # Optional: Height of the resized motion frame  (default: 1/6th of the original frame height, but no less than 180)
-  # This operates as an efficient blur alternative. Higher values will result in more granular motion detection at the expense of higher CPU usage.
-  # Lower values result in less CPU, but small changes may not register as motion.
-  frame_height: 180
+  # Optional: Height of the resized motion frame  (default: 50)
+  # This operates as an efficient blur alternative. Higher values will result in more granular motion detection at the expense
+  # of higher CPU usage. Lower values result in less CPU, but small changes may not register as motion.
+  frame_height: 50
   # Optional: motion mask
   # NOTE: see docs for more detailed info on creating masks
   mask: 0,900,1080,900,1080,1920,0,1920
@@ -218,15 +224,23 @@ motion:
 record:
   # Optional: Enable recording (default: shown below)
   enabled: False
-  # Optional: Number of days to retain recordings regardless of events (default: shown below)
-  # NOTE: This should be set to 0 and retention should be defined in events section below
-  #       if you only want to retain recordings of events.
-  retain_days: 0
+  # Optional: Retention settings for recording
+  retain:
+    # Optional: Number of days to retain recordings regardless of events (default: shown below)
+    # NOTE: This should be set to 0 and retention should be defined in events section below
+    #       if you only want to retain recordings of events.
+    days: 0
+    # Optional: Mode for retention. Available options are: all, motion, and active_objects
+    #   all - save all recording segments regardless of activity
+    #   motion - save all recordings segments with any detected motion
+    #   active_objects - save all recording segments with active/moving objects
+    # NOTE: this mode only applies when the days setting above is greater than 0
+    mode: all
   # Optional: Event recording settings
   events:
     # Optional: Maximum length of time to retain video during long events. (default: shown below)
     # NOTE: If an object is being tracked for longer than this amount of time, the retained recordings
-    #       will be the last x seconds of the event unless retain_days under record is > 0.
+    #       will be the last x seconds of the event unless retain->days under record is > 0.
     max_seconds: 300
     # Optional: Number of seconds before the event to include (default: shown below)
     pre_capture: 5
@@ -241,6 +255,16 @@ record:
     retain:
       # Required: Default retention days (default: shown below)
       default: 10
+      # Optional: Mode for retention. (default: shown below)
+      #   all - save all recording segments for events regardless of activity
+      #   motion - save all recordings segments for events with any detected motion
+      #   active_objects - save all recording segments for event with active/moving objects
+      #
+      # NOTE: If the retain mode for the camera is more restrictive than the mode configured
+      #       here, the segments will already be gone by the time this mode is applied.
+      #       For example, if the camera retain mode is "motion", the segments without motion are
+      #       never stored, so setting the mode to "all" here won't bring them back.
+      mode: active_objects
       # Optional: Per object retention days
       objects:
         person: 15
@@ -319,7 +343,7 @@ cameras:
       # Required: A list of input streams for the camera. See documentation for more information.
       inputs:
         # Required: the path to the stream
-        # NOTE: Environment variables that begin with 'FRIGATE_' may be referenced in {}
+        # NOTE: path may include environment variables, which must begin with 'FRIGATE_' and be referenced in {}
         - path: rtsp://viewer:{FRIGATE_RTSP_PASSWORD}@10.0.10.10:554/cam/realmonitor?channel=1&subtype=2
           # Required: list of roles for this stream. valid values are: detect,record,rtmp
           # NOTICE: In addition to assigning the record, and rtmp roles,

docs/docs/configuration/masks.md

@@ -36,7 +36,7 @@ motion:
     - 0,461,3,0,1919,0,1919,843,1699,492,1344
 ```
 
-![poly](/img/example-mask-poly.png)
+![poly](/img/example-mask-poly-min.png)
 
 ### Further Clarification
 

docs/docs/configuration/nvdec.md

@@ -9,6 +9,8 @@ ffmpeg with NVDEC support is required. The special docker architecture 'amd64nvi
 includes this support for amd64 platforms. An aarch64 for the Jetson, which
 also includes NVDEC may be added in the future.
 
+Some more detailed setup instructions are also available in [this issue](https://github.com/blakeblackshear/frigate/issues/1847#issuecomment-932076731).
+
 ## Docker setup
 
 ### Requirements

docs/docs/configuration/record.md

@@ -14,12 +14,11 @@ If you only used clips in previous versions with recordings disabled, you can us
 ```yaml
 record:
   enabled: True
-  retain_days: 0
   events:
     retain:
       default: 10
 ```
 
-This configuration will retain recording segments that overlap with events for 10 days. Because multiple events can reference the same recording segments, this avoids storing duplicate footage for overlapping events and reduces overall storage needs.
+This configuration will retain recording segments that overlap with events and have active tracked objects for 10 days. Because multiple events can reference the same recording segments, this avoids storing duplicate footage for overlapping events and reduces overall storage needs.
 
-When `retain_days` is set to `0`, events will have up to `max_seconds` (defaults to 5 minutes) of recordings retained. Increasing `retain_days` to `1` will allow events to exceed the `max_seconds` limitation of up to 1 day.
+When `retain_days` is set to `0`, segments will be deleted from the cache if no events are in progress.

docs/docs/configuration/zones.md

@@ -20,6 +20,10 @@ camera:
       required_zones:
         - entire_yard
         - front_yard_street
+  snapshots:
+    required_zones:
+      - entire_yard
+      - front_yard_street
   zones:
     entire_yard:
       coordinates: ... (everywhere you want a person)
@@ -31,4 +35,4 @@ camera:
         - car
 ```
 
-Only car objects can trigger the `front_yard_street` zone and only person can trigger the `entire_yard`. You will get clips for person objects that enter anywhere in the yard, and clips for cars only if they enter the street.
+Only car objects can trigger the `front_yard_street` zone and only person can trigger the `entire_yard`. You will get events for person objects that enter anywhere in the yard, and events for cars only if they enter the street.

docs/docs/faqs.md

@@ -13,13 +13,13 @@ A solid green image means that frigate has not received any frames from ffmpeg.
 
 ### How can I get sound or audio in my recordings?
 
-By default, Frigate removes audio from recordings to reduce the likelihood of failing for invalid data. If you would like to include audio, you need to override the output args to remove `-an` for where you want to include audio. The recommended audio codec is `aac`. Not all audio codecs are supported by RTMP, so you may need to re-encode your audio with `-c:a aac`. The default ffmpeg args are shown [here](configuration/index#ffmpeg).
+By default, Frigate removes audio from recordings to reduce the likelihood of failing for invalid data. If you would like to include audio, you need to override the output args to remove `-an` for where you want to include audio. The recommended audio codec is `aac`. Not all audio codecs are supported by RTMP, so you may need to re-encode your audio with `-c:a aac`. The default ffmpeg args are shown [here](configuration/index#full-configuration-reference).
 
 ### My mjpeg stream or snapshots look green and crazy
 
 This almost always means that the width/height defined for your camera are not correct. Double check the resolution with vlc or another player. Also make sure you don't have the width and height values backwards.
 
-![mismatched-resolution](/img/mismatched-resolution.jpg)
+![mismatched-resolution](/img/mismatched-resolution-min.jpg)
 
 ### I can't view events or recordings in the Web UI.
 

docs/docs/guides/camera_setup.md

@@ -17,7 +17,7 @@ The ideal resolution for detection is one where the objects you want to detect f
 
 Larger resolutions **do** improve performance if the objects are very small in the frame.
 
-![Resolutions](/img/resolutions.png)
+![Resolutions](/img/resolutions-min.jpg)
 
 ### Example Camera Configuration
 

docs/docs/guides/stationary_objects.md

@@ -15,13 +15,13 @@ Frigate is designed to track objects as they move and over-masking can prevent i
 
 :::
 
-For example, you could create multiple zones that cover your driveway. For cars, you would only notify if entered_zones has more than 1 zone. For person, you would notify regardless of the number of entered_zones.
+To only be notified of cars that enter your driveway from the street, you could create multiple zones that cover your driveway. For cars, you would only notify if `entered_zones` from the events MQTT topic has more than 1 zone.
 
-See [this example](/configuration/zones#restricting-zones-to-specific-objects) from the Zones documentation.
+See [this example](/configuration/zones#restricting-zones-to-specific-objects) from the Zones documentation to see how to restrict zones to certain object types.
 
-You can also create a zone for the entrance of your driveway and only save an event if that zone is in the list of entered_zones when the object is a car.
+![Driveway Zones](/img/driveway_zones-min.png)
 
-![Driveway Zones](/img/driveway_zones.png)
+To limit snapshots and events, you can list the zone for the entrance of your driveway under `required_zones` in your configuration file. Example below.
 
 ```yaml
 camera:

docs/docs/hardware.md

@@ -9,28 +9,31 @@ Cameras that output H.264 video and AAC audio will offer the most compatibility
 
 I recommend Dahua, Hikvision, and Amcrest in that order. Dahua edges out Hikvision because they are easier to find and order, not because they are better cameras. I personally use Dahua cameras because they are easier to purchase directly. In my experience Dahua and Hikvision both have multiple streams with configurable resolutions and frame rates and rock solid streams. They also both have models with large sensors well known for excellent image quality at night. Not all the models are equal. Larger sensors are better than higher resolutions; especially at night. Amcrest is the fallback recommendation because they are rebranded Dahuas. They are rebranding the lower end models with smaller sensors or less configuration options.
 
+Many users have reported various issues with Reolink cameras, so I do not recommend them. If you are using Reolink, I suggest the [Reolink specific configuration](configuration/camera_specific#reolink-410520-possibly-others). Wifi cameras are also not recommended. Their streams are less reliable and cause connection loss and/or lost video data.
+
 Here are some of the camera's I recommend:
 
-- [Loryta(Dahua) T5442TM-AS-LED](https://amzn.to/2Wck2hQ) (affiliate link)
-- [Loryta(Dahua) IPC-T5442TM-AS](https://amzn.to/39FODrm) (affiliate link)
-- [Amcrest IP5M-T1179EW-28MM](https://amzn.to/39H1zgt) (affiliate link)
+- <a href="https://amzn.to/3uFLtxB" target="_blank" rel="nofollow noopener sponsored">Loryta(Dahua) T5442TM-AS-LED</a> (affiliate link)
+- <a href="https://amzn.to/3isJ3gU" target="_blank" rel="nofollow noopener sponsored">Loryta(Dahua) IPC-T5442TM-AS</a> (affiliate link)
+- <a href="https://amzn.to/2ZWNWIA" target="_blank" rel="nofollow noopener sponsored">Amcrest IP5M-T1179EW-28MM</a> (affiliate link)
 
 I may earn a small commission for my endorsement, recommendation, testimonial, or link to any products or services from this website.
 
 ## Server
 
-My current favorite is the Minisforum GK50 because the dual NICs allow you to setup a dedicated private network for your cameras where they can be blocked from accessing the internet. I may earn a small commission for my endorsement, recommendation, testimonial, or link to any products or services from this website.
+My current favorite is the Odyssey X86 Blue J4125 because the Coral M.2 compatibility and dual NICs that allow you to setup a dedicated private network for your cameras where they can be blocked from accessing the internet. I may earn a small commission for my endorsement, recommendation, testimonial, or link to any products or services from this website.
 
-| Name                                                                | Inference Speed | Notes                                                                                                                         |
-| ------------------------------------------------------------------- | --------------- | ----------------------------------------------------------------------------------------------------------------------------- |
-| [Minisforum GK41](https://amzn.to/3kI0njr) (affiliate link)         | 9-10ms          | Great alternative to a NUC. Easily handles several 1080p cameras.                                                             |
-| [Minisforum GK50](https://amzn.to/3m49yKk) (affiliate link)         | 9-10ms          | Dual gigabit NICs for easy isolated camera network. Easily handles several 1080p cameras.                                     |
-| [Intel NUC](https://amzn.to/3kImYMT) (affiliate link)               | 8-10ms          | Overkill for most, but great performance. Can handle many cameras at 5fps depending on typical amounts of motion.             |
-| [BMAX B2 Plus](https://amzn.to/3uccBnD) (affiliate link)            | 10-12ms         | Good balance of performance and cost. Also capable of running many other services at the same time as frigate.                |
-| [Atomic Pi](https://amzn.to/3i9YRVw) (affiliate link)               | 16ms            | Good option for a dedicated low power board with a small number of cameras. Can leverage Intel QuickSync for stream decoding. |
-| [Raspberry Pi 3B (32bit)](https://amzn.to/3lZUi16) (affiliate link) | 60ms            | Can handle a small number of cameras, but the detection speeds are slow due to USB 2.0.                                       |
-| [Raspberry Pi 4 (32bit)](https://amzn.to/2ZpgDNW) (affiliate link)  | 15-20ms         | Can handle a small number of cameras. The 2GB version runs fine.                                                              |
-| [Raspberry Pi 4 (64bit)](https://amzn.to/2ZpgDNW) (affiliate link)  | 10-15ms         | Can handle a small number of cameras. The 2GB version runs fine.                                                              |
+| Name                                                                                                                             | Inference Speed | Coral Compatibility | Notes                                                                                                                         |
+| -------------------------------------------------------------------------------------------------------------------------------- | --------------- | ------------------- | ----------------------------------------------------------------------------------------------------------------------------- |
+| <a href="https://amzn.to/3oH4BKi" target="_blank" rel="nofollow noopener sponsored">Odyssey X86 Blue J4125</a> (affiliate link)  | 9-10ms          | M.2 B+M             | Dual gigabit NICs for easy isolated camera network. Easily handles several 1080p cameras.                                     |
+| <a href="https://amzn.to/3oxEC8m" target="_blank" rel="nofollow noopener sponsored">Minisforum GK41</a> (affiliate link)         | 9-10ms          | USB                 | Great alternative to a NUC. Easily handles several 1080p cameras.                                                             |
+| <a href="https://amzn.to/3ixJFlb" target="_blank" rel="nofollow noopener sponsored">Minisforum GK50</a> (affiliate link)         | 9-10ms          | USB                 | Dual gigabit NICs for easy isolated camera network. Easily handles several 1080p cameras.                                     |
+| <a href="https://amzn.to/3l7vCEI" target="_blank" rel="nofollow noopener sponsored">Intel NUC</a> (affiliate link)               | 8-10ms          | USB                 | Overkill for most, but great performance. Can handle many cameras at 5fps depending on typical amounts of motion.             |
+| <a href="https://amzn.to/3a6TBh8" target="_blank" rel="nofollow noopener sponsored">BMAX B2 Plus</a> (affiliate link)            | 10-12ms         | USB                 | Good balance of performance and cost. Also capable of running many other services at the same time as frigate.                |
+| <a href="https://amzn.to/2YjpY9m" target="_blank" rel="nofollow noopener sponsored">Atomic Pi</a> (affiliate link)               | 16ms            | USB                 | Good option for a dedicated low power board with a small number of cameras. Can leverage Intel QuickSync for stream decoding. |
+| <a href="https://amzn.to/2WIpwRU" target="_blank" rel="nofollow noopener sponsored">Raspberry Pi 3B (32bit)</a> (affiliate link) | 60ms            | USB                 | Can handle a small number of cameras, but the detection speeds are slow due to USB 2.0.                                       |
+| <a href="https://amzn.to/2YhSGHH" target="_blank" rel="nofollow noopener sponsored">Raspberry Pi 4 (32bit)</a> (affiliate link)  | 15-20ms         | USB                 | Can handle a small number of cameras. The 2GB version runs fine.                                                              |
+| <a href="https://amzn.to/2YhSGHH" target="_blank" rel="nofollow noopener sponsored">Raspberry Pi 4 (64bit)</a> (affiliate link)  | 10-15ms         | USB                 | Can handle a small number of cameras. The 2GB version runs fine.                                                              |
 
 ## Google Coral TPU
 
@@ -41,3 +44,25 @@ The USB version is compatible with the widest variety of hardware and does not r
 The PCIe and M.2 versions require installation of a driver on the host. Follow the instructions for your version from https://coral.ai
 
 A single Coral can handle many cameras and will be sufficient for the majority of users. You can calculate the maximum performance of your Coral based on the inference speed reported by Frigate. With an inference speed of 10, your Coral will top out at `1000/10=100`, or 100 frames per second. If your detection fps is regularly getting close to that, you should first consider tuning motion masks. If those are already properly configured, a second Coral may be needed.
+
+### What does Frigate use the CPU for and what does it use the Coral for? (ELI5 Version)
+
+This is taken from a [user question on reddit](https://www.reddit.com/r/homeassistant/comments/q8mgau/comment/hgqbxh5/?utm_source=share&utm_medium=web2x&context=3). Modified slightly for clarity.
+
+CPU Usage: I am a CPU, Mendel is a Google Coral
+
+My buddy Mendel and I have been tasked with keeping the neighbor's red footed booby off my parent's yard. Now I'm really bad at identifying birds. It takes me forever, but my buddy Mendel is incredible at it.
+
+Mendel however, struggles at pretty much anything else. So we make an agreement. I wait till I see something that moves, and snap a picture of it for Mendel. I then show him the picture and he tells me what it is. Most of the time it isn't anything. But eventually I see some movement and Mendel tells me it is the Booby. Score!
+
+_What happens when I increase the resolution of my camera?_
+
+However we realize that there is a problem. There is still booby poop all over the yard. How could we miss that! I've been watching all day! My parents check the window and realize its dirty and a bit small to see the entire yard so they clean it and put a bigger one in there. Now there is so much more to see! However I now have a much bigger area to scan for movement and have to work a lot harder! Even my buddy Mendel has to work harder, as now the pictures have a lot more detail in them that he has to look at to see if it is our sneaky booby.
+
+Basically - When you increase the resolution and/or the frame rate of the stream there is now significantly more data for the CPU to parse. That takes additional computing power. The Google Coral is really good at doing object detection, but it doesn't have time to look everywhere all the time (especially when there are many windows to check). To balance it, Frigate uses the CPU to look for movement, then sends those frames to the Coral to do object detection. This allows the Coral to be available to a large number of cameras and not overload it.
+
+### Do hwaccel args help if I am using a Coral?
+
+YES! The Coral does not help with decoding video streams.
+
+Decompressing video streams takes a significant amount of CPU power. Video compression uses key frames (also known as I-frames) to send a full frame in the video stream. The following frames only include the difference from the key frame, and the CPU has to compile each frame by merging the differences with the key frame. [More detailed explanation](https://blog.video.ibm.com/streaming-video-tips/keyframes-interframe-video-compression/). Higher resolutions and frame rates mean more processing power is needed to decode the video stream, so try and set them on the camera to avoid unnecessary decoding work.

docs/docs/index.md

@@ -20,6 +20,6 @@ Use of a [Google Coral Accelerator](https://coral.ai/products/) is optional, but
 
 ## Screenshots
 
-![Media Browser](/img/media_browser.png)
+![Media Browser](/img/media_browser-min.png)
 
-![Notification](/img/notification.png)
+![Notification](/img/notification-min.png)

docs/docs/installation.md

@@ -13,17 +13,72 @@ Frigate is a Docker container that can be run on any Docker host including as a
 
 ### Operating System
 
-Frigate runs best with docker installed on bare metal debian-based distributions. For ideal performance, Frigate needs access to underlying hardware for the Coral and GPU devices. Running Frigate in a VM on top of Proxmox, ESXi, Virtualbox, etc. is not recommended. The virtualization layer often introduces a sizable amount of overhead for communication with Coral devices.
+Frigate runs best with docker installed on bare metal debian-based distributions. For ideal performance, Frigate needs access to underlying hardware for the Coral and GPU devices. Running Frigate in a VM on top of Proxmox, ESXi, Virtualbox, etc. is not recommended. The virtualization layer often introduces a sizable amount of overhead for communication with Coral devices, but [not in all circumstances](https://github.com/blakeblackshear/frigate/discussions/1837).
 
 Windows is not officially supported, but some users have had success getting it to run under WSL or Virtualbox. Getting the GPU and/or Coral devices properly passed to Frigate may be difficult or impossible. Search previous discussions or issues for help.
 
+### Storage
+
+Frigate uses the following locations for read/write operations in the container. Docker volume mappings can be used to map these to any location on your host machine.
+
+- `/media/frigate/clips`: Used for snapshot storage. In the future, it will likely be renamed from `clips` to `snapshots`. The file structure here cannot be modified and isn't intended to be browsed or managed manually.
+- `/media/frigate/recordings`: Internal system storage for recording segments. The file structure here cannot be modified and isn't intended to be browsed or managed manually.
+- `/media/frigate/frigate.db`: Default location for the sqlite database. You will also see several files alongside this file while frigate is running. If moving the database location (often needed when using a network drive at `/media/frigate`), it is recommended to mount a volume with docker at `/db` and change the storage location of the database to `/db/frigate.db` in the config file.
+- `/tmp/cache`: Cache location for recording segments. Initial recordings are written here before being checked and converted to mp4 and moved to the recordings folder.
+- `/dev/shm`: It is not recommended to modify this directory or map it with docker. This is the location for raw decoded frames in shared memory and it's size is impacted by the `shm-size` calculations below.
+- `/config/config.yml`: Default location of the config file.
+
+#### Common docker compose storage configurations
+
+Writing to a local disk or external USB drive:
+
+```yaml
+version: "3.9"
+services:
+  frigate:
+    ...
+    volumes:
+      - /path/to/your/config.yml:/config/config.yml:ro
+      - /path/to/your/storage:/media/frigate
+      - type: tmpfs # Optional: 1GB of memory, reduces SSD/SD Card wear
+        target: /tmp/cache
+        tmpfs:
+          size: 1000000000
+    ...
+```
+
+Writing to a network drive with database on a local drive:
+
+```yaml
+version: "3.9"
+services:
+  frigate:
+    ...
+    volumes:
+      - /path/to/your/config.yml:/config/config.yml:ro
+      - /path/to/network/storage:/media/frigate
+      - /path/to/local/disk:/db
+      - type: tmpfs # Optional: 1GB of memory, reduces SSD/SD Card wear
+        target: /tmp/cache
+        tmpfs:
+          size: 1000000000
+    ...
+```
+
+frigate.yml
+
+```yaml
+database:
+  path: /db/frigate.db
+```
+
 ### Calculating required shm-size
 
 Frigate utilizes shared memory to store frames during processing. The default `shm-size` provided by Docker is 64m.
 
 The default shm-size of 64m is fine for setups with 2 or less 1080p cameras. If frigate is exiting with "Bus error" messages, it is likely because you have too many high resolution cameras and you need to specify a higher shm size.
 
-You can calculate the necessary shm-size for each camera with the following formula:
+You can calculate the necessary shm-size for each camera with the following formula using the resolution specified for detect:
 
 ```
 (width * height * 1.5 * 9 + 270480)/1048576 = <shm size in mb>
@@ -35,7 +90,7 @@ The shm size cannot be set per container for Home Assistant Addons. You must set
 
 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 [this](https://amzn.to/2XTEqp7) (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 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).
 
 ## Docker
 
@@ -102,7 +157,7 @@ docker run -d \
 
 :::caution
 
-Due to limitations in Home Assistant Operating System, Frigate cannot utilize external storage for recordings or snapshots.
+Due to limitations in Home Assistant Operating System, utilizing external storage for recordings or snapshots requires [modifying udev rules manually](https://community.home-assistant.io/t/solved-mount-usb-drive-in-hassio-to-be-used-on-the-media-folder-with-udev-customization/258406/46).
 
 :::
 

docs/docusaurus.config.js

@@ -29,6 +29,16 @@ module.exports = {
           label: 'Docs',
           position: 'left',
         },
+        {
+          href: 'https://frigate.video',
+          label: 'Website',
+          position: 'right',
+        },
+        {
+          href: 'https://demo.frigate.video',
+          label: 'Demo',
+          position: 'right',
+        },
         {
           href: 'https://github.com/blakeblackshear/frigate',
           label: 'GitHub',

docs/package-lock.json

@@ -2469,31 +2469,11 @@
       "integrity": "sha1-l6ERlkmyEa0zaR2fn0hqjsn74KM="
     },
     "ansi-align": {
-      "version": "3.0.0",
-      "resolved": "https://registry.npmjs.org/ansi-align/-/ansi-align-3.0.0.tgz",
-      "integrity": "sha512-ZpClVKqXN3RGBmKibdfWzqCY4lnjEuoNzU5T0oEFpfd/z5qJHVarukridD4juLO2FXMiwUQxr9WqQtaYa8XRYw==",
+      "version": "3.0.1",
+      "resolved": "https://registry.npmjs.org/ansi-align/-/ansi-align-3.0.1.tgz",
+      "integrity": "sha512-IOfwwBF5iczOjp/WeY4YxyjqAFMQoZufdQWDd19SEExbVLNXqvpzSJ/M7Za4/sCPmQ0+GRquoA7bGcINcxew6w==",
       "requires": {
-        "string-width": "^3.0.0"
-      },
-      "dependencies": {
-        "string-width": {
-          "version": "3.1.0",
-          "resolved": "https://registry.npmjs.org/string-width/-/string-width-3.1.0.tgz",
-          "integrity": "sha512-vafcv6KjVZKSgz06oM/H6GDBrAtz8vdhQakGjFIvNrHA6y3HCF1CInLy+QLq8dTJPQ1b+KDUqDFctkdRW44e1w==",
-          "requires": {
-            "emoji-regex": "^7.0.1",
-            "is-fullwidth-code-point": "^2.0.0",
-            "strip-ansi": "^5.1.0"
-          }
-        },
-        "strip-ansi": {
-          "version": "5.2.0",
-          "resolved": "https://registry.npmjs.org/strip-ansi/-/strip-ansi-5.2.0.tgz",
-          "integrity": "sha512-DuRs1gKbBqsMKIZlrffwlug8MHkcnpjs5VPmL1PAh+mA30U0DTotfDZ0d2UUsXpPmPmMMJ6W773MaA3J+lbiWA==",
-          "requires": {
-            "ansi-regex": "^4.1.0"
-          }
-        }
+        "string-width": "^4.1.0"
       }
     },
     "ansi-colors": {
@@ -2902,15 +2882,15 @@
       "integrity": "sha1-aN/1++YMUes3cl6p4+0xDcwed24="
     },
     "boxen": {
-      "version": "5.0.1",
-      "resolved": "https://registry.npmjs.org/boxen/-/boxen-5.0.1.tgz",
-      "integrity": "sha512-49VBlw+PrWEF51aCmy7QIteYPIFZxSpvqBdP/2itCPPlJ49kj9zg/XPRFrdkne2W+CfwXUls8exMvu1RysZpKA==",
+      "version": "5.1.2",
+      "resolved": "https://registry.npmjs.org/boxen/-/boxen-5.1.2.tgz",
+      "integrity": "sha512-9gYgQKXx+1nP8mP7CzFyaUARhg7D3n1dF/FnErWmu9l6JvGpNUN278h0aSb+QjoiKSWG+iZ3uHrcqk0qrY9RQQ==",
       "requires": {
         "ansi-align": "^3.0.0",
         "camelcase": "^6.2.0",
         "chalk": "^4.1.0",
         "cli-boxes": "^2.2.1",
-        "string-width": "^4.2.0",
+        "string-width": "^4.2.2",
         "type-fest": "^0.20.2",
         "widest-line": "^3.1.0",
         "wrap-ansi": "^7.0.0"
@@ -6826,9 +6806,9 @@
       "integrity": "sha1-y480xTIT2JVyP8urkH6UIq28r7E="
     },
     "nth-check": {
-      "version": "2.0.0",
-      "resolved": "https://registry.npmjs.org/nth-check/-/nth-check-2.0.0.tgz",
-      "integrity": "sha512-i4sc/Kj8htBrAiH1viZ0TgU8Y5XqCaV/FziYK6TBczxmeKm3AEFWqqF3195yKudrarqy7Zu80Ra5dobFjn9X/Q==",
+      "version": "2.0.1",
+      "resolved": "https://registry.npmjs.org/nth-check/-/nth-check-2.0.1.tgz",
+      "integrity": "sha512-it1vE95zF6dTT9lBsYbxvqh0Soy4SPowchj0UBGj/V6cTPnXXtQOPUbhZ6CmGzAD/rW22LQK6E96pcdJXk4A4w==",
       "requires": {
         "boolbase": "^1.0.0"
       }
@@ -7650,9 +7630,9 @@
       "integrity": "sha512-w23ch4f75V1Tnz8DajsYKvY5lF7H1+WvzvLUcF0paFxkTHSp42RS0H5CttdN2Q8RR3DRGZ9v5xD/h3n8C8kGmg=="
     },
     "prismjs": {
-      "version": "1.24.1",
-      "resolved": "https://registry.npmjs.org/prismjs/-/prismjs-1.24.1.tgz",
-      "integrity": "sha512-mNPsedLuk90RVJioIky8ANZEwYm5w9LcvCXrxHlwf4fNVSn8jEipMybMkWUyyF0JhnC+C4VcOVSBuHRKs1L5Ow=="
+      "version": "1.25.0",
+      "resolved": "https://registry.npmjs.org/prismjs/-/prismjs-1.25.0.tgz",
+      "integrity": "sha512-WCjJHl1KEWbnkQom1+SzftbtXMKQoezOCYs5rECqMN+jP+apI7ftoflyqigqzopSO3hMhTEb0mFClA8lkolgEg=="
     },
     "process-nextick-args": {
       "version": "2.0.1",
@@ -9397,9 +9377,9 @@
       },
       "dependencies": {
         "ansi-regex": {
-          "version": "5.0.0",
-          "resolved": "https://registry.npmjs.org/ansi-regex/-/ansi-regex-5.0.0.tgz",
-          "integrity": "sha512-bY6fj56OUQ0hU1KjFNDQuJFezqKdrAyFdIevADiqrWHwSlbmBNMHp5ak2f40Pm8JTFyM2mqxkG6ngkHO11f/lg=="
+          "version": "5.0.1",
+          "resolved": "https://registry.npmjs.org/ansi-regex/-/ansi-regex-5.0.1.tgz",
+          "integrity": "sha512-quJQXlTSUGL2LH9SUXo8VwsY4soanhgo6LNSm84E1LBcE8s3O0wpdiRzyR9z/ZZJMlMWv37qOOb9pdJlMUEKFQ=="
         }
       }
     },

docs/package.json

@@ -12,8 +12,8 @@
     "clear": "docusaurus clear"
   },
   "dependencies": {
-    "@docusaurus/core": "^2.0.0-beta.ff31de0ff",
-    "@docusaurus/preset-classic": "^2.0.0-beta.ff31de0ff",
+    "@docusaurus/core": "^2.0.0-beta.6",
+    "@docusaurus/preset-classic": "^2.0.0-beta.6",
     "@mdx-js/react": "^1.6.21",
     "clsx": "^1.1.1",
     "raw-loader": "^4.0.2",

frigate/app.py

@@ -12,6 +12,7 @@ import yaml
 from peewee_migrate import Router
 from playhouse.sqlite_ext import SqliteExtDatabase
 from playhouse.sqliteq import SqliteQueueDatabase
+from pydantic import ValidationError
 
 from frigate.config import DetectorTypeEnum, FrigateConfig
 from frigate.const import CACHE_DIR, CLIPS_DIR, RECORD_DIR
@@ -66,10 +67,19 @@ class FrigateApp:
 
     def init_config(self):
         config_file = os.environ.get("CONFIG_FILE", "/config/config.yml")
+
+        # Check if we can use .yaml instead of .yml
+        config_file_yaml = config_file.replace(".yml", ".yaml")
+        if os.path.isfile(config_file_yaml):
+            config_file = config_file_yaml
+
         user_config = FrigateConfig.parse_file(config_file)
         self.config = user_config.runtime_config
 
         for camera_name in self.config.cameras.keys():
+            # generage the ffmpeg commands
+            self.config.cameras[camera_name].create_ffmpeg_cmds()
+
             # create camera_metrics
             self.camera_metrics[camera_name] = {
                 "camera_fps": mp.Value("d", 0.0),
@@ -85,29 +95,6 @@ class FrigateApp:
                 "frame_queue": mp.Queue(maxsize=2),
             }
 
-    def check_config(self):
-        for name, camera in self.config.cameras.items():
-            assigned_roles = list(
-                set([r for i in camera.ffmpeg.inputs for r in i.roles])
-            )
-            if not camera.record.enabled and "record" in assigned_roles:
-                logger.warning(
-                    f"Camera {name} has record assigned to an input, but record is not enabled."
-                )
-            elif camera.record.enabled and not "record" in assigned_roles:
-                logger.warning(
-                    f"Camera {name} has record enabled, but record is not assigned to an input."
-                )
-
-            if not camera.rtmp.enabled and "rtmp" in assigned_roles:
-                logger.warning(
-                    f"Camera {name} has rtmp assigned to an input, but rtmp is not enabled."
-                )
-            elif camera.rtmp.enabled and not "rtmp" in assigned_roles:
-                logger.warning(
-                    f"Camera {name} has rtmp enabled, but rtmp is not assigned to an input."
-                )
-
     def set_log_levels(self):
         logging.getLogger().setLevel(self.config.logger.default.value.upper())
         for log, level in self.config.logger.logs.items():
@@ -127,6 +114,9 @@ class FrigateApp:
             maxsize=len(self.config.cameras.keys()) * 2
         )
 
+        # Queue for recordings info
+        self.recordings_info_queue = mp.Queue()
+
     def init_database(self):
         # Migrate DB location
         old_db_path = os.path.join(CLIPS_DIR, "frigate.db")
@@ -225,6 +215,7 @@ class FrigateApp:
             self.event_queue,
             self.event_processed_queue,
             self.video_output_queue,
+            self.recordings_info_queue,
             self.stop_event,
         )
         self.detected_frames_processor.start()
@@ -292,7 +283,9 @@ class FrigateApp:
         self.event_cleanup.start()
 
     def start_recording_maintainer(self):
-        self.recording_maintainer = RecordingMaintainer(self.config, self.stop_event)
+        self.recording_maintainer = RecordingMaintainer(
+            self.config, self.recordings_info_queue, self.stop_event
+        )
         self.recording_maintainer.start()
 
     def start_recording_cleanup(self):
@@ -320,12 +313,23 @@ class FrigateApp:
             try:
                 self.init_config()
             except Exception as e:
-                print(f"Error parsing config: {e}")
+                print("*************************************************************")
+                print("*************************************************************")
+                print("***    Your config file is not valid!                     ***")
+                print("***    Please check the docs at                           ***")
+                print("***    https://docs.frigate.video/configuration/index     ***")
+                print("*************************************************************")
+                print("*************************************************************")
+                print("***    Config Validation Errors                           ***")
+                print("*************************************************************")
+                print(e)
+                print("*************************************************************")
+                print("***    End Config Validation Errors                       ***")
+                print("*************************************************************")
                 self.log_process.terminate()
                 sys.exit(1)
             self.set_environment_vars()
             self.ensure_dirs()
-            self.check_config()
             self.set_log_levels()
             self.init_queues()
             self.init_database()

frigate/config.py

@@ -12,7 +12,7 @@ import yaml
 from pydantic import BaseModel, Extra, Field, validator
 from pydantic.fields import PrivateAttr
 
-from frigate.const import BASE_DIR, CACHE_DIR, RECORD_DIR
+from frigate.const import BASE_DIR, CACHE_DIR, YAML_EXT
 from frigate.edgetpu import load_labels
 from frigate.util import create_mask, deep_merge
 
@@ -65,8 +65,17 @@ class MqttConfig(FrigateBaseModel):
         return v
 
 
+class RetainModeEnum(str, Enum):
+    all = "all"
+    motion = "motion"
+    active_objects = "active_objects"
+
+
 class RetainConfig(FrigateBaseModel):
     default: float = Field(default=10, title="Default retention period.")
+    mode: RetainModeEnum = Field(
+        default=RetainModeEnum.active_objects, title="Retain mode."
+    )
     objects: Dict[str, float] = Field(
         default_factory=dict, title="Object retention period."
     )
@@ -88,9 +97,18 @@ class EventsConfig(FrigateBaseModel):
     )
 
 
+class RecordRetainConfig(FrigateBaseModel):
+    days: float = Field(default=0, title="Default retention period.")
+    mode: RetainModeEnum = Field(default=RetainModeEnum.all, title="Retain mode.")
+
+
 class RecordConfig(FrigateBaseModel):
     enabled: bool = Field(default=False, title="Enable record on all cameras.")
-    retain_days: float = Field(default=0, title="Recording retention period in days.")
+    # deprecated - to be removed in a future version
+    retain_days: Optional[float] = Field(title="Recording retention period in days.")
+    retain: RecordRetainConfig = Field(
+        default_factory=RecordRetainConfig, title="Record retention settings."
+    )
     events: EventsConfig = Field(
         default_factory=EventsConfig, title="Event specific settings."
     )
@@ -103,10 +121,10 @@ class MotionConfig(FrigateBaseModel):
         ge=1,
         le=255,
     )
-    contour_area: Optional[int] = Field(title="Contour Area")
+    contour_area: Optional[int] = Field(default=30, title="Contour Area")
     delta_alpha: float = Field(default=0.2, title="Delta Alpha")
     frame_alpha: float = Field(default=0.2, title="Frame Alpha")
-    frame_height: Optional[int] = Field(title="Frame Height")
+    frame_height: Optional[int] = Field(default=50, title="Frame Height")
     mask: Union[str, List[str]] = Field(
         default="", title="Coordinates polygon for the motion mask."
     )
@@ -119,15 +137,6 @@ class RuntimeMotionConfig(MotionConfig):
     def __init__(self, **config):
         frame_shape = config.get("frame_shape", (1, 1))
 
-        if "frame_height" not in config:
-            config["frame_height"] = max(frame_shape[0] // 6, 180)
-
-        if "contour_area" not in config:
-            frame_width = frame_shape[1] * config["frame_height"] / frame_shape[0]
-            config["contour_area"] = (
-                config["frame_height"] * frame_width * 0.00173611111
-            )
-
         mask = config.get("mask", "")
         config["raw_mask"] = mask
 
@@ -162,6 +171,10 @@ class DetectConfig(FrigateBaseModel):
     max_disappeared: Optional[int] = Field(
         title="Maximum number of frames the object can dissapear before detection ends."
     )
+    stationary_interval: Optional[int] = Field(
+        title="Frame interval for checking stationary objects.",
+        ge=1,
+    )
 
 
 class FilterConfig(FrigateBaseModel):
@@ -495,6 +508,7 @@ class CameraConfig(FrigateBaseModel):
     timestamp_style: TimestampStyleConfig = Field(
         default_factory=TimestampStyleConfig, title="Timestamp style configuration."
     )
+    _ffmpeg_cmds: List[Dict[str, List[str]]] = PrivateAttr()
 
     def __init__(self, **config):
         # Set zone colors
@@ -505,6 +519,10 @@ class CameraConfig(FrigateBaseModel):
                 for idx, (name, z) in enumerate(config["zones"].items())
             }
 
+        # add roles to the input if there is only one
+        if len(config["ffmpeg"]["inputs"]) == 1:
+            config["ffmpeg"]["inputs"][0]["roles"] = ["record", "rtmp", "detect"]
+
         super().__init__(**config)
 
     @property
@@ -517,6 +535,9 @@ class CameraConfig(FrigateBaseModel):
 
     @property
     def ffmpeg_cmds(self) -> List[Dict[str, List[str]]]:
+        return self._ffmpeg_cmds
+
+    def create_ffmpeg_cmds(self):
         ffmpeg_cmds = []
         for ffmpeg_input in self.ffmpeg.inputs:
             ffmpeg_cmd = self._get_ffmpeg_cmd(ffmpeg_input)
@@ -524,7 +545,7 @@ class CameraConfig(FrigateBaseModel):
                 continue
 
             ffmpeg_cmds.append({"roles": ffmpeg_input.roles, "cmd": ffmpeg_cmd})
-        return ffmpeg_cmds
+        self._ffmpeg_cmds = ffmpeg_cmds
 
     def _get_ffmpeg_cmd(self, ffmpeg_input: CameraInput):
         ffmpeg_output_args = []
@@ -560,6 +581,7 @@ class CameraConfig(FrigateBaseModel):
                 if isinstance(self.ffmpeg.output_args.record, list)
                 else self.ffmpeg.output_args.record.split(" ")
             )
+
             ffmpeg_output_args = (
                 record_args
                 + [f"{os.path.join(CACHE_DIR, self.name)}-%Y%m%d%H%M%S.mp4"]
@@ -740,6 +762,11 @@ class FrigateConfig(FrigateBaseModel):
             if camera_config.detect.max_disappeared is None:
                 camera_config.detect.max_disappeared = max_disappeared
 
+            # Default stationary_interval configuration
+            stationary_interval = camera_config.detect.fps * 10
+            if camera_config.detect.stationary_interval is None:
+                camera_config.detect.stationary_interval = stationary_interval
+
             # FFMPEG input substitution
             for input in camera_config.ffmpeg.inputs:
                 input.path = input.path.format(**FRIGATE_ENV_VARS)
@@ -787,6 +814,39 @@ class FrigateConfig(FrigateBaseModel):
                     **camera_config.motion.dict(exclude_unset=True),
                 )
 
+            # check runtime config
+            assigned_roles = list(
+                set([r for i in camera_config.ffmpeg.inputs for r in i.roles])
+            )
+            if camera_config.record.enabled and not "record" in assigned_roles:
+                raise ValueError(
+                    f"Camera {name} has record enabled, but record is not assigned to an input."
+                )
+
+            if camera_config.rtmp.enabled and not "rtmp" in assigned_roles:
+                raise ValueError(
+                    f"Camera {name} has rtmp enabled, but rtmp is not assigned to an input."
+                )
+
+            # backwards compatibility for retain_days
+            if not camera_config.record.retain_days is None:
+                logger.warning(
+                    "The 'retain_days' config option has been DEPRECATED and will be removed in a future version. Please use the 'days' setting under 'retain'"
+                )
+                if camera_config.record.retain.days == 0:
+                    camera_config.record.retain.days = camera_config.record.retain_days
+
+            # warning if the higher level record mode is potentially more restrictive than the events
+            if (
+                camera_config.record.retain.days != 0
+                and camera_config.record.retain.mode != RetainModeEnum.all
+                and camera_config.record.events.retain.mode
+                != camera_config.record.retain.mode
+            ):
+                logger.warning(
+                    f"Recording retention is configured for {camera_config.record.retain.mode} and event retention is configured for {camera_config.record.events.retain.mode}. The more restrictive retention policy will be applied."
+                )
+
             config.cameras[name] = camera_config
 
         return config
@@ -804,7 +864,7 @@ class FrigateConfig(FrigateBaseModel):
         with open(config_file) as f:
             raw_config = f.read()
 
-        if config_file.endswith(".yml"):
+        if config_file.endswith(YAML_EXT):
             config = yaml.safe_load(raw_config)
         elif config_file.endswith(".json"):
             config = json.loads(raw_config)

frigate/const.py

@@ -2,3 +2,4 @@ BASE_DIR = "/media/frigate"
 CLIPS_DIR = f"{BASE_DIR}/clips"
 RECORD_DIR = f"{BASE_DIR}/recordings"
 CACHE_DIR = "/tmp/cache"
+YAML_EXT = (".yaml", ".yml")

frigate/events.py

@@ -30,6 +30,11 @@ class EventProcessor(threading.Thread):
         self.stop_event = stop_event
 
     def run(self):
+        # set an end_time on events without an end_time on startup
+        Event.update(end_time=Event.start_time + 30).where(
+            Event.end_time == None
+        ).execute()
+
         while not self.stop_event.is_set():
             try:
                 event_type, camera, event_data = self.event_queue.get(timeout=10)
@@ -38,14 +43,35 @@ class EventProcessor(threading.Thread):
 
             logger.debug(f"Event received: {event_type} {camera} {event_data['id']}")
 
+            event_config: EventsConfig = self.config.cameras[camera].record.events
+
             if event_type == "start":
                 self.events_in_process[event_data["id"]] = event_data
 
-            if event_type == "end":
-                event_config: EventsConfig = self.config.cameras[camera].record.events
-
+            elif event_type == "update":
+                self.events_in_process[event_data["id"]] = event_data
+                # TODO: this will generate a lot of db activity possibly
                 if event_data["has_clip"] or event_data["has_snapshot"]:
-                    Event.create(
+                    Event.replace(
+                        id=event_data["id"],
+                        label=event_data["label"],
+                        camera=camera,
+                        start_time=event_data["start_time"] - event_config.pre_capture,
+                        end_time=None,
+                        top_score=event_data["top_score"],
+                        false_positive=event_data["false_positive"],
+                        zones=list(event_data["entered_zones"]),
+                        thumbnail=event_data["thumbnail"],
+                        region=event_data["region"],
+                        box=event_data["box"],
+                        area=event_data["area"],
+                        has_clip=event_data["has_clip"],
+                        has_snapshot=event_data["has_snapshot"],
+                    ).execute()
+
+            elif event_type == "end":
+                if event_data["has_clip"] or event_data["has_snapshot"]:
+                    Event.replace(
                         id=event_data["id"],
                         label=event_data["label"],
                         camera=camera,
@@ -60,11 +86,15 @@ class EventProcessor(threading.Thread):
                         area=event_data["area"],
                         has_clip=event_data["has_clip"],
                         has_snapshot=event_data["has_snapshot"],
-                    )
+                    ).execute()
 
                 del self.events_in_process[event_data["id"]]
                 self.event_processed_queue.put((event_data["id"], camera))
 
+        # set an end_time on events without an end_time before exiting
+        Event.update(end_time=datetime.datetime.now().timestamp()).where(
+            Event.end_time == None
+        ).execute()
         logger.info(f"Exiting event processor...")
 
 
@@ -192,12 +222,12 @@ class EventCleanup(threading.Thread):
         for event in duplicate_events:
             logger.debug(f"Removing duplicate: {event.id}")
             media_name = f"{event.camera}-{event.id}"
-            if event.has_snapshot:
-                media_path = Path(f"{os.path.join(CLIPS_DIR, media_name)}.jpg")
-                media_path.unlink(missing_ok=True)
-            if event.has_clip:
-                media_path = Path(f"{os.path.join(CLIPS_DIR, media_name)}.mp4")
-                media_path.unlink(missing_ok=True)
+            media_path = Path(f"{os.path.join(CLIPS_DIR, media_name)}.jpg")
+            media_path.unlink(missing_ok=True)
+            media_path = Path(f"{os.path.join(CLIPS_DIR, media_name)}-clean.png")
+            media_path.unlink(missing_ok=True)
+            media_path = Path(f"{os.path.join(CLIPS_DIR, media_name)}.mp4")
+            media_path.unlink(missing_ok=True)
 
         (
             Event.delete()

frigate/http.py

@@ -1,6 +1,7 @@
 import base64
 from collections import OrderedDict
 from datetime import datetime, timedelta
+import copy
 import json
 import glob
 import logging
@@ -190,7 +191,7 @@ def event_snapshot(id):
     download = request.args.get("download", type=bool)
     jpg_bytes = None
     try:
-        event = Event.get(Event.id == id)
+        event = Event.get(Event.id == id, Event.end_time != None)
         if not event.has_snapshot:
             return "Snapshot not available", 404
         # read snapshot from disk
@@ -321,7 +322,7 @@ def config():
     # add in the ffmpeg_cmds
     for camera_name, camera in current_app.frigate_config.cameras.items():
         camera_dict = config["cameras"][camera_name]
-        camera_dict["ffmpeg_cmds"] = camera.ffmpeg_cmds
+        camera_dict["ffmpeg_cmds"] = copy.deepcopy(camera.ffmpeg_cmds)
         for cmd in camera_dict["ffmpeg_cmds"]:
             cmd["cmd"] = " ".join(cmd["cmd"])
 
@@ -657,10 +658,15 @@ def vod_ts(camera, start_ts, end_ts):
         # Determine if we need to end the last clip early
         if recording.end_time > end_ts:
             duration -= int((recording.end_time - end_ts) * 1000)
-        clips.append(clip)
-        durations.append(duration)
+
+        if duration > 0:
+            clips.append(clip)
+            durations.append(duration)
+        else:
+            logger.warning(f"Recording clip is missing or empty: {recording.path}")
 
     if not clips:
+        logger.error("No recordings found for the requested time range")
         return "No recordings found.", 404
 
     hour_ago = datetime.now() - timedelta(hours=1)
@@ -689,15 +695,20 @@ def vod_event(id):
     try:
         event: Event = Event.get(Event.id == id)
     except DoesNotExist:
+        logger.error(f"Event not found: {id}")
         return "Event not found.", 404
 
     if not event.has_clip:
-        return "Clip not available", 404
+        logger.error(f"Event does not have recordings: {id}")
+        return "Recordings not available", 404
 
     clip_path = os.path.join(CLIPS_DIR, f"{event.camera}-{id}.mp4")
 
     if not os.path.isfile(clip_path):
-        return vod_ts(event.camera, event.start_time, event.end_time)
+        end_ts = (
+            datetime.now().timestamp() if event.end_time is None else event.end_time
+        )
+        return vod_ts(event.camera, event.start_time, end_ts)
 
     duration = int((event.end_time - event.start_time) * 1000)
     return jsonify(

frigate/models.py

@@ -27,3 +27,5 @@ class Recordings(Model):
     start_time = DateTimeField()
     end_time = DateTimeField()
     duration = FloatField()
+    motion = IntegerField(null=True)
+    objects = IntegerField(null=True)

frigate/motion.py

@@ -23,6 +23,7 @@ class MotionDetector:
             interpolation=cv2.INTER_LINEAR,
         )
         self.mask = np.where(resized_mask == [0])
+        self.save_images = False
 
     def detect(self, frame):
         motion_boxes = []
@@ -36,10 +37,15 @@ class MotionDetector:
             interpolation=cv2.INTER_LINEAR,
         )
 
-        # TODO: can I improve the contrast of the grayscale image here?
-
-        # convert to grayscale
-        # resized_frame = cv2.cvtColor(resized_frame, cv2.COLOR_BGR2GRAY)
+        # Improve contrast
+        minval = np.percentile(resized_frame, 4)
+        maxval = np.percentile(resized_frame, 96)
+        # don't adjust if the image is a single color
+        if minval < maxval:
+            resized_frame = np.clip(resized_frame, minval, maxval)
+            resized_frame = (
+                ((resized_frame - minval) / (maxval - minval)) * 255
+            ).astype(np.uint8)
 
         # mask frame
         resized_frame[self.mask] = [255]
@@ -49,6 +55,8 @@ class MotionDetector:
         if self.frame_counter < 30:
             self.frame_counter += 1
         else:
+            if self.save_images:
+                self.frame_counter += 1
             # compare to average
             frameDelta = cv2.absdiff(resized_frame, cv2.convertScaleAbs(self.avg_frame))
 
@@ -58,7 +66,6 @@ class MotionDetector:
             cv2.accumulateWeighted(frameDelta, self.avg_delta, self.config.delta_alpha)
 
             # compute the threshold image for the current frame
-            # TODO: threshold
             current_thresh = cv2.threshold(
                 frameDelta, self.config.threshold, 255, cv2.THRESH_BINARY
             )[1]
@@ -75,8 +82,10 @@ class MotionDetector:
 
             # dilate the thresholded image to fill in holes, then find contours
             # on thresholded image
-            thresh = cv2.dilate(thresh, None, iterations=2)
-            cnts = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+            thresh_dilated = cv2.dilate(thresh, None, iterations=2)
+            cnts = cv2.findContours(
+                thresh_dilated, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE
+            )
             cnts = imutils.grab_contours(cnts)
 
             # loop over the contours
@@ -94,6 +103,35 @@ class MotionDetector:
                         )
                     )
 
+            if self.save_images:
+                thresh_dilated = cv2.cvtColor(thresh_dilated, cv2.COLOR_GRAY2BGR)
+                # print("--------")
+                # print(self.frame_counter)
+                for c in cnts:
+                    contour_area = cv2.contourArea(c)
+                    # print(contour_area)
+                    if contour_area > self.config.contour_area:
+                        x, y, w, h = cv2.boundingRect(c)
+                        cv2.rectangle(
+                            thresh_dilated,
+                            (x, y),
+                            (x + w, y + h),
+                            (0, 0, 255),
+                            2,
+                        )
+                # print("--------")
+                image_row_1 = cv2.hconcat(
+                    [
+                        cv2.cvtColor(frameDelta, cv2.COLOR_GRAY2BGR),
+                        cv2.cvtColor(avg_delta_image, cv2.COLOR_GRAY2BGR),
+                    ]
+                )
+                image_row_2 = cv2.hconcat(
+                    [cv2.cvtColor(thresh, cv2.COLOR_GRAY2BGR), thresh_dilated]
+                )
+                combined_image = cv2.vconcat([image_row_1, image_row_2])
+                cv2.imwrite(f"motion/motion-{self.frame_counter}.jpg", combined_image)
+
         if len(motion_boxes) > 0:
             self.motion_frame_count += 1
             if self.motion_frame_count >= 10:

frigate/object_processing.py

@@ -71,7 +71,7 @@ class TrackedObject:
         self.camera_config = camera_config
         self.frame_cache = frame_cache
         self.current_zones = []
-        self.entered_zones = set()
+        self.entered_zones = []
         self.false_positive = True
         self.has_clip = False
         self.has_snapshot = False
@@ -147,7 +147,8 @@ class TrackedObject:
                 # if the object passed the filters once, dont apply again
                 if name in self.current_zones or not zone_filtered(self, zone.filters):
                     current_zones.append(name)
-                    self.entered_zones.add(name)
+                    if name not in self.entered_zones:
+                        self.entered_zones.append(name)
 
         # if the zones changed, signal an update
         if not self.false_positive and set(self.current_zones) != set(current_zones):
@@ -176,8 +177,9 @@ class TrackedObject:
             "box": self.obj_data["box"],
             "area": self.obj_data["area"],
             "region": self.obj_data["region"],
+            "motionless_count": self.obj_data["motionless_count"],
             "current_zones": self.current_zones.copy(),
-            "entered_zones": list(self.entered_zones).copy(),
+            "entered_zones": self.entered_zones.copy(),
             "has_clip": self.has_clip,
             "has_snapshot": self.has_snapshot,
         }
@@ -584,6 +586,7 @@ class TrackedObjectProcessor(threading.Thread):
         event_queue,
         event_processed_queue,
         video_output_queue,
+        recordings_info_queue,
         stop_event,
     ):
         threading.Thread.__init__(self)
@@ -595,6 +598,7 @@ class TrackedObjectProcessor(threading.Thread):
         self.event_queue = event_queue
         self.event_processed_queue = event_processed_queue
         self.video_output_queue = video_output_queue
+        self.recordings_info_queue = recordings_info_queue
         self.stop_event = stop_event
         self.camera_states: Dict[str, CameraState] = {}
         self.frame_manager = SharedMemoryFrameManager()
@@ -603,6 +607,8 @@ class TrackedObjectProcessor(threading.Thread):
             self.event_queue.put(("start", camera, obj.to_dict()))
 
         def update(camera, obj: TrackedObject, current_frame_time):
+            obj.has_snapshot = self.should_save_snapshot(camera, obj)
+            obj.has_clip = self.should_retain_recording(camera, obj)
             after = obj.to_dict()
             message = {
                 "before": obj.previous,
@@ -613,6 +619,9 @@ class TrackedObjectProcessor(threading.Thread):
                 f"{self.topic_prefix}/events", json.dumps(message), retain=False
             )
             obj.previous = after
+            self.event_queue.put(
+                ("update", camera, obj.to_dict(include_thumbnail=True))
+            )
 
         def end(camera, obj: TrackedObject, current_frame_time):
             # populate has_snapshot
@@ -724,7 +733,7 @@ class TrackedObjectProcessor(threading.Thread):
 
         # if there are required zones and there is no overlap
         required_zones = snapshot_config.required_zones
-        if len(required_zones) > 0 and not obj.entered_zones & set(required_zones):
+        if len(required_zones) > 0 and not set(obj.entered_zones) & set(required_zones):
             logger.debug(
                 f"Not creating snapshot for {obj.obj_data['id']} because it did not enter required zones"
             )
@@ -765,7 +774,7 @@ class TrackedObjectProcessor(threading.Thread):
     def should_mqtt_snapshot(self, camera, obj: TrackedObject):
         # if there are required zones and there is no overlap
         required_zones = self.config.cameras[camera].mqtt.required_zones
-        if len(required_zones) > 0 and not obj.entered_zones & set(required_zones):
+        if len(required_zones) > 0 and not set(obj.entered_zones) & set(required_zones):
             logger.debug(
                 f"Not sending mqtt for {obj.obj_data['id']} because it did not enter required zones"
             )
@@ -808,11 +817,26 @@ class TrackedObjectProcessor(threading.Thread):
                 frame_time, current_tracked_objects, motion_boxes, regions
             )
 
+            tracked_objects = [
+                o.to_dict() for o in camera_state.tracked_objects.values()
+            ]
+
             self.video_output_queue.put(
                 (
                     camera,
                     frame_time,
-                    current_tracked_objects,
+                    tracked_objects,
+                    motion_boxes,
+                    regions,
+                )
+            )
+
+            # send info on this frame to the recordings maintainer
+            self.recordings_info_queue.put(
+                (
+                    camera,
+                    frame_time,
+                    tracked_objects,
                     motion_boxes,
                     regions,
                 )

frigate/objects.py

@@ -13,7 +13,7 @@ import numpy as np
 from scipy.spatial import distance as dist
 
 from frigate.config import DetectConfig
-from frigate.util import draw_box_with_label
+from frigate.util import intersection_over_union
 
 
 class ObjectTracker:
@@ -27,6 +27,7 @@ class ObjectTracker:
         id = f"{obj['frame_time']}-{rand_id}"
         obj["id"] = id
         obj["start_time"] = obj["frame_time"]
+        obj["motionless_count"] = 0
         self.tracked_objects[id] = obj
         self.disappeared[id] = 0
 
@@ -36,6 +37,13 @@ class ObjectTracker:
 
     def update(self, id, new_obj):
         self.disappeared[id] = 0
+        if (
+            intersection_over_union(self.tracked_objects[id]["box"], new_obj["box"])
+            > 0.9
+        ):
+            self.tracked_objects[id]["motionless_count"] += 1
+        else:
+            self.tracked_objects[id]["motionless_count"] = 0
         self.tracked_objects[id].update(new_obj)
 
     def match_and_update(self, frame_time, new_objects):

frigate/output.py

@@ -104,7 +104,7 @@ class BirdsEyeFrameManager:
         self.blank_frame[0 : self.frame_shape[0], 0 : self.frame_shape[1]] = 16
 
         # find and copy the logo on the blank frame
-        logo_files = glob.glob("/opt/frigate/web/apple-touch-icon.*.png")
+        logo_files = glob.glob("/opt/frigate/frigate/birdseye.png")
         frigate_logo = None
         if len(logo_files) > 0:
             frigate_logo = cv2.imread(logo_files[0], cv2.IMREAD_UNCHANGED)

frigate/record.py

@@ -1,20 +1,25 @@
 import datetime
 import itertools
 import logging
+import multiprocessing as mp
 import os
+import queue
 import random
 import shutil
 import string
 import subprocess as sp
 import threading
+import time
+from collections import defaultdict
 from pathlib import Path
 
 import psutil
 from peewee import JOIN, DoesNotExist
 
-from frigate.config import FrigateConfig
+from frigate.config import RetainModeEnum, FrigateConfig
 from frigate.const import CACHE_DIR, RECORD_DIR
 from frigate.models import Event, Recordings
+from frigate.util import area
 
 logger = logging.getLogger(__name__)
 
@@ -38,20 +43,28 @@ def remove_empty_directories(directory):
 
 
 class RecordingMaintainer(threading.Thread):
-    def __init__(self, config: FrigateConfig, stop_event):
+    def __init__(
+        self, config: FrigateConfig, recordings_info_queue: mp.Queue, stop_event
+    ):
         threading.Thread.__init__(self)
         self.name = "recording_maint"
         self.config = config
+        self.recordings_info_queue = recordings_info_queue
         self.stop_event = stop_event
+        self.first_pass = True
+        self.recordings_info = defaultdict(list)
+        self.end_time_cache = {}
 
     def move_files(self):
-        recordings = [
-            d
-            for d in os.listdir(CACHE_DIR)
-            if os.path.isfile(os.path.join(CACHE_DIR, d))
-            and d.endswith(".mp4")
-            and not d.startswith("clip_")
-        ]
+        cache_files = sorted(
+            [
+                d
+                for d in os.listdir(CACHE_DIR)
+                if os.path.isfile(os.path.join(CACHE_DIR, d))
+                and d.endswith(".mp4")
+                and not d.startswith("clip_")
+            ]
+        )
 
         files_in_use = []
         for process in psutil.process_iter():
@@ -66,7 +79,9 @@ class RecordingMaintainer(threading.Thread):
             except:
                 continue
 
-        for f in recordings:
+        # group recordings by camera
+        grouped_recordings = defaultdict(list)
+        for f in cache_files:
             # Skip files currently in use
             if f in files_in_use:
                 continue
@@ -76,45 +91,187 @@ class RecordingMaintainer(threading.Thread):
             camera, date = basename.rsplit("-", maxsplit=1)
             start_time = datetime.datetime.strptime(date, "%Y%m%d%H%M%S")
 
-            # Just delete files if recordings are turned off
-            if (
-                not camera in self.config.cameras
-                or not self.config.cameras[camera].record.enabled
-            ):
-                Path(cache_path).unlink(missing_ok=True)
-                continue
-
-            ffprobe_cmd = [
-                "ffprobe",
-                "-v",
-                "error",
-                "-show_entries",
-                "format=duration",
-                "-of",
-                "default=noprint_wrappers=1:nokey=1",
-                f"{cache_path}",
-            ]
-            p = sp.run(ffprobe_cmd, capture_output=True)
-            if p.returncode == 0:
-                duration = float(p.stdout.decode().strip())
-                end_time = start_time + datetime.timedelta(seconds=duration)
-            else:
-                logger.info(f"bad file: {f}")
-                Path(cache_path).unlink(missing_ok=True)
-                continue
-
-            directory = os.path.join(
-                RECORD_DIR, start_time.strftime("%Y-%m/%d/%H"), camera
+            grouped_recordings[camera].append(
+                {
+                    "cache_path": cache_path,
+                    "start_time": start_time,
+                }
             )
 
-            if not os.path.exists(directory):
-                os.makedirs(directory)
+        # delete all cached files past the most recent 5
+        keep_count = 5
+        for camera in grouped_recordings.keys():
+            if len(grouped_recordings[camera]) > keep_count:
+                to_remove = grouped_recordings[camera][:-keep_count]
+                for f in to_remove:
+                    Path(f["cache_path"]).unlink(missing_ok=True)
+                    self.end_time_cache.pop(f["cache_path"], None)
+                grouped_recordings[camera] = grouped_recordings[camera][-keep_count:]
 
-            file_name = f"{start_time.strftime('%M.%S.mp4')}"
-            file_path = os.path.join(directory, file_name)
+        for camera, recordings in grouped_recordings.items():
 
+            # clear out all the recording info for old frames
+            while (
+                len(self.recordings_info[camera]) > 0
+                and self.recordings_info[camera][0][0]
+                < recordings[0]["start_time"].timestamp()
+            ):
+                self.recordings_info[camera].pop(0)
+
+            # get all events with the end time after the start of the oldest cache file
+            # or with end_time None
+            events: Event = (
+                Event.select()
+                .where(
+                    Event.camera == camera,
+                    (Event.end_time == None)
+                    | (Event.end_time >= recordings[0]["start_time"].timestamp()),
+                    Event.has_clip,
+                )
+                .order_by(Event.start_time)
+            )
+            for r in recordings:
+                cache_path = r["cache_path"]
+                start_time = r["start_time"]
+
+                # Just delete files if recordings are turned off
+                if (
+                    not camera in self.config.cameras
+                    or not self.config.cameras[camera].record.enabled
+                ):
+                    Path(cache_path).unlink(missing_ok=True)
+                    self.end_time_cache.pop(cache_path, None)
+                    continue
+
+                if cache_path in self.end_time_cache:
+                    end_time, duration = self.end_time_cache[cache_path]
+                else:
+                    ffprobe_cmd = [
+                        "ffprobe",
+                        "-v",
+                        "error",
+                        "-show_entries",
+                        "format=duration",
+                        "-of",
+                        "default=noprint_wrappers=1:nokey=1",
+                        f"{cache_path}",
+                    ]
+                    p = sp.run(ffprobe_cmd, capture_output=True)
+                    if p.returncode == 0:
+                        duration = float(p.stdout.decode().strip())
+                        end_time = start_time + datetime.timedelta(seconds=duration)
+                        self.end_time_cache[cache_path] = (end_time, duration)
+                    else:
+                        logger.warning(f"Discarding a corrupt recording segment: {f}")
+                        Path(cache_path).unlink(missing_ok=True)
+                        continue
+
+                # if cached file's start_time is earlier than the retain days for the camera
+                if start_time <= (
+                    (
+                        datetime.datetime.now()
+                        - datetime.timedelta(
+                            days=self.config.cameras[camera].record.retain.days
+                        )
+                    )
+                ):
+                    # if the cached segment overlaps with the events:
+                    overlaps = False
+                    for event in events:
+                        # if the event starts in the future, stop checking events
+                        # and remove this segment
+                        if event.start_time > end_time.timestamp():
+                            overlaps = False
+                            Path(cache_path).unlink(missing_ok=True)
+                            self.end_time_cache.pop(cache_path, None)
+                            break
+
+                        # if the event is in progress or ends after the recording starts, keep it
+                        # and stop looking at events
+                        if (
+                            event.end_time is None
+                            or event.end_time >= start_time.timestamp()
+                        ):
+                            overlaps = True
+                            break
+
+                    if overlaps:
+                        record_mode = self.config.cameras[
+                            camera
+                        ].record.events.retain.mode
+                        # move from cache to recordings immediately
+                        self.store_segment(
+                            camera,
+                            start_time,
+                            end_time,
+                            duration,
+                            cache_path,
+                            record_mode,
+                        )
+                # else retain days includes this segment
+                else:
+                    record_mode = self.config.cameras[camera].record.retain.mode
+                    self.store_segment(
+                        camera, start_time, end_time, duration, cache_path, record_mode
+                    )
+
+    def segment_stats(self, camera, start_time, end_time):
+        active_count = 0
+        motion_count = 0
+        for frame in self.recordings_info[camera]:
+            # frame is after end time of segment
+            if frame[0] > end_time.timestamp():
+                break
+            # frame is before start time of segment
+            if frame[0] < start_time.timestamp():
+                continue
+
+            active_count += len(
+                [
+                    o
+                    for o in frame[1]
+                    if not o["false_positive"] and o["motionless_count"] > 0
+                ]
+            )
+
+            motion_count += sum([area(box) for box in frame[2]])
+
+        return (motion_count, active_count)
+
+    def store_segment(
+        self,
+        camera,
+        start_time,
+        end_time,
+        duration,
+        cache_path,
+        store_mode: RetainModeEnum,
+    ):
+        motion_count, active_count = self.segment_stats(camera, start_time, end_time)
+
+        # check if the segment shouldn't be stored
+        if (store_mode == RetainModeEnum.motion and motion_count == 0) or (
+            store_mode == RetainModeEnum.active_objects and active_count == 0
+        ):
+            Path(cache_path).unlink(missing_ok=True)
+            self.end_time_cache.pop(cache_path, None)
+            return
+
+        directory = os.path.join(RECORD_DIR, start_time.strftime("%Y-%m/%d/%H"), camera)
+
+        if not os.path.exists(directory):
+            os.makedirs(directory)
+
+        file_name = f"{start_time.strftime('%M.%S.mp4')}"
+        file_path = os.path.join(directory, file_name)
+
+        try:
+            start_frame = datetime.datetime.now().timestamp()
             # copy then delete is required when recordings are stored on some network drives
             shutil.copyfile(cache_path, file_path)
+            logger.debug(
+                f"Copied {file_path} in {datetime.datetime.now().timestamp()-start_frame} seconds."
+            )
             os.remove(cache_path)
 
             rand_id = "".join(
@@ -127,12 +284,61 @@ class RecordingMaintainer(threading.Thread):
                 start_time=start_time.timestamp(),
                 end_time=end_time.timestamp(),
                 duration=duration,
+                motion=motion_count,
+                objects=active_count,
             )
+        except Exception as e:
+            logger.error(f"Unable to store recording segment {cache_path}")
+            Path(cache_path).unlink(missing_ok=True)
+            logger.error(e)
+
+        # clear end_time cache
+        self.end_time_cache.pop(cache_path, None)
 
     def run(self):
         # Check for new files every 5 seconds
-        while not self.stop_event.wait(5):
-            self.move_files()
+        wait_time = 5
+        while not self.stop_event.wait(wait_time):
+            run_start = datetime.datetime.now().timestamp()
+
+            # empty the recordings info queue
+            while True:
+                try:
+                    (
+                        camera,
+                        frame_time,
+                        current_tracked_objects,
+                        motion_boxes,
+                        regions,
+                    ) = self.recordings_info_queue.get(False)
+
+                    if self.config.cameras[camera].record.enabled:
+                        self.recordings_info[camera].append(
+                            (
+                                frame_time,
+                                current_tracked_objects,
+                                motion_boxes,
+                                regions,
+                            )
+                        )
+                except queue.Empty:
+                    break
+
+            try:
+                self.move_files()
+            except Exception as e:
+                logger.error(
+                    "Error occurred when attempting to maintain recording cache"
+                )
+                logger.error(e)
+            duration = datetime.datetime.now().timestamp() - run_start
+            wait_time = max(0, 5 - duration)
+            if wait_time == 0 and not self.first_pass:
+                logger.warning(
+                    "Cache is taking longer than 5 seconds to clear. Your recordings disk may be too slow."
+                )
+            if self.first_pass:
+                self.first_pass = False
 
         logger.info(f"Exiting recording maintenance...")
 
@@ -157,7 +363,7 @@ class RecordingCleanup(threading.Thread):
 
         logger.debug("Start deleted cameras.")
         # Handle deleted cameras
-        expire_days = self.config.record.retain_days
+        expire_days = self.config.record.retain.days
         expire_before = (
             datetime.datetime.now() - datetime.timedelta(days=expire_days)
         ).timestamp()
@@ -183,7 +389,7 @@ class RecordingCleanup(threading.Thread):
                 datetime.datetime.now()
                 - datetime.timedelta(seconds=config.record.events.max_seconds)
             ).timestamp()
-            expire_days = config.record.retain_days
+            expire_days = config.record.retain.days
             expire_before = (
                 datetime.datetime.now() - datetime.timedelta(days=expire_days)
             ).timestamp()
@@ -203,13 +409,18 @@ class RecordingCleanup(threading.Thread):
             events: Event = (
                 Event.select()
                 .where(
-                    Event.camera == camera, Event.end_time < expire_date, Event.has_clip
+                    Event.camera == camera,
+                    # need to ensure segments for all events starting
+                    # before the expire date are included
+                    Event.start_time < expire_date,
+                    Event.has_clip,
                 )
                 .order_by(Event.start_time)
                 .objects()
             )
 
             # loop over recordings and see if they overlap with any non-expired events
+            # TODO: expire segments based on segment stats according to config
             event_start = 0
             deleted_recordings = set()
             for recording in recordings.objects().iterator():
@@ -224,9 +435,9 @@ class RecordingCleanup(threading.Thread):
                         keep = False
                         break
 
-                    # if the event ends after the recording starts, keep it
+                    # if the event is in progress or ends after the recording starts, keep it
                     # and stop looking at events
-                    if event.end_time >= recording.start_time:
+                    if event.end_time is None or event.end_time >= recording.start_time:
                         keep = True
                         break
 
@@ -237,8 +448,19 @@ class RecordingCleanup(threading.Thread):
                     if event.end_time < recording.start_time:
                         event_start = idx
 
-                # Delete recordings outside of the retention window
-                if not keep:
+                # Delete recordings outside of the retention window or based on the retention mode
+                if (
+                    not keep
+                    or (
+                        config.record.events.retain.mode == RetainModeEnum.motion
+                        and recording.motion == 0
+                    )
+                    or (
+                        config.record.events.retain.mode
+                        == RetainModeEnum.active_objects
+                        and recording.objects == 0
+                    )
+                ):
                     Path(recording.path).unlink(missing_ok=True)
                     deleted_recordings.add(recording.id)
 
@@ -255,29 +477,31 @@ class RecordingCleanup(threading.Thread):
 
         default_expire = (
             datetime.datetime.now().timestamp()
-            - SECONDS_IN_DAY * self.config.record.retain_days
+            - SECONDS_IN_DAY * self.config.record.retain.days
         )
         delete_before = {}
 
         for name, camera in self.config.cameras.items():
             delete_before[name] = (
                 datetime.datetime.now().timestamp()
-                - SECONDS_IN_DAY * camera.record.retain_days
+                - SECONDS_IN_DAY * camera.record.retain.days
             )
 
         # find all the recordings older than the oldest recording in the db
         try:
-            oldest_recording = (
-                Recordings.select().order_by(Recordings.start_time.desc()).get()
-            )
+            oldest_recording = Recordings.select().order_by(Recordings.start_time).get()
 
-            oldest_timestamp = oldest_recording.start_time
+            p = Path(oldest_recording.path)
+            oldest_timestamp = p.stat().st_mtime - 1
         except DoesNotExist:
             oldest_timestamp = datetime.datetime.now().timestamp()
+        except FileNotFoundError:
+            logger.warning(f"Unable to find file from recordings database: {p}")
+            oldest_timestamp = datetime.datetime.now().timestamp()
 
         logger.debug(f"Oldest recording in the db: {oldest_timestamp}")
         process = sp.run(
-            ["find", RECORD_DIR, "-type", "f", "-newermt", f"@{oldest_timestamp}"],
+            ["find", RECORD_DIR, "-type", "f", "!", "-newermt", f"@{oldest_timestamp}"],
             capture_output=True,
             text=True,
         )
@@ -285,21 +509,52 @@ class RecordingCleanup(threading.Thread):
 
         for f in files_to_check:
             p = Path(f)
-            if p.stat().st_mtime < delete_before.get(p.parent.name, default_expire):
-                p.unlink(missing_ok=True)
+            try:
+                if p.stat().st_mtime < delete_before.get(p.parent.name, default_expire):
+                    p.unlink(missing_ok=True)
+            except FileNotFoundError:
+                logger.warning(f"Attempted to expire missing file: {f}")
 
         logger.debug("End expire files (legacy).")
 
+    def sync_recordings(self):
+        logger.debug("Start sync recordings.")
+
+        # get all recordings in the db
+        recordings: Recordings = Recordings.select()
+
+        # get all recordings files on disk
+        process = sp.run(
+            ["find", RECORD_DIR, "-type", "f"],
+            capture_output=True,
+            text=True,
+        )
+        files_on_disk = process.stdout.splitlines()
+
+        recordings_to_delete = []
+        for recording in recordings.objects().iterator():
+            if not recording.path in files_on_disk:
+                recordings_to_delete.append(recording.id)
+
+        logger.debug(
+            f"Deleting {len(recordings_to_delete)} recordings with missing files"
+        )
+        Recordings.delete().where(Recordings.id << recordings_to_delete).execute()
+
+        logger.debug("End sync recordings.")
+
     def run(self):
-        # Expire recordings every minute, clean directories every hour.
+        # on startup sync recordings with disk (disabled due to too much CPU usage)
+        # self.sync_recordings()
+
+        # Expire tmp clips every minute, recordings and clean directories every hour.
         for counter in itertools.cycle(range(60)):
             if self.stop_event.wait(60):
                 logger.info(f"Exiting recording cleanup...")
                 break
-
-            self.expire_recordings()
             self.clean_tmp_clips()
 
             if counter == 0:
+                self.expire_recordings()
                 self.expire_files()
                 remove_empty_directories(RECORD_DIR)

frigate/stats.py

@@ -4,6 +4,7 @@ import threading
 import time
 import psutil
 import shutil
+import os
 
 from frigate.config import FrigateConfig
 from frigate.const import RECORD_DIR, CLIPS_DIR, CACHE_DIR
@@ -31,6 +32,28 @@ def get_fs_type(path):
     return fsType
 
 
+def read_temperature(path):
+    if os.path.isfile(path):
+        with open(path) as f:
+            line = f.readline().strip()
+            return int(line) / 1000
+    return None
+
+
+def get_temperatures():
+    temps = {}
+
+    # Get temperatures for all attached Corals
+    base = "/sys/class/apex/"
+    if os.path.isdir(base):
+        for apex in os.listdir(base):
+            temp = read_temperature(os.path.join(base, apex, "temp"))
+            if temp is not None:
+                temps[apex] = temp
+
+    return temps
+
+
 def stats_snapshot(stats_tracking):
     camera_metrics = stats_tracking["camera_metrics"]
     stats = {}
@@ -61,6 +84,7 @@ def stats_snapshot(stats_tracking):
         "uptime": (int(time.time()) - stats_tracking["started"]),
         "version": VERSION,
         "storage": {},
+        "temperatures": get_temperatures(),
     }
 
     for path in [RECORD_DIR, CLIPS_DIR, CACHE_DIR, "/dev/shm"]:

frigate/test/test_config.py

@@ -702,7 +702,11 @@ class TestConfig(unittest.TestCase):
                         "inputs": [
                             {
                                 "path": "rtsp://10.0.0.1:554/video",
-                                "roles": ["detect", "clips"],
+                                "roles": ["detect"],
+                            },
+                            {
+                                "path": "rtsp://10.0.0.1:554/video2",
+                                "roles": ["clips"],
                             },
                         ]
                     },
@@ -717,6 +721,87 @@ class TestConfig(unittest.TestCase):
 
         self.assertRaises(ValidationError, lambda: FrigateConfig(**config))
 
+    def test_fails_on_missing_role(self):
+
+        config = {
+            "mqtt": {"host": "mqtt"},
+            "cameras": {
+                "back": {
+                    "ffmpeg": {
+                        "inputs": [
+                            {
+                                "path": "rtsp://10.0.0.1:554/video",
+                                "roles": ["detect"],
+                            },
+                            {
+                                "path": "rtsp://10.0.0.1:554/video2",
+                                "roles": ["record"],
+                            },
+                        ]
+                    },
+                    "detect": {
+                        "height": 1080,
+                        "width": 1920,
+                        "fps": 5,
+                    },
+                    "rtmp": {"enabled": True},
+                }
+            },
+        }
+
+        frigate_config = FrigateConfig(**config)
+        self.assertRaises(ValueError, lambda: frigate_config.runtime_config)
+
+    def test_works_on_missing_role_multiple_cams(self):
+
+        config = {
+            "mqtt": {"host": "mqtt"},
+            "rtmp": {"enabled": False},
+            "cameras": {
+                "back": {
+                    "ffmpeg": {
+                        "inputs": [
+                            {
+                                "path": "rtsp://10.0.0.1:554/video",
+                                "roles": ["detect"],
+                            },
+                            {
+                                "path": "rtsp://10.0.0.1:554/video2",
+                                "roles": ["record"],
+                            },
+                        ]
+                    },
+                    "detect": {
+                        "height": 1080,
+                        "width": 1920,
+                        "fps": 5,
+                    },
+                },
+                "cam2": {
+                    "ffmpeg": {
+                        "inputs": [
+                            {
+                                "path": "rtsp://10.0.0.1:554/video",
+                                "roles": ["detect"],
+                            },
+                            {
+                                "path": "rtsp://10.0.0.1:554/video2",
+                                "roles": ["record"],
+                            },
+                        ]
+                    },
+                    "detect": {
+                        "height": 1080,
+                        "width": 1920,
+                        "fps": 5,
+                    },
+                },
+            },
+        }
+
+        frigate_config = FrigateConfig(**config)
+        runtime_config = frigate_config.runtime_config
+
     def test_global_detect(self):
 
         config = {
@@ -958,6 +1043,34 @@ class TestConfig(unittest.TestCase):
         runtime_config = frigate_config.runtime_config
         assert runtime_config.cameras["back"].rtmp.enabled
 
+    def test_global_rtmp_default(self):
+
+        config = {
+            "mqtt": {"host": "mqtt"},
+            "rtmp": {"enabled": False},
+            "cameras": {
+                "back": {
+                    "ffmpeg": {
+                        "inputs": [
+                            {
+                                "path": "rtsp://10.0.0.1:554/video",
+                                "roles": ["detect"],
+                            },
+                            {
+                                "path": "rtsp://10.0.0.1:554/video2",
+                                "roles": ["record"],
+                            },
+                        ]
+                    },
+                }
+            },
+        }
+        frigate_config = FrigateConfig(**config)
+        assert config == frigate_config.dict(exclude_unset=True)
+
+        runtime_config = frigate_config.runtime_config
+        assert not runtime_config.cameras["back"].rtmp.enabled
+
     def test_global_live(self):
 
         config = {

frigate/test/test_reduce_boxes.py

@@ -0,0 +1,27 @@
+import cv2
+import numpy as np
+from unittest import TestCase, main
+from frigate.video import box_overlaps, reduce_boxes
+
+
+class TestBoxOverlaps(TestCase):
+    def test_overlap(self):
+        assert box_overlaps((100, 100, 200, 200), (50, 50, 150, 150))
+
+    def test_overlap_2(self):
+        assert box_overlaps((50, 50, 150, 150), (100, 100, 200, 200))
+
+    def test_no_overlap(self):
+        assert not box_overlaps((100, 100, 200, 200), (250, 250, 350, 350))
+
+
+class TestReduceBoxes(TestCase):
+    def test_cluster(self):
+        clusters = reduce_boxes(
+            [(144, 290, 221, 459), (225, 178, 426, 341), (343, 105, 584, 250)]
+        )
+        assert len(clusters) == 2
+
+
+if __name__ == "__main__":
+    main(verbosity=2)

frigate/util.py

@@ -191,7 +191,7 @@ def draw_box_with_label(
 
 def calculate_region(frame_shape, xmin, ymin, xmax, ymax, multiplier=2):
     # size is the longest edge and divisible by 4
-    size = int(max(xmax - xmin, ymax - ymin) // 4 * 4 * multiplier)
+    size = int((max(xmax - xmin, ymax - ymin) * multiplier) // 4 * 4)
     # dont go any smaller than 300
     if size < 300:
         size = 300

frigate/video.py

@@ -3,18 +3,18 @@ import itertools
 import logging
 import multiprocessing as mp
 import queue
-import subprocess as sp
 import signal
+import subprocess as sp
 import threading
 import time
 from collections import defaultdict
-from setproctitle import setproctitle
 from typing import Dict, List
 
-from cv2 import cv2
 import numpy as np
+from cv2 import cv2, reduce
+from setproctitle import setproctitle
 
-from frigate.config import CameraConfig
+from frigate.config import CameraConfig, DetectConfig
 from frigate.edgetpu import RemoteObjectDetector
 from frigate.log import LogPipe
 from frigate.motion import MotionDetector
@@ -23,8 +23,11 @@ from frigate.util import (
     EventsPerSecond,
     FrameManager,
     SharedMemoryFrameManager,
+    area,
     calculate_region,
     clipped,
+    intersection,
+    intersection_over_union,
     listen,
     yuv_region_2_rgb,
 )
@@ -364,6 +367,7 @@ def track_camera(
         frame_queue,
         frame_shape,
         model_shape,
+        config.detect,
         frame_manager,
         motion_detector,
         object_detector,
@@ -379,26 +383,36 @@ def track_camera(
     logger.info(f"{name}: exiting subprocess")
 
 
-def reduce_boxes(boxes):
-    if len(boxes) == 0:
-        return []
-    reduced_boxes = cv2.groupRectangles(
-        [list(b) for b in itertools.chain(boxes, boxes)], 1, 0.2
-    )[0]
-    return [tuple(b) for b in reduced_boxes]
+def box_overlaps(b1, b2):
+    if b1[2] < b2[0] or b1[0] > b2[2] or b1[1] > b2[3] or b1[3] < b2[1]:
+        return False
+    return True
+
+
+def reduce_boxes(boxes, iou_threshold=0.0):
+    clusters = []
+
+    for box in boxes:
+        matched = 0
+        for cluster in clusters:
+            if intersection_over_union(box, cluster) > iou_threshold:
+                matched = 1
+                cluster[0] = min(cluster[0], box[0])
+                cluster[1] = min(cluster[1], box[1])
+                cluster[2] = max(cluster[2], box[2])
+                cluster[3] = max(cluster[3], box[3])
+
+        if not matched:
+            clusters.append(list(box))
+
+    return [tuple(c) for c in clusters]
 
 
-# modified from https://stackoverflow.com/a/40795835
 def intersects_any(box_a, boxes):
     for box in boxes:
-        if (
-            box_a[2] < box[0]
-            or box_a[0] > box[2]
-            or box_a[1] > box[3]
-            or box_a[3] < box[1]
-        ):
-            continue
-        return True
+        if box_overlaps(box_a, box):
+            return True
+    return False
 
 
 def detect(
@@ -434,6 +448,7 @@ def process_frames(
     frame_queue: mp.Queue,
     frame_shape,
     model_shape,
+    detect_config: DetectConfig,
     frame_manager: FrameManager,
     motion_detector: MotionDetector,
     object_detector: RemoteObjectDetector,
@@ -487,11 +502,28 @@ def process_frames(
         # look for motion
         motion_boxes = motion_detector.detect(frame)
 
-        # only get the tracked object boxes that intersect with motion
+        # get stationary object ids
+        # check every Nth frame for stationary objects
+        # disappeared objects are not stationary
+        # also check for overlapping motion boxes
+        stationary_object_ids = [
+            obj["id"]
+            for obj in object_tracker.tracked_objects.values()
+            # if there hasn't been motion for 10 frames
+            if obj["motionless_count"] >= 10
+            # and it isn't due for a periodic check
+            and obj["motionless_count"] % detect_config.stationary_interval != 0
+            # and it hasn't disappeared
+            and object_tracker.disappeared[obj["id"]] == 0
+            # and it doesn't overlap with any current motion boxes
+            and not intersects_any(obj["box"], motion_boxes)
+        ]
+
+        # get tracked object boxes that aren't stationary
         tracked_object_boxes = [
             obj["box"]
             for obj in object_tracker.tracked_objects.values()
-            if intersects_any(obj["box"], motion_boxes)
+            if not obj["id"] in stationary_object_ids
         ]
 
         # combine motion boxes with known locations of existing objects
@@ -503,17 +535,25 @@ def process_frames(
             for a in combined_boxes
         ]
 
-        # combine overlapping regions
-        combined_regions = reduce_boxes(regions)
-
-        # re-compute regions
+        # consolidate regions with heavy overlap
         regions = [
             calculate_region(frame_shape, a[0], a[1], a[2], a[3], 1.0)
-            for a in combined_regions
+            for a in reduce_boxes(regions, 0.4)
         ]
 
         # resize regions and detect
-        detections = []
+        # seed with stationary objects
+        detections = [
+            (
+                obj["label"],
+                obj["score"],
+                obj["box"],
+                obj["area"],
+                obj["region"],
+            )
+            for obj in object_tracker.tracked_objects.values()
+            if obj["id"] in stationary_object_ids
+        ]
         for region in regions:
             detections.extend(
                 detect(
@@ -582,14 +622,46 @@ def process_frames(
             if refining:
                 refine_count += 1
 
-        # Limit to the detections overlapping with motion areas
-        # to avoid picking up stationary background objects
-        detections_with_motion = [
-            d for d in detections if intersects_any(d[2], motion_boxes)
-        ]
+        ## drop detections that overlap too much
+        consolidated_detections = []
+        # group by name
+        detected_object_groups = defaultdict(lambda: [])
+        for detection in detections:
+            detected_object_groups[detection[0]].append(detection)
+
+        # loop over detections grouped by label
+        for group in detected_object_groups.values():
+            # if the group only has 1 item, skip
+            if len(group) == 1:
+                consolidated_detections.append(group[0])
+                continue
+
+            # sort smallest to largest by area
+            sorted_by_area = sorted(group, key=lambda g: g[3])
+
+            for current_detection_idx in range(0, len(sorted_by_area)):
+                current_detection = sorted_by_area[current_detection_idx][2]
+                overlap = 0
+                for to_check_idx in range(
+                    min(current_detection_idx + 1, len(sorted_by_area)),
+                    len(sorted_by_area),
+                ):
+                    to_check = sorted_by_area[to_check_idx][2]
+                    # if 90% of smaller detection is inside of another detection, consolidate
+                    if (
+                        area(intersection(current_detection, to_check))
+                        / area(current_detection)
+                        > 0.9
+                    ):
+                        overlap = 1
+                        break
+                if overlap == 0:
+                    consolidated_detections.append(
+                        sorted_by_area[current_detection_idx]
+                    )
 
         # now that we have refined our detections, we need to track objects
-        object_tracker.match_and_update(frame_time, detections_with_motion)
+        object_tracker.match_and_update(frame_time, consolidated_detections)
 
         # add to the queue if not full
         if detected_objects_queue.full():

migrations/003_create_recordings_table.py

@@ -28,17 +28,19 @@ SQL = pw.SQL
 
 
 def migrate(migrator, database, fake=False, **kwargs):
-    migrator.create_model(Recordings)
-
-    def add_index():
-        # First add the index here, because there is a bug in peewee_migrate
-        # when trying to create an multi-column index in the same migration
-        # as the table: https://github.com/klen/peewee_migrate/issues/19
-        Recordings.add_index("start_time", "end_time")
-        Recordings.create_table()
-
-    migrator.python(add_index)
+    migrator.sql(
+        'CREATE TABLE IF NOT EXISTS "recordings" ("id" VARCHAR(30) NOT NULL PRIMARY KEY, "camera" VARCHAR(20) NOT NULL, "path" VARCHAR(255) NOT NULL, "start_time" DATETIME NOT NULL, "end_time" DATETIME NOT NULL, "duration" REAL NOT NULL)'
+    )
+    migrator.sql(
+        'CREATE INDEX IF NOT EXISTS "recordings_camera" ON "recordings" ("camera")'
+    )
+    migrator.sql(
+        'CREATE UNIQUE INDEX IF NOT EXISTS "recordings_path" ON "recordings" ("path")'
+    )
+    migrator.sql(
+        'CREATE INDEX IF NOT EXISTS "recordings_start_time_end_time" ON "recordings" (start_time, end_time)'
+    )
 
 
 def rollback(migrator, database, fake=False, **kwargs):
-    migrator.remove_model(Recordings)
+    pass

migrations/005_make_end_time_nullable.py

@@ -0,0 +1,43 @@
+"""Peewee migrations -- 004_add_bbox_region_area.py.
+
+Some examples (model - class or model name)::
+
+    > Model = migrator.orm['model_name']            # Return model in current state by name
+
+    > migrator.sql(sql)                             # Run custom SQL
+    > migrator.python(func, *args, **kwargs)        # Run python code
+    > migrator.create_model(Model)                  # Create a model (could be used as decorator)
+    > migrator.remove_model(model, cascade=True)    # Remove a model
+    > migrator.add_fields(model, **fields)          # Add fields to a model
+    > migrator.change_fields(model, **fields)       # Change fields
+    > migrator.remove_fields(model, *field_names, cascade=True)
+    > migrator.rename_field(model, old_field_name, new_field_name)
+    > migrator.rename_table(model, new_table_name)
+    > migrator.add_index(model, *col_names, unique=False)
+    > migrator.drop_index(model, *col_names)
+    > migrator.add_not_null(model, *field_names)
+    > migrator.drop_not_null(model, *field_names)
+    > migrator.add_default(model, field_name, default)
+
+"""
+
+import datetime as dt
+import peewee as pw
+from playhouse.sqlite_ext import *
+from decimal import ROUND_HALF_EVEN
+from frigate.models import Event
+
+try:
+    import playhouse.postgres_ext as pw_pext
+except ImportError:
+    pass
+
+SQL = pw.SQL
+
+
+def migrate(migrator, database, fake=False, **kwargs):
+    migrator.drop_not_null(Event, "end_time")
+
+
+def rollback(migrator, database, fake=False, **kwargs):
+    pass

migrations/006_add_motion_active_objects.py

@@ -0,0 +1,47 @@
+"""Peewee migrations -- 004_add_bbox_region_area.py.
+
+Some examples (model - class or model name)::
+
+    > Model = migrator.orm['model_name']            # Return model in current state by name
+
+    > migrator.sql(sql)                             # Run custom SQL
+    > migrator.python(func, *args, **kwargs)        # Run python code
+    > migrator.create_model(Model)                  # Create a model (could be used as decorator)
+    > migrator.remove_model(model, cascade=True)    # Remove a model
+    > migrator.add_fields(model, **fields)          # Add fields to a model
+    > migrator.change_fields(model, **fields)       # Change fields
+    > migrator.remove_fields(model, *field_names, cascade=True)
+    > migrator.rename_field(model, old_field_name, new_field_name)
+    > migrator.rename_table(model, new_table_name)
+    > migrator.add_index(model, *col_names, unique=False)
+    > migrator.drop_index(model, *col_names)
+    > migrator.add_not_null(model, *field_names)
+    > migrator.drop_not_null(model, *field_names)
+    > migrator.add_default(model, field_name, default)
+
+"""
+
+import datetime as dt
+import peewee as pw
+from playhouse.sqlite_ext import *
+from decimal import ROUND_HALF_EVEN
+from frigate.models import Recordings
+
+try:
+    import playhouse.postgres_ext as pw_pext
+except ImportError:
+    pass
+
+SQL = pw.SQL
+
+
+def migrate(migrator, database, fake=False, **kwargs):
+    migrator.add_fields(
+        Recordings,
+        objects=pw.IntegerField(null=True),
+        motion=pw.IntegerField(null=True),
+    )
+
+
+def rollback(migrator, database, fake=False, **kwargs):
+    migrator.remove_fields(Recordings, ["objects", "motion"])

process_clip.py

@@ -1,23 +1,26 @@
-import datetime
+import sys
+from typing_extensions import runtime
+
+sys.path.append("/lab/frigate")
+
 import json
 import logging
 import multiprocessing as mp
 import os
 import subprocess as sp
 import sys
-from unittest import TestCase, main
 
 import click
+import csv
 import cv2
 import numpy as np
 
-from frigate.config import FRIGATE_CONFIG_SCHEMA, FrigateConfig
+from frigate.config import FrigateConfig
 from frigate.edgetpu import LocalObjectDetector
 from frigate.motion import MotionDetector
 from frigate.object_processing import CameraState
 from frigate.objects import ObjectTracker
 from frigate.util import (
-    DictFrameManager,
     EventsPerSecond,
     SharedMemoryFrameManager,
     draw_box_with_label,
@@ -96,20 +99,22 @@ class ProcessClip:
         ffmpeg_process.wait()
         ffmpeg_process.communicate()
 
-    def process_frames(self, objects_to_track=["person"], object_filters={}):
+    def process_frames(
+        self, object_detector, objects_to_track=["person"], object_filters={}
+    ):
         mask = np.zeros((self.frame_shape[0], self.frame_shape[1], 1), np.uint8)
         mask[:] = 255
-        motion_detector = MotionDetector(
-            self.frame_shape, mask, self.camera_config.motion
-        )
+        motion_detector = MotionDetector(self.frame_shape, self.camera_config.motion)
+        motion_detector.save_images = False
 
-        object_detector = LocalObjectDetector(labels="/labelmap.txt")
         object_tracker = ObjectTracker(self.camera_config.detect)
         process_info = {
             "process_fps": mp.Value("d", 0.0),
             "detection_fps": mp.Value("d", 0.0),
             "detection_frame": mp.Value("d", 0.0),
         }
+
+        detection_enabled = mp.Value("d", 1)
         stop_event = mp.Event()
         model_shape = (self.config.model.height, self.config.model.width)
 
@@ -118,6 +123,7 @@ class ProcessClip:
             self.frame_queue,
             self.frame_shape,
             model_shape,
+            self.camera_config.detect,
             self.frame_manager,
             motion_detector,
             object_detector,
@@ -126,25 +132,16 @@ class ProcessClip:
             process_info,
             objects_to_track,
             object_filters,
-            mask,
+            detection_enabled,
             stop_event,
             exit_on_empty=True,
         )
 
-    def top_object(self, debug_path=None):
-        obj_detected = False
-        top_computed_score = 0.0
-
-        def handle_event(name, obj, frame_time):
-            nonlocal obj_detected
-            nonlocal top_computed_score
-            if obj.computed_score > top_computed_score:
-                top_computed_score = obj.computed_score
-            if not obj.false_positive:
-                obj_detected = True
-
-        self.camera_state.on("new", handle_event)
-        self.camera_state.on("update", handle_event)
+    def stats(self, debug_path=None):
+        total_regions = 0
+        total_motion_boxes = 0
+        object_ids = set()
+        total_frames = 0
 
         while not self.detected_objects_queue.empty():
             (
@@ -154,7 +151,8 @@ class ProcessClip:
                 motion_boxes,
                 regions,
             ) = self.detected_objects_queue.get()
-            if not debug_path is None:
+
+            if debug_path:
                 self.save_debug_frame(
                     debug_path, frame_time, current_tracked_objects.values()
                 )
@@ -162,10 +160,26 @@ class ProcessClip:
             self.camera_state.update(
                 frame_time, current_tracked_objects, motion_boxes, regions
             )
+            total_regions += len(regions)
+            total_motion_boxes += len(motion_boxes)
+            top_score = 0
+            for id, obj in self.camera_state.tracked_objects.items():
+                if not obj.false_positive:
+                    object_ids.add(id)
+                    if obj.top_score > top_score:
+                        top_score = obj.top_score
 
-        self.frame_manager.delete(self.camera_state.previous_frame_id)
+            total_frames += 1
 
-        return {"object_detected": obj_detected, "top_score": top_computed_score}
+            self.frame_manager.delete(self.camera_state.previous_frame_id)
+
+        return {
+            "total_regions": total_regions,
+            "total_motion_boxes": total_motion_boxes,
+            "true_positive_objects": len(object_ids),
+            "total_frames": total_frames,
+            "top_score": top_score,
+        }
 
     def save_debug_frame(self, debug_path, frame_time, tracked_objects):
         current_frame = cv2.cvtColor(
@@ -178,7 +192,6 @@ class ProcessClip:
         for obj in tracked_objects:
             thickness = 2
             color = (0, 0, 175)
-
             if obj["frame_time"] != frame_time:
                 thickness = 1
                 color = (255, 0, 0)
@@ -221,10 +234,9 @@ class ProcessClip:
 @click.command()
 @click.option("-p", "--path", required=True, help="Path to clip or directory to test.")
 @click.option("-l", "--label", default="person", help="Label name to detect.")
-@click.option("-t", "--threshold", default=0.85, help="Threshold value for objects.")
-@click.option("-s", "--scores", default=None, help="File to save csv of top scores")
+@click.option("-o", "--output", default=None, help="File to save csv of data")
 @click.option("--debug-path", default=None, help="Path to output frames for debugging.")
-def process(path, label, threshold, scores, debug_path):
+def process(path, label, output, debug_path):
     clips = []
     if os.path.isdir(path):
         files = os.listdir(path)
@@ -235,51 +247,79 @@ def process(path, label, threshold, scores, debug_path):
 
     json_config = {
         "mqtt": {"host": "mqtt"},
+        "detectors": {"coral": {"type": "edgetpu", "device": "usb"}},
         "cameras": {
             "camera": {
                 "ffmpeg": {
                     "inputs": [
                         {
                             "path": "path.mp4",
-                            "global_args": "",
-                            "input_args": "",
+                            "global_args": "-hide_banner",
+                            "input_args": "-loglevel info",
                             "roles": ["detect"],
                         }
                     ]
                 },
-                "height": 1920,
-                "width": 1080,
+                "rtmp": {"enabled": False},
+                "record": {"enabled": False},
             }
         },
     }
 
+    object_detector = LocalObjectDetector(labels="/labelmap.txt")
+
     results = []
     for c in clips:
         logger.info(c)
         frame_shape = get_frame_shape(c)
 
-        json_config["cameras"]["camera"]["height"] = frame_shape[0]
-        json_config["cameras"]["camera"]["width"] = frame_shape[1]
+        json_config["cameras"]["camera"]["detect"] = {
+            "height": frame_shape[0],
+            "width": frame_shape[1],
+        }
         json_config["cameras"]["camera"]["ffmpeg"]["inputs"][0]["path"] = c
 
-        config = FrigateConfig(config=FRIGATE_CONFIG_SCHEMA(json_config))
+        frigate_config = FrigateConfig(**json_config)
+        runtime_config = frigate_config.runtime_config
+        runtime_config.cameras["camera"].create_ffmpeg_cmds()
 
-        process_clip = ProcessClip(c, frame_shape, config)
+        process_clip = ProcessClip(c, frame_shape, runtime_config)
         process_clip.load_frames()
-        process_clip.process_frames(objects_to_track=[label])
+        process_clip.process_frames(object_detector, objects_to_track=[label])
 
-        results.append((c, process_clip.top_object(debug_path)))
+        results.append((c, process_clip.stats(debug_path)))
 
-    if not scores is None:
-        with open(scores, "w") as writer:
-            for result in results:
-                writer.write(f"{result[0]},{result[1]['top_score']}\n")
-
-    positive_count = sum(1 for result in results if result[1]["object_detected"])
+    positive_count = sum(
+        1 for result in results if result[1]["true_positive_objects"] > 0
+    )
     print(
         f"Objects were detected in {positive_count}/{len(results)}({positive_count/len(results)*100:.2f}%) clip(s)."
     )
 
+    if output:
+        # now we will open a file for writing
+        data_file = open(output, "w")
+
+        # create the csv writer object
+        csv_writer = csv.writer(data_file)
+
+        # Counter variable used for writing
+        # headers to the CSV file
+        count = 0
+
+        for result in results:
+            if count == 0:
+
+                # Writing headers of CSV file
+                header = ["file"] + list(result[1].keys())
+                csv_writer.writerow(header)
+                count += 1
+
+            # Writing data of CSV file
+            csv_writer.writerow([result[0]] + list(result[1].values()))
+
+        data_file.close()
+
 
 if __name__ == "__main__":
     process()

web/package.json

@@ -14,7 +14,7 @@
     "@cycjimmy/jsmpeg-player": "^5.0.1",
     "date-fns": "^2.21.3",
     "idb-keyval": "^5.0.2",
-    "immer": "^8.0.1",
+    "immer": "^9.0.6",
     "preact": "^10.5.9",
     "preact-async-route": "^2.2.1",
     "preact-router": "^3.2.1",

web/src/Sidebar.jsx

@@ -61,7 +61,7 @@ export default function Sidebar() {
           <Separator />
         </Fragment>
       ) : null}
-      <Destination className="self-end" href="https://blakeblackshear.github.io/frigate" text="Documentation" />
+      <Destination className="self-end" href="https://docs.frigate.video" text="Documentation" />
       <Destination className="self-end" href="https://github.com/blakeblackshear/frigate" text="GitHub" />
     </NavigationDrawer>
   );

web/src/api/__tests__/mqtt.test.jsx

@@ -121,12 +121,12 @@ describe('MqttProvider', () => {
       </MqttProvider>
     );
     await screen.findByTestId('data');
-    expect(screen.getByTestId('front/detect/state')).toHaveTextContent('{"lastUpdate":123456,"payload":"ON"}');
-    expect(screen.getByTestId('front/recordings/state')).toHaveTextContent('{"lastUpdate":123456,"payload":"OFF"}');
-    expect(screen.getByTestId('front/snapshots/state')).toHaveTextContent('{"lastUpdate":123456,"payload":"ON"}');
-    expect(screen.getByTestId('side/detect/state')).toHaveTextContent('{"lastUpdate":123456,"payload":"OFF"}');
-    expect(screen.getByTestId('side/recordings/state')).toHaveTextContent('{"lastUpdate":123456,"payload":"OFF"}');
-    expect(screen.getByTestId('side/snapshots/state')).toHaveTextContent('{"lastUpdate":123456,"payload":"OFF"}');
+    expect(screen.getByTestId('front/detect/state')).toHaveTextContent('{"lastUpdate":123456,"payload":"ON","retain":true}');
+    expect(screen.getByTestId('front/recordings/state')).toHaveTextContent('{"lastUpdate":123456,"payload":"OFF","retain":true}');
+    expect(screen.getByTestId('front/snapshots/state')).toHaveTextContent('{"lastUpdate":123456,"payload":"ON","retain":true}');
+    expect(screen.getByTestId('side/detect/state')).toHaveTextContent('{"lastUpdate":123456,"payload":"OFF","retain":true}');
+    expect(screen.getByTestId('side/recordings/state')).toHaveTextContent('{"lastUpdate":123456,"payload":"OFF","retain":true}');
+    expect(screen.getByTestId('side/snapshots/state')).toHaveTextContent('{"lastUpdate":123456,"payload":"OFF","retain":true}');
   });
 });
 

web/src/api/mqtt.jsx

@@ -42,9 +42,9 @@ export function MqttProvider({
   useEffect(() => {
     Object.keys(config.cameras).forEach((camera) => {
       const { name, record, detect, snapshots } = config.cameras[camera];
-      dispatch({ topic: `${name}/recordings/state`, payload: record.enabled ? 'ON' : 'OFF' });
-      dispatch({ topic: `${name}/detect/state`, payload: detect.enabled ? 'ON' : 'OFF' });
-      dispatch({ topic: `${name}/snapshots/state`, payload: snapshots.enabled ? 'ON' : 'OFF' });
+      dispatch({ topic: `${name}/recordings/state`, payload: record.enabled ? 'ON' : 'OFF', retain: true });
+      dispatch({ topic: `${name}/detect/state`, payload: detect.enabled ? 'ON' : 'OFF', retain: true });
+      dispatch({ topic: `${name}/snapshots/state`, payload: snapshots.enabled ? 'ON' : 'OFF', retain: true });
     });
   }, [config]);
 

web/src/components/JSMpegPlayer.jsx

@@ -3,7 +3,7 @@ import { baseUrl } from '../api/baseUrl';
 import { useRef, useEffect } from 'preact/hooks';
 import JSMpeg from '@cycjimmy/jsmpeg-player';
 
-export default function JSMpegPlayer({ camera }) {
+export default function JSMpegPlayer({ camera, width, height }) {
   const playerRef = useRef();
   const url = `${baseUrl.replace(/^http/, 'ws')}/live/${camera}`
 
@@ -32,6 +32,6 @@ export default function JSMpegPlayer({ camera }) {
   }, [url]);
 
   return (
-    <div ref={playerRef} class="jsmpeg" />
+    <div ref={playerRef} class="jsmpeg" style={`max-height: ${height}px; max-width: ${width}px`} />
   );
 }

web/src/routes/Camera.jsx

@@ -21,6 +21,7 @@ export default function Camera({ camera }) {
   const [viewMode, setViewMode] = useState('live');
 
   const cameraConfig = config?.cameras[camera];
+  const liveWidth = Math.round(cameraConfig.live.height * (cameraConfig.detect.width / cameraConfig.detect.height))
   const [options, setOptions] = usePersistence(`${camera}-feed`, emptyObject);
 
   const handleSetOption = useCallback(
@@ -87,7 +88,7 @@ export default function Camera({ camera }) {
     player = (
       <Fragment>
         <div>
-          <JSMpegPlayer camera={camera} />
+          <JSMpegPlayer camera={camera} width={liveWidth} height={cameraConfig.live.height} />
         </div>
       </Fragment>
     );

web/src/routes/Event.jsx

@@ -99,7 +99,7 @@ export default function Event({ eventId, close, scrollRef }) {
   }
 
   const startime = new Date(data.start_time * 1000);
-  const endtime = new Date(data.end_time * 1000);
+  const endtime = data.end_time ? new Date(data.end_time * 1000) : null;
   return (
     <div className="space-y-4">
       <div className="flex md:flex-row justify-between flex-wrap flex-col">
@@ -155,7 +155,7 @@ export default function Event({ eventId, close, scrollRef }) {
               <Tr index={1}>
                 <Td>Timeframe</Td>
                 <Td>
-                  {startime.toLocaleString()} – {endtime.toLocaleString()}
+                  {startime.toLocaleString()}{endtime === null ? ` – ${endtime.toLocaleString()}`:''}
                 </Td>
               </Tr>
               <Tr>
@@ -186,7 +186,7 @@ export default function Event({ eventId, close, scrollRef }) {
                     },
                   ],
                   poster: data.has_snapshot
-                    ? `${apiHost}/clips/${data.camera}-${eventId}.jpg`
+                    ? `${apiHost}/api/events/${eventId}/snapshot.jpg`
                     : `data:image/jpeg;base64,${data.thumbnail}`,
                 }}
                 seekOptions={{ forward: 10, back: 5 }}
@@ -199,7 +199,7 @@ export default function Event({ eventId, close, scrollRef }) {
               <img
                 src={
                   data.has_snapshot
-                    ? `${apiHost}/clips/${data.camera}-${eventId}.jpg`
+                    ? `${apiHost}/api/events/${eventId}/snapshot.jpg`
                     : `data:image/jpeg;base64,${data.thumbnail}`
                 }
                 alt={`${data.label} at ${(data.top_score * 100).toFixed(1)}% confidence`}

web/src/routes/Events/components/tableRow.jsx

@@ -42,7 +42,7 @@ const EventsRow = memo(
     );
 
     const start = new Date(parseInt(startTime * 1000, 10));
-    const end = new Date(parseInt(endTime * 1000, 10));
+    const end = endTime ? new Date(parseInt(endTime * 1000, 10)) : null;
 
     return (
       <Tbody reference={innerRef}>
@@ -102,7 +102,7 @@ const EventsRow = memo(
           </Td>
           <Td>{start.toLocaleDateString()}</Td>
           <Td>{start.toLocaleTimeString()}</Td>
-          <Td>{end.toLocaleTimeString()}</Td>
+          <Td>{end === null ? 'In progress' : end.toLocaleTimeString()}</Td>
         </Tr>
         {viewEvent === id ? (
           <Tr className="border-b-1">

web/src/routes/__tests__/Camera.test.jsx

@@ -13,7 +13,7 @@ describe('Camera Route', () => {
     mockSetOptions = jest.fn();
     mockUsePersistence = jest.spyOn(Context, 'usePersistence').mockImplementation(() => [{}, mockSetOptions]);
     jest.spyOn(Api, 'useConfig').mockImplementation(() => ({
-      data: { cameras: { front: { name: 'front', objects: { track: ['taco', 'cat', 'dog'] } } } },
+      data: { cameras: { front: { name: 'front', detect: {width: 1280, height: 720}, live: {height: 720}, objects: { track: ['taco', 'cat', 'dog'] } } } },
     }));
     jest.spyOn(Api, 'useApiHost').mockImplementation(() => 'http://base-url.local:5000');
     jest.spyOn(AutoUpdatingCameraImage, 'default').mockImplementation(({ searchParams }) => {