Recordings - fix expire_file

ref: https://github.com/blakeblackshear/frigate/issues/373

.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

@@ -1,11 +1,8 @@
-.DS_Store
-*.pyc
+*.pyc 
 debug
 .vscode
 config/config.yml
 models
 *.mp4
 *.db
-frigate/version.py
-web/build
-web/node_modules
+frigate/version.py

Makefile

@@ -1,59 +1,54 @@
 default_target: amd64_frigate
 
-COMMIT_HASH := $(shell git log -1 --pretty=format:"%h"|tail -1)
+COMMIT_HASH := $(shell git log -1 --pretty=format:"%h")
 
 version:
-	echo "VERSION='0.8.1-$(COMMIT_HASH)'" > frigate/version.py
-
-web:
-	docker build --tag frigate-web --file docker/Dockerfile.web web/
+	echo "VERSION='0.8.0-$(COMMIT_HASH)'" > frigate/version.py
 
 amd64_wheels:
-	docker build --tag blakeblackshear/frigate-wheels:1.0.1-amd64 --file docker/Dockerfile.wheels .
+	docker build --tag blakeblackshear/frigate-wheels:amd64 --file docker/Dockerfile.wheels .
 
 amd64_ffmpeg:
 	docker build --tag blakeblackshear/frigate-ffmpeg:1.1.0-amd64 --file docker/Dockerfile.ffmpeg.amd64 .
 
-amd64_frigate: version web
-	docker build --tag frigate-base --build-arg ARCH=amd64 --build-arg FFMPEG_VERSION=1.1.0 --build-arg WHEELS_VERSION=1.0.1 --file docker/Dockerfile.base .
+amd64_frigate: version
+	docker build --tag frigate-base --build-arg ARCH=amd64 --build-arg FFMPEG_VERSION=1.1.0 --file docker/Dockerfile.base .
 	docker build --tag frigate --file docker/Dockerfile.amd64 .
 
 amd64_all: amd64_wheels amd64_ffmpeg amd64_frigate
 
 amd64nvidia_wheels:
-	docker build --tag blakeblackshear/frigate-wheels:1.0.1-amd64nvidia --file docker/Dockerfile.wheels .
+	docker build --tag blakeblackshear/frigate-wheels:amd64nvidia --file docker/Dockerfile.wheels .
 
 amd64nvidia_ffmpeg:
 	docker build --tag blakeblackshear/frigate-ffmpeg:1.0.0-amd64nvidia --file docker/Dockerfile.ffmpeg.amd64nvidia .
 
-amd64nvidia_frigate: version web
-	docker build --tag frigate-base --build-arg ARCH=amd64nvidia --build-arg FFMPEG_VERSION=1.0.0 --build-arg WHEELS_VERSION=1.0.1 --file docker/Dockerfile.base .
+amd64nvidia_frigate: version
+	docker build --tag frigate-base --build-arg ARCH=amd64nvidia --build-arg FFMPEG_VERSION=1.0.0 --file docker/Dockerfile.base .
 	docker build --tag frigate --file docker/Dockerfile.amd64nvidia .
 
 amd64nvidia_all: amd64nvidia_wheels amd64nvidia_ffmpeg amd64nvidia_frigate
 
 aarch64_wheels:
-	docker build --tag blakeblackshear/frigate-wheels:1.0.1-aarch64 --file docker/Dockerfile.wheels .
+	docker build --tag blakeblackshear/frigate-wheels:aarch64 --file docker/Dockerfile.wheels.aarch64 .
 
 aarch64_ffmpeg:
 	docker build --tag blakeblackshear/frigate-ffmpeg:1.0.0-aarch64 --file docker/Dockerfile.ffmpeg.aarch64 .
 
-aarch64_frigate: version web
-	docker build --tag frigate-base --build-arg ARCH=aarch64 --build-arg FFMPEG_VERSION=1.0.0 --build-arg WHEELS_VERSION=1.0.1 --file docker/Dockerfile.base .
+aarch64_frigate: version
+	docker build --tag frigate-base --build-arg ARCH=aarch64 --build-arg FFMPEG_VERSION=1.0.0 --file docker/Dockerfile.base .
 	docker build --tag frigate --file docker/Dockerfile.aarch64 .
 
 armv7_all: armv7_wheels armv7_ffmpeg armv7_frigate
 
 armv7_wheels:
-	docker build --tag blakeblackshear/frigate-wheels:1.0.1-armv7 --file docker/Dockerfile.wheels .
+	docker build --tag blakeblackshear/frigate-wheels:armv7 --file docker/Dockerfile.wheels .
 
 armv7_ffmpeg:
 	docker build --tag blakeblackshear/frigate-ffmpeg:1.0.0-armv7 --file docker/Dockerfile.ffmpeg.armv7 .
 
-armv7_frigate: version web
-	docker build --tag frigate-base --build-arg ARCH=armv7 --build-arg FFMPEG_VERSION=1.0.0 --build-arg WHEELS_VERSION=1.0.1 --file docker/Dockerfile.base .
+armv7_frigate: version
+	docker build --tag frigate-base --build-arg ARCH=armv7 --build-arg FFMPEG_VERSION=1.0.0 --file docker/Dockerfile.base .
 	docker build --tag frigate --file docker/Dockerfile.armv7 .
 
 armv7_all: armv7_wheels armv7_ffmpeg armv7_frigate
-
-.PHONY: web

docker/Dockerfile.base

@@ -1,9 +1,7 @@
 ARG ARCH=amd64
-ARG WHEELS_VERSION
 ARG FFMPEG_VERSION
-FROM blakeblackshear/frigate-wheels:${WHEELS_VERSION}-${ARCH} as wheels
+FROM blakeblackshear/frigate-wheels:${ARCH} as wheels
 FROM blakeblackshear/frigate-ffmpeg:${FFMPEG_VERSION}-${ARCH} as ffmpeg
-FROM frigate-web as web
 
 FROM ubuntu:20.04
 LABEL maintainer "blakeb@blakeshome.com"
@@ -32,7 +30,7 @@ RUN apt-get -qq update \
     && (apt-get autoremove -y; apt-get autoclean -y)
 
 RUN pip3 install \
-    peewee_migrate \
+    peewee \
     zeroconf \
     voluptuous
 
@@ -45,9 +43,6 @@ RUN wget -q https://github.com/google-coral/test_data/raw/master/ssdlite_mobiled
 
 WORKDIR /opt/frigate/
 ADD frigate frigate/
-ADD migrations migrations/
-
-COPY --from=web /opt/frigate/build web/
 
 COPY run.sh /run.sh
 RUN chmod +x /run.sh

docker/Dockerfile.web

@@ -1,9 +0,0 @@
-ARG NODE_VERSION=14.0
-
-FROM node:${NODE_VERSION}
-
-WORKDIR /opt/frigate
-
-COPY . .
-
-RUN npm install && npm run build

docker/Dockerfile.wheels

@@ -18,14 +18,13 @@ RUN apt-get -qq update \
     gcc gfortran libopenblas-dev liblapack-dev cython
 
 RUN wget -q https://bootstrap.pypa.io/get-pip.py -O get-pip.py \
-    && python3 get-pip.py "pip==20.2.4"
+    && python3 get-pip.py
 
 RUN pip3 install scikit-build
 
 RUN pip3 wheel --wheel-dir=/wheels \
     opencv-python-headless \
-    # pinning due to issue in 1.19.5 https://github.com/numpy/numpy/issues/18131
-    numpy==1.19.4 \
+    numpy \
     imutils \
     scipy \
     psutil \
@@ -33,9 +32,7 @@ RUN pip3 wheel --wheel-dir=/wheels \
     paho-mqtt \
     PyYAML \
     matplotlib \
-    click \
-    setproctitle \
-    peewee
+    click
 
 FROM scratch
 

docker/Dockerfile.wheels.aarch64

@@ -0,0 +1,49 @@
+FROM ubuntu:20.04 as build
+
+ENV DEBIAN_FRONTEND=noninteractive
+
+RUN apt-get -qq update \
+    && apt-get -qq install -y \
+    python3 \
+    python3-dev \
+    wget \
+    # opencv dependencies
+    build-essential cmake git pkg-config libgtk-3-dev \
+    libavcodec-dev libavformat-dev libswscale-dev libv4l-dev \
+    libxvidcore-dev libx264-dev libjpeg-dev libpng-dev libtiff-dev \
+    gfortran openexr libatlas-base-dev libssl-dev\
+    libtbb2 libtbb-dev libdc1394-22-dev libopenexr-dev \
+    libgstreamer-plugins-base1.0-dev libgstreamer1.0-dev \
+    # scipy dependencies
+    gcc gfortran libopenblas-dev liblapack-dev cython
+
+RUN wget -q https://bootstrap.pypa.io/get-pip.py -O get-pip.py \
+    && python3 get-pip.py
+
+# need to build cmake from source because binary distribution is broken for arm64
+# https://github.com/scikit-build/cmake-python-distributions/issues/115
+# https://github.com/skvark/opencv-python/issues/366
+# https://github.com/scikit-build/cmake-python-distributions/issues/96#issuecomment-663062358
+RUN pip3 install scikit-build
+
+RUN git clone https://github.com/scikit-build/cmake-python-distributions.git \
+    && cd cmake-python-distributions/ \
+    && python3 setup.py bdist_wheel
+
+RUN pip3 install cmake-python-distributions/dist/*.whl
+
+RUN pip3 wheel --wheel-dir=/wheels \
+    opencv-python-headless \
+    numpy \
+    imutils \
+    scipy \
+    psutil \
+    Flask \
+    paho-mqtt \
+    PyYAML \
+    matplotlib \
+    click
+
+FROM scratch
+
+COPY --from=build /wheels /wheels

docs/.gitignore

@@ -1,20 +0,0 @@
-# Dependencies
-/node_modules
-
-# Production
-/build
-
-# Generated files
-.docusaurus
-.cache-loader
-
-# Misc
-.DS_Store
-.env.local
-.env.development.local
-.env.test.local
-.env.production.local
-
-npm-debug.log*
-yarn-debug.log*
-yarn-error.log*

docs/README.md

@@ -1,33 +0,0 @@
-# Website
-
-This website is built using [Docusaurus 2](https://v2.docusaurus.io/), a modern static website generator.
-
-## Installation
-
-```console
-yarn install
-```
-
-## Local Development
-
-```console
-yarn start
-```
-
-This command starts a local development server and open up a browser window. Most changes are reflected live without having to restart the server.
-
-## Build
-
-```console
-yarn build
-```
-
-This command generates static content into the `build` directory and can be served using any static contents hosting service.
-
-## Deployment
-
-```console
-GIT_USER=<Your GitHub username> USE_SSH=true yarn deploy
-```
-
-If you are using GitHub pages for hosting, this command is a convenient way to build the website and push to the `gh-pages` branch.

docs/babel.config.js

@@ -1,3 +0,0 @@
-module.exports = {
-  presets: [require.resolve('@docusaurus/core/lib/babel/preset')],
-};

docs/cameras.md

@@ -0,0 +1,21 @@
+# Camera Specific Configuration
+Frigate should work with most RTSP cameras and h264 feeds such as Dahua.
+
+## RTMP Cameras
+The input parameters need to be adjusted for RTMP cameras
+```yaml
+ffmpeg:
+input_args:
+    - -avoid_negative_ts
+    - make_zero
+    - -fflags
+    - nobuffer
+    - -flags
+    - low_delay
+    - -strict
+    - experimental
+    - -fflags
+    - +genpts+discardcorrupt
+    - -use_wallclock_as_timestamps
+    - '1'
+```

docs/docs/configuration/advanced.md

@@ -1,139 +0,0 @@
----
-id: advanced
-title: Advanced
-sidebar_label: Advanced
----
-
-## Advanced configuration
-
-### `motion`
-
-Global motion detection config. These may also be defined at the camera level.
-
-```yaml
-motion:
-  # Optional: The threshold passed to cv2.threshold to determine if a pixel is different enough to be counted as motion. (default: shown below)
-  # 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
-  # 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: 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.
-  delta_alpha: 0.2
-  # Optional: Alpha value passed to cv2.accumulateWeighted when averaging frames to determine the background (default: shown below)
-  # Higher values mean the current frame impacts the average a lot, and a new object will be averaged into the background faster.
-  # 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)
-  # 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
-```
-
-### `detect`
-
-Global object detection settings. These may also be defined at the camera level.
-
-```yaml
-detect:
-  # Optional: Number of frames without a detection before frigate considers an object to be gone. (default: double the frame rate)
-  max_disappeared: 10
-```
-
-### `logger`
-
-Change the default log level for troubleshooting purposes.
-
-```yaml
-logger:
-  # Optional: default log level (default: shown below)
-  default: info
-  # Optional: module by module log level configuration
-  logs:
-    frigate.mqtt: error
-```
-
-Available log levels are: `debug`, `info`, `warning`, `error`, `critical`
-
-Examples of available modules are:
-
-- `frigate.app`
-- `frigate.mqtt`
-- `frigate.edgetpu`
-- `frigate.zeroconf`
-- `detector.<detector_name>`
-- `watchdog.<camera_name>`
-- `ffmpeg.<camera_name>.<sorted_roles>` NOTE: All FFmpeg logs are sent as `error` level.
-
-### `environment_vars`
-
-This section can be used to set environment variables for those unable to modify the environment of the container (ie. within Hass.io)
-
-```yaml
-environment_vars:
-  EXAMPLE_VAR: value
-```
-
-### `database`
-
-Event and clip information is managed in a sqlite database at `/media/frigate/clips/frigate.db`. If that database is deleted, clips will be orphaned and will need to be cleaned up manually. They also won't show up in the Media Browser within HomeAssistant.
-
-If you are storing your clips on a network share (SMB, NFS, etc), you may get a `database is locked` error message on startup. You can customize the location of the database in the config if necessary.
-
-This may need to be in a custom location if network storage is used for clips.
-
-```yaml
-database:
-  path: /media/frigate/clips/frigate.db
-```
-
-### `detectors`
-
-```yaml
-detectors:
-  # Required: name of the detector
-  coral:
-    # Required: type of the detector
-    # Valid values are 'edgetpu' (requires device property below) and 'cpu'. type: edgetpu
-    # Optional: device name as defined here: https://coral.ai/docs/edgetpu/multiple-edgetpu/#using-the-tensorflow-lite-python-api
-    device: usb
-    # Optional: num_threads value passed to the tflite.Interpreter (default: shown below)
-    # This value is only used for CPU types
-    num_threads: 3
-```
-
-### `model`
-
-```yaml
-model:
-  # Required: height of the trained model
-  height: 320
-  # Required: width of the trained model
-  width: 320
-```
-
-## Custom Models
-
-Models for both CPU and EdgeTPU (Coral) are bundled in the image. You can use your own models with volume mounts:
-
-- CPU Model: `/cpu_model.tflite`
-- EdgeTPU Model: `/edgetpu_model.tflite`
-- Labels: `/labelmap.txt`
-
-You also need to update the model width/height in the config if they differ from the defaults.
-
-### Customizing the Labelmap
-
-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. You must retain the same number of labels, but you can change the names. To change:
-
-- Download the [COCO labelmap](https://dl.google.com/coral/canned_models/coco_labels.txt)
-- Modify the label names as desired. For example, change `7 truck` to `7 car`
-- Mount the new file at `/labelmap.txt` in the container with an additional volume
-  ```
-  -v ./config/labelmap.txt:/labelmap.txt
-  ```

docs/docs/configuration/cameras.md

@@ -1,433 +0,0 @@
----
-id: cameras
-title: Cameras
----
-
-## Setting Up Camera Inputs
-
-Up to 4 inputs can be configured for each camera and the role of each input can be mixed and matched based on your needs. This allows you to use a lower resolution stream for object detection, but create clips from a higher resolution stream, or vice versa.
-
-Each role can only be assigned to one input per camera. The options for roles are as follows:
-
-| Role     | Description                                                                          |
-| -------- | ------------------------------------------------------------------------------------ |
-| `detect` | Main feed for object detection                                                       |
-| `clips`  | Clips of events from objects detected in the `detect` feed. [docs](#recording-clips) |
-| `record` | Saves 60 second segments of the video feed. [docs](#247-recordings)                  |
-| `rtmp`   | Broadcast as an RTMP feed for other services to consume. [docs](#rtmp-streams)       |
-
-### Example
-
-```yaml
-mqtt:
-  host: mqtt.server.com
-cameras:
-  back:
-    ffmpeg:
-      inputs:
-        - path: rtsp://viewer:{FRIGATE_RTSP_PASSWORD}@10.0.10.10:554/cam/realmonitor?channel=1&subtype=2
-          roles:
-            - detect
-            - rtmp
-        - path: rtsp://viewer:{FRIGATE_RTSP_PASSWORD}@10.0.10.10:554/live
-          roles:
-            - clips
-            - record
-    width: 1280
-    height: 720
-    fps: 5
-```
-
-## Masks & Zones
-
-### Masks
-Masks are used to ignore initial detection in areas of your camera's field of view.
-
-There are two types of masks available:
-- **Motion masks**: Motion masks are used to prevent unwanted types of motion from triggering detection. Try watching the video feed with `Motion Boxes` enabled to see what may be regularly detected as motion. For example, you want to mask out your timestamp, the sky, rooftops, etc. Keep in mind that this mask only prevents motion from being detected and does not prevent objects from being detected if object detection was started due to motion in unmasked areas. Motion is also used during object tracking to refine the object detection area in the next frame. Over masking will make it more difficult for objects to be tracked. To see this effect, create a mask, and then watch the video feed with `Motion Boxes` enabled again.
-- **Object filter masks**: Object filter masks are used to filter out false positives for a given object type. These should be used to filter any areas where it is not possible for an object of that type to be. The bottom center of the detected object's bounding box is evaluated against the mask. If it is in a masked area, it is assumed to be a false positive. For example, you may want to mask out rooftops, walls, the sky, treetops for people. For cars, masking locations other than the street or your driveway will tell frigate that anything in your yard is a false positive.
-
-To create a poly mask:
-
-1. Visit the [web UI](/usage/web)
-1. Click the camera you wish to create a mask for
-1. Click "Mask & Zone creator"
-1. Click "Add" on the type of mask or zone you would like to create
-1. Click on the camera's latest image to create a masked area. The yaml representation will be updated in real-time
-1. When you've finished creating your mask, click "Copy" and paste the contents into your `config.yaml` file and restart Frigate
-
-Example of a finished row corresponding to the below example image:
-
-```yaml
-motion:
-  mask: '0,461,3,0,1919,0,1919,843,1699,492,1344,458,1346,336,973,317,869,375,866,432'
-```
-
-![poly](/img/example-mask-poly.png)
-
-```yaml
-# Optional: camera level motion config
-motion:
-  # Optional: motion mask
-  # NOTE: see docs for more detailed info on creating masks
-  mask: 0,900,1080,900,1080,1920,0,1920
-```
-
-### Zones
-
-Zones allow you to define a specific area of the frame and apply additional filters for object types so you can determine whether or not an object is within a particular area. Zones cannot have the same name as a camera. If desired, a single zone can include multiple cameras if you have multiple cameras covering the same area by configuring zones with the same name for each camera.
-
-During testing, `draw_zones` should be set in the config to draw the zone on the frames so you can adjust as needed. The zone line will increase in thickness when any object enters the zone.
-
-To create a zone, follow the same steps above for a "Motion mask", but use the section of the web UI for creating a zone instead.
-
-```yaml
-# Optional: zones for this camera
-zones:
-  # Required: name of the zone
-  # NOTE: This must be different than any camera names, but can match with another zone on another
-  #       camera.
-  front_steps:
-    # Required: List of x,y coordinates to define the polygon of the zone.
-    # NOTE: Coordinates can be generated at https://www.image-map.net/
-    coordinates: 545,1077,747,939,788,805
-    # Optional: Zone level object filters.
-    # NOTE: The global and camera filters are applied upstream.
-    filters:
-      person:
-        min_area: 5000
-        max_area: 100000
-        threshold: 0.7
-```
-
-## Objects
-
-```yaml
-# Optional: Camera level object filters config.
-objects:
-  track:
-    - person
-    - car
-  filters:
-    person:
-      min_area: 5000
-      max_area: 100000
-      min_score: 0.5
-      threshold: 0.7
-      # Optional: mask to prevent this object type from being detected in certain areas (default: no mask)
-      # Checks based on the bottom center of the bounding box of the object
-      mask: 0,0,1000,0,1000,200,0,200
-```
-
-## Clips
-
-Frigate can save video clips without any CPU overhead for encoding by simply copying the stream directly with FFmpeg. It leverages FFmpeg's segment functionality to maintain a cache of video for each camera. The cache files are written to disk at `/tmp/cache` and do not introduce memory overhead. When an object is being tracked, it will extend the cache to ensure it can assemble a clip when the event ends. Once the event ends, it again uses FFmpeg to assemble a clip by combining the video clips without any encoding by the CPU. Assembled clips are are saved to `/media/frigate/clips`. Clips are retained according to the retention settings defined on the config for each object type.
-
-:::caution
-Previous versions of frigate included `-vsync drop` in input parameters. This is not compatible with FFmpeg's segment feature and must be removed from your input parameters if you have overrides set.
-:::
-
-```yaml
-clips:
-  # Required: enables clips for the camera (default: shown below)
-  # This value can be set via MQTT and will be updated in startup based on retained value
-  enabled: False
-  # Optional: Number of seconds before the event to include in the clips (default: shown below)
-  pre_capture: 5
-  # Optional: Number of seconds after the event to include in the clips (default: shown below)
-  post_capture: 5
-  # Optional: Objects to save clips for. (default: all tracked objects)
-  objects:
-    - person
-  # Optional: Camera override for retention settings (default: global values)
-  retain:
-    # Required: Default retention days (default: shown below)
-    default: 10
-    # Optional: Per object retention days
-    objects:
-      person: 15
-```
-
-## Snapshots
-
-Frigate can save a snapshot image to `/media/frigate/clips` for each event named as `<camera>-<id>.jpg`.
-
-```yaml
-# Optional: Configuration for the jpg snapshots written to the clips directory for each event
-snapshots:
-  # Optional: Enable writing jpg snapshot to /media/frigate/clips (default: shown below)
-  # This value can be set via MQTT and will be updated in startup based on retained value
-  enabled: False
-  # Optional: print a timestamp on the snapshots (default: shown below)
-  timestamp: False
-  # Optional: draw bounding box on the snapshots (default: shown below)
-  bounding_box: False
-  # Optional: crop the snapshot (default: shown below)
-  crop: False
-  # Optional: height to resize the snapshot to (default: original size)
-  height: 175
-  # Optional: Camera override for retention settings (default: global values)
-  retain:
-    # Required: Default retention days (default: shown below)
-    default: 10
-    # Optional: Per object retention days
-    objects:
-      person: 15
-```
-
-## 24/7 Recordings
-
-24/7 recordings can be enabled and are stored at `/media/frigate/recordings`. The folder structure for the recordings is `YYYY-MM/DD/HH/<camera_name>/MM.SS.mp4`. These recordings are written directly from your camera stream without re-encoding and are available in HomeAssistant's media browser. Each camera supports a configurable retention policy in the config.
-
-:::caution
-Previous versions of frigate included `-vsync drop` in input parameters. This is not compatible with FFmpeg's segment feature and must be removed from your input parameters if you have overrides set.
-:::
-
-```yaml
-# Optional: 24/7 recording configuration
-record:
-  # Optional: Enable recording (default: global setting)
-  enabled: False
-  # Optional: Number of days to retain (default: global setting)
-  retain_days: 30
-```
-
-## RTMP streams
-
-Frigate can re-stream your video feed as a RTMP feed for other applications such as HomeAssistant to utilize it at `rtmp://<frigate_host>/live/<camera_name>`. Port 1935 must be open. This allows you to use a video feed for detection in frigate and HomeAssistant live view at the same time without having to make two separate connections to the camera. The video feed is copied from the original video feed directly to avoid re-encoding. This feed does not include any annotation by Frigate.
-
-Some video feeds are not compatible with RTMP. If you are experiencing issues, check to make sure your camera feed is h264 with AAC audio. If your camera doesn't support a compatible format for RTMP, you can use the ffmpeg args to re-encode it on the fly at the expense of increased CPU utilization.
-
-## Full example
-
-The following is a full example of all of the options together for a camera configuration
-
-```yaml
-cameras:
-  # Required: name of the camera
-  back:
-    # Required: ffmpeg settings for the camera
-    ffmpeg:
-      # 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 {}
-        - 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,clips,rtmp
-          # NOTICE: In addition to assigning the record, clips, and rtmp roles,
-          # they must also be enabled in the camera config.
-          roles:
-            - detect
-            - rtmp
-          # Optional: stream specific global args (default: inherit)
-          global_args:
-          # Optional: stream specific hwaccel args (default: inherit)
-          hwaccel_args:
-          # Optional: stream specific input args (default: inherit)
-          input_args:
-
-      # Optional: camera specific global args (default: inherit)
-      global_args:
-      # Optional: camera specific hwaccel args (default: inherit)
-      hwaccel_args:
-      # Optional: camera specific input args (default: inherit)
-      input_args:
-      # Optional: camera specific output args (default: inherit)
-      output_args:
-
-    # Required: width of the frame for the input with the detect role
-    width: 1280
-    # Required: height of the frame for the input with the detect role
-    height: 720
-    # Optional: desired fps for your camera for the input with the detect role
-    # NOTE: Recommended value of 5. Ideally, try and reduce your FPS on the camera.
-    #       Frigate will attempt to autodetect if not specified.
-    fps: 5
-
-    # Optional: camera level motion config
-    motion:
-      # Optional: motion mask
-      # NOTE: see docs for more detailed info on creating masks
-      mask: 0,900,1080,900,1080,1920,0,1920
-
-    # Optional: timeout for highest scoring image before allowing it
-    # to be replaced by a newer image. (default: shown below)
-    best_image_timeout: 60
-
-    # Optional: zones for this camera
-    zones:
-      # Required: name of the zone
-      # NOTE: This must be different than any camera names, but can match with another zone on another
-      #       camera.
-      front_steps:
-        # Required: List of x,y coordinates to define the polygon of the zone.
-        # NOTE: Coordinates can be generated at https://www.image-map.net/
-        coordinates: 545,1077,747,939,788,805
-        # Optional: Zone level object filters.
-        # NOTE: The global and camera filters are applied upstream.
-        filters:
-          person:
-            min_area: 5000
-            max_area: 100000
-            threshold: 0.7
-
-    # Optional: Camera level detect settings
-    detect:
-      # Optional: enables detection for the camera (default: True)
-      # This value can be set via MQTT and will be updated in startup based on retained value
-      enabled: True
-      # Optional: Number of frames without a detection before frigate considers an object to be gone. (default: double the frame rate)
-      max_disappeared: 10
-
-    # Optional: save clips configuration
-    clips:
-      # Required: enables clips for the camera (default: shown below)
-      # This value can be set via MQTT and will be updated in startup based on retained value
-      enabled: False
-      # Optional: Number of seconds before the event to include in the clips (default: shown below)
-      pre_capture: 5
-      # Optional: Number of seconds after the event to include in the clips (default: shown below)
-      post_capture: 5
-      # Optional: Objects to save clips for. (default: all tracked objects)
-      objects:
-        - person
-      # Optional: Camera override for retention settings (default: global values)
-      retain:
-        # Required: Default retention days (default: shown below)
-        default: 10
-        # Optional: Per object retention days
-        objects:
-          person: 15
-
-    # Optional: 24/7 recording configuration
-    record:
-      # Optional: Enable recording (default: global setting)
-      enabled: False
-      # Optional: Number of days to retain (default: global setting)
-      retain_days: 30
-
-    # Optional: RTMP re-stream configuration
-    rtmp:
-      # Required: Enable the live stream (default: True)
-      enabled: True
-
-    # Optional: Configuration for the jpg snapshots written to the clips directory for each event
-    snapshots:
-      # Optional: Enable writing jpg snapshot to /media/frigate/clips (default: shown below)
-      # This value can be set via MQTT and will be updated in startup based on retained value
-      enabled: False
-      # Optional: print a timestamp on the snapshots (default: shown below)
-      timestamp: False
-      # Optional: draw bounding box on the snapshots (default: shown below)
-      bounding_box: False
-      # Optional: crop the snapshot (default: shown below)
-      crop: False
-      # Optional: height to resize the snapshot to (default: original size)
-      height: 175
-      # Optional: Camera override for retention settings (default: global values)
-      retain:
-        # Required: Default retention days (default: shown below)
-        default: 10
-        # Optional: Per object retention days
-        objects:
-          person: 15
-
-    # Optional: Configuration for the jpg snapshots published via MQTT
-    mqtt:
-      # Optional: Enable publishing snapshot via mqtt for camera (default: shown below)
-      # NOTE: Only applies to publishing image data to MQTT via 'frigate/<camera_name>/<object_name>/snapshot'.
-      # All other messages will still be published.
-      enabled: True
-      # Optional: print a timestamp on the snapshots (default: shown below)
-      timestamp: True
-      # Optional: draw bounding box on the snapshots (default: shown below)
-      bounding_box: True
-      # Optional: crop the snapshot (default: shown below)
-      crop: True
-      # Optional: height to resize the snapshot to (default: shown below)
-      height: 270
-
-    # Optional: Camera level object filters config.
-    objects:
-      track:
-        - person
-        - car
-      filters:
-        person:
-          min_area: 5000
-          max_area: 100000
-          min_score: 0.5
-          threshold: 0.7
-          # Optional: mask to prevent this object type from being detected in certain areas (default: no mask)
-          # Checks based on the bottom center of the bounding box of the object
-          mask: 0,0,1000,0,1000,200,0,200
-```
-
-## Camera specific configuration
-
-### RTMP Cameras
-
-The input parameters need to be adjusted for RTMP cameras
-
-```yaml
-ffmpeg:
-  input_args:
-    - -avoid_negative_ts
-    - make_zero
-    - -fflags
-    - nobuffer
-    - -flags
-    - low_delay
-    - -strict
-    - experimental
-    - -fflags
-    - +genpts+discardcorrupt
-    - -use_wallclock_as_timestamps
-    - '1'
-```
-
-### Reolink 410/520 (possibly others)
-Several users have reported success with the rtmp video from Reolink cameras.
-
-```yaml
-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'
-```
-
-
-### Blue Iris RTSP Cameras
-
-You will need to remove `nobuffer` flag for Blue Iris RTSP cameras
-
-```yaml
-ffmpeg:
-  input_args:
-    - -avoid_negative_ts
-    - make_zero
-    - -flags
-    - low_delay
-    - -strict
-    - experimental
-    - -fflags
-    - +genpts+discardcorrupt
-    - -rtsp_transport
-    - tcp
-    - -stimeout
-    - '5000000'
-    - -use_wallclock_as_timestamps
-    - '1'
-```

docs/docs/configuration/detectors.md

@@ -1,53 +0,0 @@
----
-id: detectors
-title: Detectors
----
-
-The default config will look for a USB Coral device. If you do not have a Coral, you will need to configure a CPU detector. If you have PCI or multiple Coral devices, you need to configure your detector devices in the config file. When using multiple detectors, they run in dedicated processes, but pull from a common queue of requested detections across all cameras.
-
-Frigate supports `edgetpu` and `cpu` as detector types. The device value should be specified according to the [Documentation for the TensorFlow Lite Python API](https://coral.ai/docs/edgetpu/multiple-edgetpu/#using-the-tensorflow-lite-python-api).
-
-**Note**: There is no support for Nvidia GPUs to perform object detection with tensorflow. It can be used for ffmpeg decoding, but not object detection.
-
-Single USB Coral:
-
-```yaml
-detectors:
-  coral:
-    type: edgetpu
-    device: usb
-```
-
-Multiple USB Corals:
-
-```yaml
-detectors:
-  coral1:
-    type: edgetpu
-    device: usb:0
-  coral2:
-    type: edgetpu
-    device: usb:1
-```
-
-Mixing Corals:
-
-```yaml
-detectors:
-  coral_usb:
-    type: edgetpu
-    device: usb
-  coral_pci:
-    type: edgetpu
-    device: pci
-```
-
-CPU Detectors (not recommended):
-
-```yaml
-detectors:
-  cpu1:
-    type: cpu
-  cpu2:
-    type: cpu
-```

docs/docs/configuration/false_positives.md

@@ -1,19 +0,0 @@
----
-id: false_positives
-title: Reducing false positives
----
-
-Tune your object filters to adjust false positives: `min_area`, `max_area`, `min_score`, `threshold`.
-
-For object filters in your configuration, any single detection below `min_score` will be ignored as a false positive. `threshold` is based on the median of the history of scores (padded to 3 values) for a tracked object. Consider the following frames when `min_score` is set to 0.6 and threshold is set to 0.85:
-
-| Frame | Current Score | Score History                     | Computed Score | Detected Object |
-| ----- | ------------- | --------------------------------- | -------------- | --------------- |
-| 1     | 0.7           | 0.0, 0, 0.7                       | 0.0            | No              |
-| 2     | 0.55          | 0.0, 0.7, 0.0                     | 0.0            | No              |
-| 3     | 0.85          | 0.7, 0.0, 0.85                    | 0.7            | No              |
-| 4     | 0.90          | 0.7, 0.85, 0.95, 0.90             | 0.875          | Yes             |
-| 5     | 0.88          | 0.7, 0.85, 0.95, 0.90, 0.88       | 0.88           | Yes             |
-| 6     | 0.95          | 0.7, 0.85, 0.95, 0.90, 0.88, 0.95 | 0.89           | Yes             |
-
-In frame 2, the score is below the `min_score` value, so frigate ignores it and it becomes a 0.0. The computed score is the median of the score history (padding to at least 3 values), and only when that computed score crosses the `threshold` is the object marked as a true positive. That happens in frame 4 in the example.

docs/docs/configuration/index.md

@@ -1,138 +0,0 @@
----
-id: index
-title: Configuration
----
-
-HassOS users can manage their configuration directly in the addon Configuration tab. For other installations, the default location for the config file is `/config/config.yml`. This can be overridden with the `CONFIG_FILE` environment variable. Camera specific ffmpeg parameters are documented [here](cameras.md).
-
-It is recommended to start with a minimal configuration and add to it:
-
-```yaml
-mqtt:
-  host: mqtt.server.com
-cameras:
-  back:
-    ffmpeg:
-      inputs:
-        - path: rtsp://viewer:{FRIGATE_RTSP_PASSWORD}@10.0.10.10:554/cam/realmonitor?channel=1&subtype=2
-          roles:
-            - detect
-            - rtmp
-    width: 1280
-    height: 720
-    fps: 5
-```
-
-## Required
-
-## `mqtt`
-
-```yaml
-mqtt:
-  # Required: host name
-  host: mqtt.server.com
-  # Optional: port (default: shown below)
-  port: 1883
-  # Optional: topic prefix (default: shown below)
-  # WARNING: must be unique if you are running multiple instances
-  topic_prefix: frigate
-  # Optional: client id (default: shown below)
-  # WARNING: must be unique if you are running multiple instances
-  client_id: frigate
-  # Optional: user
-  user: mqtt_user
-  # Optional: password
-  # NOTE: Environment variables that begin with 'FRIGATE_' may be referenced in {}.
-  #       eg. password: '{FRIGATE_MQTT_PASSWORD}'
-  password: password
-  # Optional: interval in seconds for publishing stats (default: shown below)
-  stats_interval: 60
-```
-
-## `cameras`
-
-Each of your cameras must be configured. The following is the minimum required to register a camera in Frigate. Check the [camera configuration page](cameras.md) for a complete list of options.
-
-```yaml
-cameras:
-  # Name of your camera
-  front_door:
-    ffmpeg:
-      inputs:
-        - path: rtsp://viewer:{FRIGATE_RTSP_PASSWORD}@10.0.10.10:554/cam/realmonitor?channel=1&subtype=2
-          roles:
-            - detect
-            - rtmp
-    width: 1280
-    height: 720
-    fps: 5
-```
-
-## Optional
-
-### `clips`
-
-```yaml
-clips:
-  # 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 cache
-  #       will begin to expire and the resulting clip will be the last x seconds of the event.
-  max_seconds: 300
-  # Optional: size of tmpfs mount to create for cache files (default: not set)
-  # mount -t tmpfs -o size={tmpfs_cache_size} tmpfs /tmp/cache
-  # NOTICE: Addon users must have Protection mode disabled for the addon when using this setting.
-  # Also, if you have mounted a tmpfs volume through docker, this value should not be set in your config.
-  tmpfs_cache_size: 256m
-  # Optional: Retention settings for clips (default: shown below)
-  retain:
-    # Required: Default retention days (default: shown below)
-    default: 10
-    # Optional: Per object retention days
-    objects:
-      person: 15
-```
-
-### `ffmpeg`
-
-```yaml
-ffmpeg:
-  # Optional: global ffmpeg args (default: shown below)
-  global_args: -hide_banner -loglevel warning
-  # Optional: global hwaccel args (default: shown below)
-  # NOTE: See hardware acceleration docs for your specific device
-  hwaccel_args: []
-  # Optional: global input args (default: shown below)
-  input_args: -avoid_negative_ts make_zero -fflags +genpts+discardcorrupt -rtsp_transport tcp -stimeout 5000000 -use_wallclock_as_timestamps 1
-  # Optional: global output args
-  output_args:
-    # Optional: output args for detect streams (default: shown below)
-    detect: -f rawvideo -pix_fmt yuv420p
-    # Optional: output args for record streams (default: shown below)
-    record: -f segment -segment_time 60 -segment_format mp4 -reset_timestamps 1 -strftime 1 -c copy -an
-    # Optional: output args for clips streams (default: shown below)
-    clips: -f segment -segment_time 10 -segment_format mp4 -reset_timestamps 1 -strftime 1 -c copy -an
-    # Optional: output args for rtmp streams (default: shown below)
-    rtmp: -c copy -f flv
-```
-
-### `objects`
-
-Can be overridden at the camera level
-
-```yaml
-objects:
-  # Optional: list of objects to track from labelmap.txt (default: shown below)
-  track:
-    - person
-  # Optional: filters to reduce false positives for specific object types
-  filters:
-    person:
-      # Optional: minimum width*height of the bounding box for the detected object (default: 0)
-      min_area: 5000
-      # Optional: maximum width*height of the bounding box for the detected object (default: 24000000)
-      max_area: 100000
-      # Optional: minimum score for the object to initiate tracking (default: shown below)
-      min_score: 0.5
-      # Optional: minimum decimal percentage for tracked object's computed score to be considered a true positive (default: shown below)
-      threshold: 0.7
-```

docs/docs/configuration/optimizing.md

@@ -1,72 +0,0 @@
----
-id: optimizing
-title: Optimizing performance
----
-
-- **Google Coral**: It is strongly recommended to use a Google Coral, but Frigate will fall back to CPU in the event one is not found. Offloading TensorFlow to the Google Coral is an order of magnitude faster and will reduce your CPU load dramatically. A $60 device will outperform $2000 CPU. Frigate should work with any supported Coral device from https://coral.ai
-- **Resolution**: For the `detect` input, choose a camera resolution where the smallest object you want to detect barely fits inside a 300x300px square. The model used by Frigate is trained on 300x300px images, so you will get worse performance and no improvement in accuracy by using a larger resolution since Frigate resizes the area where it is looking for objects to 300x300 anyway.
-- **FPS**: 5 frames per second should be adequate. Higher frame rates will require more CPU usage without improving detections or accuracy. Reducing the frame rate on your camera will have the greatest improvement on system resources.
-- **Hardware Acceleration**: Make sure you configure the `hwaccel_args` for your hardware. They provide a significant reduction in CPU usage if they are available.
-- **Masks**: Masks can be used to ignore motion and reduce your idle CPU load. If you have areas with regular motion such as timestamps or trees blowing in the wind, frigate will constantly try to determine if that motion is from a person or other object you are tracking. Those detections not only increase your average CPU usage, but also clog the pipeline for detecting objects elsewhere. If you are experiencing high values for `detection_fps` when no objects of interest are in the cameras, you should use masks to tell frigate to ignore movement from trees, bushes, timestamps, or any part of the image where detections should not be wasted looking for objects.
-
-### FFmpeg Hardware Acceleration
-
-Frigate works on Raspberry Pi 3b/4 and x86 machines. It is recommended to update your configuration to enable hardware accelerated decoding in ffmpeg. Depending on your system, these parameters may not be compatible.
-
-Raspberry Pi 3/4 (32-bit OS)
-**NOTICE**: If you are using the addon, ensure you turn off `Protection mode` for hardware acceleration.
-
-```yaml
-ffmpeg:
-  hwaccel_args:
-    - -c:v
-    - h264_mmal
-```
-
-Raspberry Pi 3/4 (64-bit OS)
-**NOTICE**: If you are using the addon, ensure you turn off `Protection mode` for hardware acceleration.
-
-```yaml
-ffmpeg:
-  hwaccel_args:
-    - -c:v
-    - h264_v4l2m2m
-```
-
-Intel-based CPUs (<10th Generation) via Quicksync (https://trac.ffmpeg.org/wiki/Hardware/QuickSync)
-
-```yaml
-ffmpeg:
-  hwaccel_args:
-    - -hwaccel
-    - vaapi
-    - -hwaccel_device
-    - /dev/dri/renderD128
-    - -hwaccel_output_format
-    - yuv420p
-```
-
-Intel-based CPUs (>=10th Generation) via Quicksync (https://trac.ffmpeg.org/wiki/Hardware/QuickSync)
-
-```yaml
-ffmpeg:
-  hwaccel_args:
-    - -hwaccel
-    - qsv
-    - -qsv_device
-    - /dev/dri/renderD128
-```
-
-AMD/ATI GPUs (Radeon HD 2000 and newer GPUs) via libva-mesa-driver (https://trac.ffmpeg.org/wiki/Hardware/QuickSync)
-**Note:** You also need to set `LIBVA_DRIVER_NAME=radeonsi` as an environment variable on the container.
-
-```yaml
-ffmpeg:
-  hwaccel_args:
-    - -hwaccel
-    - vaapi
-    - -hwaccel_device
-    - /dev/dri/renderD128
-```
-
-Nvidia GPU based decoding via NVDEC is supported, but requires special configuration. See the [nvidia NVDEC documentation](/configuration/nvdec) for more details.

docs/docs/hardware.md

@@ -1,20 +0,0 @@
----
-id: hardware
-title: Recommended hardware
----
-
-## Cameras
-
-Cameras that output H.264 video and AAC audio will offer the most compatibility with all features of Frigate and HomeAssistant. It is also helpful if your camera supports multiple substreams to allow different resolutions to be used for detection, streaming, clips, and recordings without re-encoding.
-
-## Computer
-
-| Name                    | Inference Speed | Notes                                                                                                                         |
-| ----------------------- | --------------- | ----------------------------------------------------------------------------------------------------------------------------- |
-| Atomic Pi               | 16ms            | Good option for a dedicated low power board with a small number of cameras. Can leverage Intel QuickSync for stream decoding. |
-| Intel NUC NUC7i3BNK     | 8-10ms          | Great performance. Can handle many cameras at 5fps depending on typical amounts of motion.                                    |
-| BMAX B2 Plus            | 10-12ms         | Good balance of performance and cost. Also capable of running many other services at the same time as frigate.                |
-| Minisforum GK41         | 9-10ms          | Great alternative to a NUC with dual Gigabit NICs. Easily handles several 1080p cameras.                                      |
-| Raspberry Pi 3B (32bit) | 60ms            | Can handle a small number of cameras, but the detection speeds are slow due to USB 2.0.                                       |
-| Raspberry Pi 4 (32bit)  | 15-20ms         | Can handle a small number of cameras. The 2GB version runs fine.                                                              |
-| Raspberry Pi 4 (64bit)  | 10-15ms         | Can handle a small number of cameras. The 2GB version runs fine.                                                              |

docs/docs/how-it-works.md

@@ -1,13 +0,0 @@
----
-id: how-it-works
-title: How Frigate Works
-sidebar_label: How it works
----
-
-Frigate is designed to minimize resource and maximize performance by only looking for objects when and where it is necessary
-
-![Diagram](/img/diagram.png)
-
-1. Look for Motion
-2. Calculate Detection Regions
-3. Run Object Detection

docs/docs/index.md

@@ -1,25 +0,0 @@
----
-id: index
-title: Frigate
-sidebar_label: Features
-slug: /
----
-
-A complete and local NVR designed for HomeAssistant with AI object detection. Uses OpenCV and Tensorflow to perform realtime object detection locally for IP cameras.
-
-Use of a [Google Coral Accelerator](https://coral.ai/products/) is optional, but highly recommended. The Coral will outperform even the best CPUs and can process 100+ FPS with very little overhead.
-
-- Tight integration with HomeAssistant via a [custom component](https://github.com/blakeblackshear/frigate-hass-integration)
-- Designed to minimize resource use and maximize performance by only looking for objects when and where it is necessary
-- Leverages multiprocessing heavily with an emphasis on realtime over processing every frame
-- Uses a very low overhead motion detection to determine where to run object detection
-- Object detection with TensorFlow runs in separate processes for maximum FPS
-- Communicates over MQTT for easy integration into other systems
-- 24/7 recording
-- Re-streaming via RTMP to reduce the number of connections to your camera
-
-## Screenshots
-
-![Media Browser](/img/media_browser.png)
-
-![Notification](/img/notification.png)

docs/docs/installation.md

@@ -1,122 +0,0 @@
----
-id: installation
-title: Installation
----
-
-Frigate is a Docker container that can be run on any Docker host including as a [HassOS Addon](https://www.home-assistant.io/addons/). See instructions below for installing the HassOS addon.
-
-For HomeAssistant users, there is also a [custom component (aka integration)](https://github.com/blakeblackshear/frigate-hass-integration). This custom component adds tighter integration with HomeAssistant by automatically setting up camera entities, sensors, media browser for clips and recordings, and a public API to simplify notifications.
-
-Note that HassOS Addons and custom components are different things. If you are already running Frigate with Docker directly, you do not need the Addon since the Addon would run another instance of Frigate.
-
-## HassOS Addon
-
-HassOS users can install via the addon repository. Frigate requires an MQTT server.
-
-1. Navigate to Supervisor > Add-on Store > Repositories
-1. Add https://github.com/blakeblackshear/frigate-hass-addons
-1. Setup your configuration in the `Configuration` tab
-1. Start the addon container
-1. If you are using hardware acceleration for ffmpeg, you will need to disable "Protection mode"
-
-## Docker
-
-Make sure you choose the right image for your architecture:
-
-|Arch|Image Name|
-|-|-|
-|amd64|blakeblackshear/frigate:stable-amd64|
-|amd64nvidia|blakeblackshear/frigate:stable-amd64nvidia|
-|armv7|blakeblackshear/frigate:stable-armv7|
-|aarch64|blakeblackshear/frigate:stable-aarch64|
-
-It is recommended to run with docker-compose:
-
-```yaml
-version: '3.6'
-services:
-  frigate:
-    container_name: frigate
-    restart: unless-stopped
-    privileged: true
-    image: blakeblackshear/frigate:0.8.0-beta2-amd64
-    volumes:
-      - /dev/bus/usb:/dev/bus/usb
-      - /etc/localtime:/etc/localtime:ro
-      - <path_to_config>:/config
-      - <path_to_directory_for_clips>:/media/frigate/clips
-      - <path_to_directory_for_recordings>:/media/frigate/recordings
-      - type: tmpfs # Optional: 1GB of memory, reduces SSD/SD Card wear
-        target: /tmp/cache
-        tmpfs:
-          size: 1000000000
-    ports:
-      - '5000:5000'
-      - '1935:1935' # RTMP feeds
-    environment:
-      FRIGATE_RTSP_PASSWORD: 'password'
-```
-
-If you can't use docker compose, you can run the container with something similar to this:
-
-```bash
-docker run --rm \
---name frigate \
---privileged \
---mount type=tmpfs,target=/tmp/cache,tmpfs-size=1000000000 \
--v /dev/bus/usb:/dev/bus/usb \
--v <path_to_directory_for_clips>:/media/frigate/clips \
--v <path_to_directory_for_recordings>:/media/frigate/recordings \
--v <path_to_config>:/config:ro \
--v /etc/localtime:/etc/localtime:ro \
--e FRIGATE_RTSP_PASSWORD='password' \
--p 5000:5000 \
--p 1935:1935 \
-blakeblackshear/frigate:0.8.0-beta2-amd64
-```
-
-### Calculating shm-size
-
-The default shm-size of 64m is fine for setups with 3 or less 1080p cameras. If frigate is exiting with "Bus error" messages, it could be 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:
-
-```
-(width * height * 1.5 * 7 + 270480)/1048576 = <shm size in mb>
-```
-
-The shm size cannot be set per container for HomeAssistant Addons. You must set `default-shm-size` in `/etc/docker/daemon.json` to increase the default shm size. This will increase the shm size for all of your docker containers. This may or may not cause issues with your setup. https://docs.docker.com/engine/reference/commandline/dockerd/#daemon-configuration-file
-
-## Kubernetes
-
-Use the [helm chart](https://github.com/blakeblackshear/blakeshome-charts/tree/master/charts/frigate).
-
-## Virtualization
-
-For ideal performance, Frigate needs access to underlying hardware for the Coral and GPU devices for ffmpeg decoding. Running Frigate in a VM on top of Proxmox, ESXi, Virtualbox, etc. is not recommended. The virtualization layer typically introduces a sizable amount of overhead for communication with Coral devices.
-
-### Proxmox
-
-Some people have had success running Frigate in LXC directly with the following config:
-
-```
-arch: amd64
-cores: 2
-features: nesting=1
-hostname: FrigateLXC
-memory: 4096
-net0: name=eth0,bridge=vmbr0,firewall=1,hwaddr=2E:76:AE:5A:58:48,ip=dhcp,ip6=auto,type=veth
-ostype: debian
-rootfs: local-lvm:vm-115-disk-0,size=12G
-swap: 512
-lxc.cgroup.devices.allow: c 189:385 rwm
-lxc.mount.entry: /dev/dri/renderD128 dev/dri/renderD128 none bind,optional,create=file
-lxc.mount.entry: /dev/bus/usb/004/002 dev/bus/usb/004/002 none bind,optional,create=file
-lxc.apparmor.profile: unconfined
-lxc.cgroup.devices.allow: a
-lxc.cap.drop:
-```
-
-### ESX
-For details on running Frigate under ESX, see details [here](https://github.com/blakeblackshear/frigate/issues/305).
-

docs/docs/mdx.md

@@ -1,17 +0,0 @@
----
-id: mdx
-title: Powered by MDX
----
-
-You can write JSX and use React components within your Markdown thanks to [MDX](https://mdxjs.com/).
-
-export const Highlight = ({children, color}) => ( <span style={{
-      backgroundColor: color,
-      borderRadius: '2px',
-      color: '#fff',
-      padding: '0.2rem',
-    }}>{children}</span> );
-
-<Highlight color="#25c2a0">Docusaurus green</Highlight> and <Highlight color="#1877F2">Facebook blue</Highlight> are my favorite colors.
-
-I can write **Markdown** alongside my _JSX_!

docs/docs/troubleshooting.md

@@ -1,20 +0,0 @@
----
-id: troubleshooting
-title: Troubleshooting and FAQ
----
-
-### How can I get sound or audio in my clips and recordings?
-By default, Frigate removes audio from clips and 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 default ffmpeg args are shown [here](configuration/index#ffmpeg).
-
-### 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)
-
-## "[mov,mp4,m4a,3gp,3g2,mj2 @ 0x5639eeb6e140] moov atom not found"
-
-These messages in the logs are expected in certain situations. Frigate checks the integrity of the video cache before assembling clips. Occasionally these cached files will be invalid and cleaned up automatically.
-
-## "On connect called"
-
-If you see repeated "On connect called" messages in your config, check for another instance of frigate. This happens when multiple frigate containers are trying to connect to mqtt with the same client_id.

docs/docs/usage/api.md

@@ -1,181 +0,0 @@
----
-id: api
-title: HTTP API
----
-
-A web server is available on port 5000 with the following endpoints.
-
-### `/api/<camera_name>`
-
-An mjpeg stream for debugging. Keep in mind the mjpeg endpoint is for debugging only and will put additional load on the system when in use.
-
-Accepts the following query string parameters:
-
-| param       | Type | Description                                                        |
-| ----------- | ---- | ------------------------------------------------------------------ |
-| `fps`       | int  | Frame rate                                                         |
-| `h`         | int  | Height in pixels                                                   |
-| `bbox`      | int  | Show bounding boxes for detected objects (0 or 1)                  |
-| `timestamp` | int  | Print the timestamp in the upper left (0 or 1)                     |
-| `zones`     | int  | Draw the zones on the image (0 or 1)                               |
-| `mask`      | int  | Overlay the mask on the image (0 or 1)                             |
-| `motion`    | int  | Draw blue boxes for areas with detected motion (0 or 1)            |
-| `regions`   | int  | Draw green boxes for areas where object detection was run (0 or 1) |
-
-You can access a higher resolution mjpeg stream by appending `h=height-in-pixels` to the endpoint. For example `http://localhost:5000/back?h=1080`. You can also increase the FPS by appending `fps=frame-rate` to the URL such as `http://localhost:5000/back?fps=10` or both with `?fps=10&h=1000`.
-
-### `/api/<camera_name>/<object_name>/best.jpg[?h=300&crop=1]`
-
-The best snapshot for any object type. It is a full resolution image by default.
-
-Example parameters:
-
-- `h=300`: resizes the image to 300 pixes tall
-- `crop=1`: crops the image to the region of the detection rather than returning the entire image
-
-### `/api/<camera_name>/latest.jpg[?h=300]`
-
-The most recent frame that frigate has finished processing. It is a full resolution image by default.
-
-Accepts the following query string parameters:
-
-| param       | Type | Description                                                        |
-| ----------- | ---- | ------------------------------------------------------------------ |
-| `h`         | int  | Height in pixels                                                   |
-| `bbox`      | int  | Show bounding boxes for detected objects (0 or 1)                  |
-| `timestamp` | int  | Print the timestamp in the upper left (0 or 1)                     |
-| `zones`     | int  | Draw the zones on the image (0 or 1)                               |
-| `mask`      | int  | Overlay the mask on the image (0 or 1)                             |
-| `motion`    | int  | Draw blue boxes for areas with detected motion (0 or 1)            |
-| `regions`   | int  | Draw green boxes for areas where object detection was run (0 or 1) |
-
-Example parameters:
-
-- `h=300`: resizes the image to 300 pixes tall
-
-### `/api/stats`
-
-Contains some granular debug info that can be used for sensors in HomeAssistant.
-
-Sample response:
-
-```json
-{
-  /* Per Camera Stats */
-  "back": {
-    /***************
-     * Frames per second being consumed from your camera. If this is higher
-     * than it is supposed to be, you should set -r FPS in your input_args.
-     * camera_fps = process_fps + skipped_fps
-     ***************/
-    "camera_fps": 5.0,
-    /***************
-     * Number of times detection is run per second. This can be higher than
-     * your camera FPS because frigate often looks at the same frame multiple times
-     * or in multiple locations
-     ***************/
-    "detection_fps": 1.5,
-    /***************
-     * PID for the ffmpeg process that consumes this camera
-     ***************/
-    "capture_pid": 27,
-    /***************
-     * PID for the process that runs detection for this camera
-     ***************/
-    "pid": 34,
-    /***************
-     * Frames per second being processed by frigate.
-     ***************/
-    "process_fps": 5.1,
-    /***************
-     * Frames per second skip for processing by frigate.
-     ***************/
-    "skipped_fps": 0.0
-  },
-  /***************
-   * Sum of detection_fps across all cameras and detectors.
-   * This should be the sum of all detection_fps values from cameras.
-   ***************/
-  "detection_fps": 5.0,
-  /* Detectors Stats */
-  "detectors": {
-    "coral": {
-      /***************
-       * Timestamp when object detection started. If this value stays non-zero and constant
-       * for a long time, that means the detection process is stuck.
-       ***************/
-      "detection_start": 0.0,
-      /***************
-       * Time spent running object detection in milliseconds.
-       ***************/
-      "inference_speed": 10.48,
-      /***************
-       * PID for the shared process that runs object detection on the Coral.
-       ***************/
-      "pid": 25321
-    }
-  },
-  "service": {
-    /* Uptime in seconds */
-    "uptime": 10,
-    "version": "0.8.0-8883709"
-  }
-}
-```
-
-### `/api/config`
-
-A json representation of your configuration
-
-### `/api/version`
-
-Version info
-
-### `/api/events`
-
-Events from the database. Accepts the following query string parameters:
-
-| param                | Type | Description                                   |
-| -------------------- | ---- | --------------------------------------------- |
-| `before`             | int  | Epoch time                                    |
-| `after`              | int  | Epoch time                                    |
-| `camera`             | str  | Camera name                                   |
-| `label`              | str  | Label name                                    |
-| `zone`               | str  | Zone name                                     |
-| `limit`              | int  | Limit the number of events returned           |
-| `has_snapshot`       | int  | Filter to events that have snapshots (0 or 1) |
-| `has_clip`           | int  | Filter to events that have clips (0 or 1)     |
-| `include_thumbnails` | int  | Include thumbnails in the response (0 or 1)   |
-
-### `/api/events/summary`
-
-Returns summary data for events in the database. Used by the HomeAssistant integration.
-
-### `/api/events/<id>`
-
-Returns data for a single event.
-
-### `/api/events/<id>/thumbnail.jpg`
-
-Returns a thumbnail for the event id optimized for notifications. Works while the event is in progress and after completion. Passing `?format=android` will convert the thumbnail to 2:1 aspect ratio.
-
-### `/api/events/<id>/snapshot.jpg`
-
-Returns the snapshot image for the event id. Works while the event is in progress and after completion.
-
-Accepts the following query string parameters, but they are only applied when an event is in progress. After the event is completed, the saved snapshot is returned from disk without modification:
-
-| param       | Type | Description                                       |
-| ----------- | ---- | ------------------------------------------------- |
-| `h`         | int  | Height in pixels                                  |
-| `bbox`      | int  | Show bounding boxes for detected objects (0 or 1) |
-| `timestamp` | int  | Print the timestamp in the upper left (0 or 1)    |
-| `crop`      | int  | Crop the snapshot to the (0 or 1)                 |
-
-### `/clips/<camera>-<id>.mp4`
-
-Video clip for the given camera and event id.
-
-### `/clips/<camera>-<id>.jpg`
-
-JPG snapshot for the given camera and event id.

docs/docs/usage/home-assistant.md

@@ -1,120 +0,0 @@
----
-id: home-assistant
-title: Integration with Home Assistant
-sidebar_label: Home Assistant
----
-
-The best way to integrate with HomeAssistant is to use the [official integration](https://github.com/blakeblackshear/frigate-hass-integration). When configuring the integration, you will be asked for the `Host` of your frigate instance. This value should be the url you use to access Frigate in the browser and will look like `http://<host>:5000/`. If you are using HassOS with the addon, the host should be `http://ccab4aaf-frigate:5000` (or `http://ccab4aaf-frigate-beta:5000` if your are using the beta version of the addon). HomeAssistant needs access to port 5000 (api) and 1935 (rtmp) for all features. The integration will setup the following entities within HomeAssistant:
-
-## Sensors:
-
-- Stats to monitor frigate performance
-- Object counts for all zones and cameras
-
-## Cameras:
-
-- Cameras for image of the last detected object for each camera
-- Camera entities with stream support (requires RTMP)
-
-## Media Browser:
-
-- Rich UI with thumbnails for browsing event clips
-- Rich UI for browsing 24/7 recordings by month, day, camera, time
-
-## API:
-
-- Notification API with public facing endpoints for images in notifications
-
-### Notifications
-
-Frigate publishes event information in the form of a change feed via MQTT. This allows lots of customization for notifications to meet your needs. Event changes are published with `before` and `after` information as shown [here](#frigateevents).
-
-Here is a simple example of a notification automation of events which will update the existing notification for each change. This means the image you see in the notification will update as frigate finds a "better" image.
-
-```yaml
-automation:
-  - alias: Notify of events
-    trigger:
-      platform: mqtt
-      topic: frigate/events
-    action:
-      - service: notify.mobile_app_pixel_3
-        data_template:
-          message: 'A {{trigger.payload_json["after"]["label"]}} was detected.'
-          data:
-            image: 'https://your.public.hass.address.com/api/frigate/notifications/{{trigger.payload_json["after"]["id"]}}/thumbnail.jpg?format=android'
-            tag: '{{trigger.payload_json["after"]["id"]}}'
-```
-
-```yaml
-automation:
-  - alias: When a person enters a zone named yard
-    trigger:
-      platform: mqtt
-      topic: frigate/events
-    conditions:
-      - "{{ trigger.payload_json['after']['label'] == 'person' }}"
-      - "{{ 'yard' in trigger.payload_json['after']['entered_zones'] }}"
-    action:
-      - service: notify.mobile_app_pixel_3
-        data_template:
-          message: "A {{trigger.payload_json['after']['label']}} has entered the yard."
-          data:
-            image: "https://url.com/api/frigate/notifications/{{trigger.payload_json['after']['id']}}/thumbnail.jpg"
-            tag: "{{trigger.payload_json['after']['id']}}"
-```
-
-```yaml
-- alias: When a person leaves a zone named yard
-  trigger:
-    platform: mqtt
-    topic: frigate/events
-  conditions:
-    - "{{ trigger.payload_json['after']['label'] == 'person' }}"
-    - "{{ 'yard' in trigger.payload_json['before']['current_zones'] }}"
-    - "{{ not 'yard' in trigger.payload_json['after']['current_zones'] }}"
-  action:
-    - service: notify.mobile_app_pixel_3
-      data_template:
-        message: "A {{trigger.payload_json['after']['label']}} has left the yard."
-        data:
-          image: "https://url.com/api/frigate/notifications/{{trigger.payload_json['after']['id']}}/thumbnail.jpg"
-          tag: "{{trigger.payload_json['after']['id']}}"
-```
-
-```yaml
-- alias: Notify for dogs in the front with a high top score
-  trigger:
-    platform: mqtt
-    topic: frigate/events
-  conditions:
-    - "{{ trigger.payload_json['after']['label'] == 'dog' }}"
-    - "{{ trigger.payload_json['after']['camera'] == 'front' }}"
-    - "{{ trigger.payload_json['after']['top_score'] > 0.98 }}"
-  action:
-    - service: notify.mobile_app_pixel_3
-      data_template:
-        message: 'High confidence dog detection.'
-        data:
-          image: "https://url.com/api/frigate/notifications/{{trigger.payload_json['after']['id']}}/thumbnail.jpg"
-          tag: "{{trigger.payload_json['after']['id']}}"
-```
-
-If you are using telegram, you can fetch the image directly from Frigate:
-
-```yaml
-automation:
-  - alias: Notify of events
-    trigger:
-      platform: mqtt
-      topic: frigate/events
-    action:
-      - service: notify.telegram_full
-        data_template:
-          message: 'A {{trigger.payload_json["after"]["label"]}} was detected.'
-          data:
-            photo:
-              # this url should work for addon users
-              - url: 'http://ccab4aaf-frigate:5000/api/events/{{trigger.payload_json["after"]["id"]}}/thumbnail.jpg'
-                caption: 'A {{trigger.payload_json["after"]["label"]}} was detected on {{ trigger.payload_json["after"]["camera"] }} camera'
-```

docs/docs/usage/mqtt.md

@@ -1,99 +0,0 @@
----
-id: mqtt
-title: MQTT
----
-
-These are the MQTT messages generated by Frigate. The default topic_prefix is `frigate`, but can be changed in the config file.
-
-### `frigate/available`
-
-Designed to be used as an availability topic with HomeAssistant. Possible message are:
-"online": published when frigate is running (on startup)
-"offline": published right before frigate stops
-
-### `frigate/<camera_name>/<object_name>`
-
-Publishes the count of objects for the camera for use as a sensor in HomeAssistant.
-
-### `frigate/<zone_name>/<object_name>`
-
-Publishes the count of objects for the zone for use as a sensor in HomeAssistant.
-
-### `frigate/<camera_name>/<object_name>/snapshot`
-
-Publishes a jpeg encoded frame of the detected object type. When the object is no longer detected, the highest confidence image is published or the original image
-is published again.
-
-The height and crop of snapshots can be configured in the config.
-
-### `frigate/events`
-
-Message published for each changed event. The first message is published when the tracked object is no longer marked as a false_positive. When frigate finds a better snapshot of the tracked object or when a zone change occurs, it will publish a message with the same id. When the event ends, a final message is published with `end_time` set.
-
-```json
-{
-  "type": "update", // new, update, or end
-  "before": {
-    "id": "1607123955.475377-mxklsc",
-    "camera": "front_door",
-    "frame_time": 1607123961.837752,
-    "label": "person",
-    "top_score": 0.958984375,
-    "false_positive": false,
-    "start_time": 1607123955.475377,
-    "end_time": null,
-    "score": 0.7890625,
-    "box": [424, 500, 536, 712],
-    "area": 23744,
-    "region": [264, 450, 667, 853],
-    "current_zones": ["driveway"],
-    "entered_zones": ["yard", "driveway"],
-    "thumbnail": null
-  },
-  "after": {
-    "id": "1607123955.475377-mxklsc",
-    "camera": "front_door",
-    "frame_time": 1607123962.082975,
-    "label": "person",
-    "top_score": 0.958984375,
-    "false_positive": false,
-    "start_time": 1607123955.475377,
-    "end_time": null,
-    "score": 0.87890625,
-    "box": [432, 496, 544, 854],
-    "area": 40096,
-    "region": [218, 440, 693, 915],
-    "current_zones": ["yard", "driveway"],
-    "entered_zones": ["yard", "driveway"],
-    "thumbnail": null
-  }
-}
-```
-
-### `frigate/stats`
-
-Same data available at `/api/stats` published at a configurable interval.
-
-### `frigate/<camera_name>/detect/set`
-
-Topic to turn detection for a camera on and off. Expected values are `ON` and `OFF`.
-
-### `frigate/<camera_name>/detect/state`
-
-Topic with current state of detection for a camera. Published values are `ON` and `OFF`.
-
-### `frigate/<camera_name>/clips/set`
-
-Topic to turn clips for a camera on and off. Expected values are `ON` and `OFF`.
-
-### `frigate/<camera_name>/clips/state`
-
-Topic with current state of clips for a camera. Published values are `ON` and `OFF`.
-
-### `frigate/<camera_name>/snapshots/set`
-
-Topic to turn snapshots for a camera on and off. Expected values are `ON` and `OFF`.
-
-### `frigate/<camera_name>/snapshots/state`
-
-Topic with current state of snapshots for a camera. Published values are `ON` and `OFF`.

docs/docs/usage/web.md

@@ -1,10 +0,0 @@
----
-id: web
-title: Web Interface
----
-
-Frigate comes bundled with a simple web ui that supports the following:
-
-- Show cameras
-- Browse events
-- Mask helper

docs/docusaurus.config.js

@@ -1,76 +0,0 @@
-module.exports = {
-  title: 'Frigate',
-  tagline: 'NVR With Realtime Object Detection for IP Cameras',
-  url: 'https://blakeblackshear.github.io',
-  baseUrl: '/frigate/',
-  onBrokenLinks: 'throw',
-  onBrokenMarkdownLinks: 'warn',
-  favicon: 'img/favicon.ico',
-  organizationName: 'blakeblackshear',
-  projectName: 'frigate',
-  themeConfig: {
-    algolia: {
-      apiKey: '81ec882db78f7fed05c51daf973f0362',
-      indexName: 'frigate'
-    },
-    navbar: {
-      title: 'Frigate',
-      logo: {
-        alt: 'Frigate',
-        src: 'img/logo.svg',
-        srcDark: 'img/logo-dark.svg',
-      },
-      items: [
-        {
-          to: '/',
-          activeBasePath: 'docs',
-          label: 'Docs',
-          position: 'left',
-        },
-        {
-          href: 'https://github.com/blakeblackshear/frigate',
-          label: 'GitHub',
-          position: 'right',
-        },
-      ],
-    },
-    sidebarCollapsible: false,
-    hideableSidebar: true,
-    footer: {
-      style: 'dark',
-      links: [
-        {
-          title: 'Community',
-          items: [
-            {
-              label: 'GitHub',
-              href: 'https://github.com/blakeblackshear/frigate',
-            },
-            {
-              label: 'Discussions',
-              href: 'https://github.com/blakeblackshear/frigate/discussions',
-            },
-          ],
-        },
-      ],
-      copyright: `Copyright © ${new Date().getFullYear()} Blake Blackshear`,
-    },
-  },
-  presets: [
-    [
-      '@docusaurus/preset-classic',
-      {
-        docs: {
-          routeBasePath: '/',
-          sidebarPath: require.resolve('./sidebars.js'),
-          // Please change this to your repo.
-          editUrl: 'https://github.com/blakeblackshear/frigate/edit/master/docs/',
-        },
-
-        theme: {
-          customCss: require.resolve('./src/css/custom.css'),
-        },
-      },
-    ],
-  ],
-};

docs/how-frigate-works.md

@@ -0,0 +1,10 @@
+# How Frigate Works
+Frigate is designed to minimize resource and maximize performance by only looking for objects when and where it is necessary
+
+![Diagram](diagram.png)
+
+## 1. Look for Motion
+
+## 2. Calculate Detection Regions
+
+## 3. Run Object Detection

docs/notification-examples.md

@@ -0,0 +1,71 @@
+# Notification examples
+
+Here are some examples of notifications for the HomeAssistant android companion app:
+```yaml
+automation:
+
+  - alias: When a person enters a zone named yard
+    trigger:
+      platform: mqtt
+      topic: frigate/events
+    conditions: 
+      - "{{ trigger.payload_json['after']['label'] == 'person' }}"
+      - "{{ 'yard' in trigger.payload_json['after']['entered_zones'] }}"
+    action:
+      - service: notify.mobile_app_pixel_3
+        data_template:
+          message: "A {{trigger.payload_json['after']['label']}} has entered the yard."
+          data:
+            image: "https://url.com/api/frigate/notifications/{{trigger.payload_json['after']['id']}}.jpg"
+            tag: "{{trigger.payload_json['after']['id']}}"
+
+  - alias: When a person leaves a zone named yard
+    trigger:
+      platform: mqtt
+      topic: frigate/events
+    conditions: 
+      - "{{ trigger.payload_json['after']['label'] == 'person' }}"
+      - "{{ 'yard' in trigger.payload_json['before']['current_zones'] }}"
+      - "{{ not 'yard' in trigger.payload_json['after']['current_zones'] }}"
+    action:
+      - service: notify.mobile_app_pixel_3
+        data_template:
+          message: "A {{trigger.payload_json['after']['label']}} has left the yard."
+          data:
+            image: "https://url.com/api/frigate/notifications/{{trigger.payload_json['after']['id']}}.jpg"
+            tag: "{{trigger.payload_json['after']['id']}}"
+
+  - alias: Notify for dogs in the front with a high top score
+    trigger:
+      platform: mqtt
+      topic: frigate/events
+    conditions: 
+      - "{{ trigger.payload_json['after']['label'] == 'dog' }}"
+      - "{{ trigger.payload_json['after']['camera'] == 'front' }}"
+      - "{{ trigger.payload_json['after']['top_score'] > 0.98 }}"
+    action:
+      - service: notify.mobile_app_pixel_3
+        data_template:
+          message: 'High confidence dog detection.'
+          data:
+            image: "https://url.com/api/frigate/notifications/{{trigger.payload_json['after']['id']}}.jpg"
+            tag: "{{trigger.payload_json['after']['id']}}"
+```
+
+If you are using telegram, you can fetch the image directly from Frigate:
+```yaml
+automation:
+  - alias: Notify of events
+    trigger:
+      platform: mqtt
+      topic: frigate/events
+    action:
+      - service: notify.telegram_full
+        data_template:
+          message: 'A {{trigger.payload_json["after"]["label"]}} was detected.'
+          data:
+            photo:
+              # this url should work for addon users
+              - url: 'http://ccab4aaf-frigate:5000/events/{{trigger.payload_json["after"]["id"]}}/snapshot.jpg'
+                caption : 'A {{trigger.payload_json["after"]["label"]}} was detected on {{ trigger.payload_json["after"]["camera"] }} camera'
+```

docs/nvdec.md

@@ -1,18 +1,14 @@
----
-id: nvdec
-title: nVidia hardware decoder
----
+# nVidia hardware decoder (NVDEC)
 
 Certain nvidia cards include a hardware decoder, which can greatly improve the
-performance of video decoding. In order to use NVDEC, a special build of
+performance of video decoding. In order to use NVDEC, a special build of 
 ffmpeg with NVDEC support is required. The special docker architecture 'amd64nvidia'
-includes this support for amd64 platforms. An aarch64 for the Jetson, which
+includes this support for amd64 platforms. An aarch64 for the Jetson, which 
 also includes NVDEC may be added in the future.
 
 ## Docker setup
 
 ### Requirements
-
 [nVidia closed source driver](https://www.nvidia.com/en-us/drivers/unix/) required to access NVDEC.
 [nvidia-docker](https://github.com/NVIDIA/nvidia-docker) required to pass NVDEC to docker.
 
@@ -22,7 +18,6 @@ In order to pass NVDEC, the docker engine must be set to `nvidia` and the enviro
 `NVIDIA_VISIBLE_DEVICES=all` and `NVIDIA_DRIVER_CAPABILITIES=compute,utility,video` must be set.
 
 In a docker compose file, these lines need to be set:
-
 ```
 services:
   frigate:
@@ -31,16 +26,15 @@ services:
     runtime: nvidia
     environment:
       - NVIDIA_VISIBLE_DEVICES=all
-      - NVIDIA_DRIVER_CAPABILITIES=compute,utility,video
+      - NVIDIA_DRIVER_CAPABILITIES=compute,utility,video 
 ```
 
 ### Setting up the configuration file
 
-In your frigate config.yml, you'll need to set ffmpeg to use the hardware decoder.
-The decoder you choose will depend on the input video.
+In your frigate config.yml, you'll need to set ffmpeg to use the hardware decoder. 
+The decoder you choose will depend on the input video. 
 
 A list of supported codecs (you can use `ffmpeg -decoders | grep cuvid` in the container to get a list)
-
 ```
  V..... h263_cuvid           Nvidia CUVID H263 decoder (codec h263)
  V..... h264_cuvid           Nvidia CUVID H264 decoder (codec h264)
@@ -52,7 +46,7 @@ A list of supported codecs (you can use `ffmpeg -decoders | grep cuvid` in the c
  V..... vc1_cuvid            Nvidia CUVID VC1 decoder (codec vc1)
  V..... vp8_cuvid            Nvidia CUVID VP8 decoder (codec vp8)
  V..... vp9_cuvid            Nvidia CUVID VP9 decoder (codec vp9)
-```
+ ```
 
 For example, for H265 video (hevc), you'll select `hevc_cuvid`. Add
 `-c:v hevc_covid` to your ffmpeg input arguments:
@@ -61,7 +55,7 @@ For example, for H265 video (hevc), you'll select `hevc_cuvid`. Add
 ffmpeg:
   input_args:
     ...
-    - -c:v
+    - -c:v 
     - hevc_cuvid
 ```
 
@@ -81,7 +75,7 @@ processes:
 | 38%   41C    P2    36W / 125W |   2082MiB /  5942MiB |      5%      Default |
 |                               |                      |                  N/A |
 +-------------------------------+----------------------+----------------------+
-
+                                                                               
 +-----------------------------------------------------------------------------+
 | Processes:                                                                  |
 |  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
@@ -102,9 +96,10 @@ using the fps filter:
 
 ```
   output_args:
-    - -filter:v
+    - -filter:v 
     - fps=fps=5
 ```
 
 This setting, for example, allows Frigate to consume my 10-15fps camera streams on
 my relatively low powered Haswell machine with relatively low cpu usage.
+

docs/package.json

@@ -1,34 +0,0 @@
-{
-  "name": "docs",
-  "version": "0.0.0",
-  "private": true,
-  "scripts": {
-    "docusaurus": "docusaurus",
-    "start": "docusaurus start",
-    "build": "docusaurus build",
-    "swizzle": "docusaurus swizzle",
-    "deploy": "docusaurus deploy",
-    "serve": "docusaurus serve",
-    "clear": "docusaurus clear"
-  },
-  "dependencies": {
-    "@docusaurus/core": "2.0.0-alpha.70",
-    "@docusaurus/preset-classic": "2.0.0-alpha.70",
-    "@mdx-js/react": "^1.6.21",
-    "clsx": "^1.1.1",
-    "react": "^16.8.4",
-    "react-dom": "^16.8.4"
-  },
-  "browserslist": {
-    "production": [
-      ">0.5%",
-      "not dead",
-      "not op_mini all"
-    ],
-    "development": [
-      "last 1 chrome version",
-      "last 1 firefox version",
-      "last 1 safari version"
-    ]
-  }
-}

docs/sidebars.js

@@ -1,14 +0,0 @@
-module.exports = {
-  docs: {
-    Frigate: ['index', 'how-it-works', 'hardware', 'installation', 'troubleshooting'],
-    Configuration: [
-      'configuration/index',
-      'configuration/cameras',
-      'configuration/optimizing',
-      'configuration/detectors',
-      'configuration/false_positives',
-      'configuration/advanced',
-    ],
-    Usage: ['usage/home-assistant', 'usage/web', 'usage/api', 'usage/mqtt'],
-  },
-};

docs/src/css/custom.css

@@ -1,25 +0,0 @@
-/* stylelint-disable docusaurus/copyright-header */
-/**
- * Any CSS included here will be global. The classic template
- * bundles Infima by default. Infima is a CSS framework designed to
- * work well for content-centric websites.
- */
-
-/* You can override the default Infima variables here. */
-:root {
-  --ifm-color-primary: #3b82f7;
-  --ifm-color-primary-dark: #1d4ed8;
-  --ifm-color-primary-darker: #1e40af;
-  --ifm-color-primary-darkest: #1e3a8a;
-  --ifm-color-primary-light: #60a5fa;
-  --ifm-color-primary-lighter: #93c5fd;
-  --ifm-color-primary-lightest: #dbeafe;
-  --ifm-code-font-size: 95%;
-}
-
-.docusaurus-highlight-code-line {
-  background-color: rgb(72, 77, 91);
-  display: block;
-  margin: 0 calc(-1 * var(--ifm-pre-padding));
-  padding: 0 var(--ifm-pre-padding);
-}

docs/static/img/logo-dark.svg

@@ -1,3 +0,0 @@
-<svg width="512" height="512" viewBox="0 0 512 512" fill="none" xmlns="http://www.w3.org/2000/svg">
-<path d="M130 446.5C131.6 459.3 145 468 137 470C129 472 94 406.5 86 378.5C78 350.5 73.5 319 75.4999 301C77.4999 283 181 255 181 247.5C181 240 147.5 247 146 241C144.5 235 171.3 238.6 178.5 229C189.75 214 204 216.5 213 208.5C222 200.5 233 170 235 157C237 144 215 129 209 119C203 109 222 102 268 83C314 64 460 22 462 27C464 32 414 53 379 66C344 79 287 104 287 111C287 118 290 123.5 288 139.5C286 155.5 285.76 162.971 282 173.5C279.5 180.5 277 197 282 212C286 224 299 233 305 235C310 235.333 323.8 235.8 339 235C358 234 385 236 385 241C385 246 344 243 344 250C344 257 386 249 385 256C384 263 350 260 332 260C317.6 260 296.333 259.333 287 256L285 263C281.667 263 274.7 265 267.5 265C258.5 265 258 268 241.5 268C225 268 230 267 215 266C200 265 144 308 134 322C124 336 130 370 130 385.5C130 399.428 128 430.5 130 446.5Z" fill="white"/>
-</svg>

docs/static/img/logo.svg

@@ -1,3 +0,0 @@
-<svg width="512" height="512" viewBox="0 0 512 512" fill="none" xmlns="http://www.w3.org/2000/svg">
-<path d="M130 446.5C131.6 459.3 145 468 137 470C129 472 94 406.5 86 378.5C78 350.5 73.5 319 75.5 301C77.4999 283 181 255 181 247.5C181 240 147.5 247 146 241C144.5 235 171.3 238.6 178.5 229C189.75 214 204 216.5 213 208.5C222 200.5 233 170 235 157C237 144 215 129 209 119C203 109 222 102 268 83C314 64 460 22 462 27C464 32 414 53 379 66C344 79 287 104 287 111C287 118 290 123.5 288 139.5C286 155.5 285.76 162.971 282 173.5C279.5 180.5 277 197 282 212C286 224 299 233 305 235C310 235.333 323.8 235.8 339 235C358 234 385 236 385 241C385 246 344 243 344 250C344 257 386 249 385 256C384 263 350 260 332 260C317.6 260 296.333 259.333 287 256L285 263C281.667 263 274.7 265 267.5 265C258.5 265 258 268 241.5 268C225 268 230 267 215 266C200 265 144 308 134 322C124 336 130 370 130 385.5C130 399.428 128 430.5 130 446.5Z" fill="black"/>
-</svg>

frigate/app.py

@@ -8,9 +8,7 @@ import sys
 import signal
 
 import yaml
-from peewee_migrate import Router
 from playhouse.sqlite_ext import SqliteExtDatabase
-from playhouse.sqliteq import SqliteQueueDatabase
 
 from frigate.config import FrigateConfig
 from frigate.const import RECORD_DIR, CLIPS_DIR, CACHE_DIR
@@ -22,7 +20,6 @@ from frigate.models import Event
 from frigate.mqtt import create_mqtt_client
 from frigate.object_processing import TrackedObjectProcessor
 from frigate.record import RecordingMaintainer
-from frigate.stats import StatsEmitter, stats_init
 from frigate.video import capture_camera, track_camera
 from frigate.watchdog import FrigateWatchdog
 from frigate.zeroconf import broadcast_zeroconf
@@ -40,10 +37,6 @@ class FrigateApp():
         self.log_queue = mp.Queue()
         self.camera_metrics = {}
 
-    def set_environment_vars(self):
-        for key, value in self.config.environment_vars.items():
-            os.environ[key] = value
-
     def ensure_dirs(self):
         for d in [RECORD_DIR, CLIPS_DIR, CACHE_DIR]:
             if not os.path.exists(d) and not os.path.islink(d):
@@ -52,7 +45,7 @@ class FrigateApp():
             else:
                 logger.debug(f"Skipping directory: {d}")
 
-        tmpfs_size = self.config.clips.tmpfs_cache_size
+        tmpfs_size = self.config.save_clips.tmpfs_cache_size
         if tmpfs_size:
              logger.info(f"Creating tmpfs of size {tmpfs_size}")
              rc = os.system(f"mount -t tmpfs -o size={tmpfs_size} tmpfs {CACHE_DIR}")
@@ -75,21 +68,20 @@ class FrigateApp():
                 'camera_fps': mp.Value('d', 0.0),
                 'skipped_fps': mp.Value('d', 0.0),
                 'process_fps': mp.Value('d', 0.0),
-                'detection_enabled': mp.Value('i', self.config.cameras[camera_name].detect.enabled),
                 'detection_fps': mp.Value('d', 0.0),
                 'detection_frame': mp.Value('d', 0.0),
                 'read_start': mp.Value('d', 0.0),
                 'ffmpeg_pid': mp.Value('i', 0),
-                'frame_queue': mp.Queue(maxsize=2),
+                '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.clips.enabled and 'clips' in assigned_roles:
-                logger.warning(f"Camera {name} has clips assigned to an input, but clips is not enabled.")
-            elif camera.clips.enabled and not 'clips' in assigned_roles:
-                logger.warning(f"Camera {name} has clips enabled, but clips is not assigned to an input.")
+            if not camera.save_clips.enabled and 'clips' in assigned_roles:
+                logger.warning(f"Camera {name} has clips assigned to an input, but save_clips is not enabled.")
+            elif camera.save_clips.enabled and not 'clips' in assigned_roles:
+                logger.warning(f"Camera {name} has save_clips enabled, but clips is not assigned to an input.")
 
             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.")
@@ -118,27 +110,16 @@ class FrigateApp():
         self.detected_frames_queue = mp.Queue(maxsize=len(self.config.cameras.keys())*2)
 
     def init_database(self):
-        migrate_db = SqliteExtDatabase(self.config.database.path)
-
-        # Run migrations
-        del(logging.getLogger('peewee_migrate').handlers[:])
-        router = Router(migrate_db)
-        router.run()
-
-        migrate_db.close()
-
-        self.db = SqliteQueueDatabase(self.config.database.path)
+        self.db = SqliteExtDatabase(self.config.database.path)
         models = [Event]
         self.db.bind(models)
-
-    def init_stats(self):
-        self.stats_tracking = stats_init(self.camera_metrics, self.detectors)
+        self.db.create_tables(models, safe=True)
 
     def init_web_server(self):
-        self.flask_app = create_app(self.config, self.db, self.stats_tracking, self.detected_frames_processor)
+        self.flask_app = create_app(self.config, self.db, self.camera_metrics, self.detectors, self.detected_frames_processor)
 
     def init_mqtt(self):
-        self.mqtt_client = create_mqtt_client(self.config, self.camera_metrics)
+        self.mqtt_client = create_mqtt_client(self.config.mqtt)
 
     def start_detectors(self):
         model_shape = (self.config.model.height, self.config.model.width)
@@ -192,10 +173,6 @@ class FrigateApp():
         self.recording_maintainer = RecordingMaintainer(self.config, self.stop_event)
         self.recording_maintainer.start()
 
-    def start_stats_emitter(self):
-        self.stats_emitter = StatsEmitter(self.config, self.stats_tracking, self.mqtt_client, self.config.mqtt.topic_prefix, self.stop_event)
-        self.stats_emitter.start()
-
     def start_watchdog(self):
         self.frigate_watchdog = FrigateWatchdog(self.detectors, self.stop_event)
         self.frigate_watchdog.start()
@@ -206,10 +183,9 @@ class FrigateApp():
             try:
                 self.init_config()
             except Exception as e:
-                print(f"Error parsing config: {e}")
+                logger.error(f"Error parsing config: {e}")
                 self.log_process.terminate()
                 sys.exit(1)
-            self.set_environment_vars()
             self.ensure_dirs()
             self.check_config()
             self.set_log_levels()
@@ -224,12 +200,10 @@ class FrigateApp():
         self.start_detected_frames_processor()
         self.start_camera_processors()
         self.start_camera_capture_processes()
-        self.init_stats()
         self.init_web_server()
         self.start_event_processor()
         self.start_event_cleanup()
         self.start_recording_maintainer()
-        self.start_stats_emitter()
         self.start_watchdog()
         # self.zeroconf = broadcast_zeroconf(self.config.mqtt.client_id)
 
@@ -250,7 +224,6 @@ class FrigateApp():
         self.event_processor.join()
         self.event_cleanup.join()
         self.recording_maintainer.join()
-        self.stats_emitter.join()
         self.frigate_watchdog.join()
 
         for detector in self.detectors.values():

frigate/edgetpu.py

@@ -8,7 +8,6 @@ import threading
 import signal
 from abc import ABC, abstractmethod
 from multiprocessing.connection import Connection
-from setproctitle import setproctitle
 from typing import Dict
 
 import numpy as np
@@ -62,15 +61,16 @@ class LocalObjectDetector(ObjectDetector):
                 logger.info(f"Attempting to load TPU as {device_config['device']}")
                 edge_tpu_delegate = load_delegate('libedgetpu.so.1.0', device_config)
                 logger.info("TPU found")
-                self.interpreter = tflite.Interpreter(
-                    model_path='/edgetpu_model.tflite',
-                    experimental_delegates=[edge_tpu_delegate])
             except ValueError:
-                logger.info("No EdgeTPU detected.")
-                raise
-        else:
+                logger.info("No EdgeTPU detected. Falling back to CPU.")
+        
+        if edge_tpu_delegate is None:
             self.interpreter = tflite.Interpreter(
                 model_path='/cpu_model.tflite', num_threads=num_threads)
+        else:
+            self.interpreter = tflite.Interpreter(
+                model_path='/edgetpu_model.tflite',
+                experimental_delegates=[edge_tpu_delegate])
         
         self.interpreter.allocate_tensors()
 
@@ -110,7 +110,6 @@ def run_detector(name: str, detection_queue: mp.Queue, out_events: Dict[str, mp.
     threading.current_thread().name = f"detector:{name}"
     logger = logging.getLogger(f"detector.{name}")
     logger.info(f"Starting detection process: {os.getpid()}")
-    setproctitle(f"frigate.detector.{name}")
     listen()
 
     stop_event = mp.Event()

frigate/events.py

@@ -88,32 +88,24 @@ class EventProcessor(threading.Thread):
             earliest_event = datetime.datetime.now().timestamp()
 
         # if the earliest event exceeds the max seconds, cap it
-        max_seconds = self.config.clips.max_seconds
+        max_seconds = self.config.save_clips.max_seconds
         if datetime.datetime.now().timestamp()-earliest_event > max_seconds:
             earliest_event = datetime.datetime.now().timestamp()-max_seconds
         
         for f, data in list(self.cached_clips.items()):
             if earliest_event-90 > data['start_time']+data['duration']:
                 del self.cached_clips[f]
-                logger.debug(f"Cleaning up cached file {f}")
                 os.remove(os.path.join(CACHE_DIR,f))
 
     def create_clip(self, camera, event_data, pre_capture, post_capture):
         # get all clips from the camera with the event sorted
         sorted_clips = sorted([c for c in self.cached_clips.values() if c['camera'] == camera], key = lambda i: i['start_time'])
 
-        # if there are no clips in the cache or we are still waiting on a needed file check every 5 seconds
-        wait_count = 0
         while len(sorted_clips) == 0 or sorted_clips[-1]['start_time'] + sorted_clips[-1]['duration'] < event_data['end_time']+post_capture:
-            if wait_count > 4:
-                logger.warning(f"Unable to create clip for {camera} and event {event_data['id']}. There were no cache files for this event.")
-                return False
-            logger.debug(f"No cache clips for {camera}. Waiting...")
             time.sleep(5)
             self.refresh_cache()
             # get all clips from the camera with the event sorted
             sorted_clips = sorted([c for c in self.cached_clips.values() if c['camera'] == camera], key = lambda i: i['start_time'])
-            wait_count += 1
         
         playlist_start = event_data['start_time']-pre_capture
         playlist_end = event_data['end_time']+post_capture
@@ -155,8 +147,7 @@ class EventProcessor(threading.Thread):
         p = sp.run(ffmpeg_cmd, input="\n".join(playlist_lines), encoding='ascii', capture_output=True)
         if p.returncode != 0:
             logger.error(p.stderr)
-            return False
-        return True
+            return
 
     def run(self):
         while True:
@@ -171,20 +162,28 @@ class EventProcessor(threading.Thread):
                     self.refresh_cache()
                 continue
 
-            logger.debug(f"Event received: {event_type} {camera} {event_data['id']}")
             self.refresh_cache()
 
+            save_clips_config = self.config.cameras[camera].save_clips
+
+            # if save clips is not enabled for this camera, just continue
+            if not save_clips_config.enabled:
+                if event_type == 'end':
+                    self.event_processed_queue.put((event_data['id'], camera))
+                continue
+
+            # if specific objects are listed for this camera, only save clips for them
+            if not event_data['label'] in save_clips_config.objects:
+                if event_type == 'end':
+                    self.event_processed_queue.put((event_data['id'], camera))
+                continue
+
             if event_type == 'start':
                 self.events_in_process[event_data['id']] = event_data
 
             if event_type == 'end':
-                clips_config = self.config.cameras[camera].clips
-
-                if not event_data['false_positive']:
-                    clip_created = False
-                    if clips_config.enabled and (clips_config.objects is None or event_data['label'] in clips_config.objects):
-                        clip_created = self.create_clip(camera, event_data, clips_config.pre_capture, clips_config.post_capture)
-                    
+                if len(self.cached_clips) > 0 and not event_data['false_positive']:
+                    self.create_clip(camera, event_data, save_clips_config.pre_capture, save_clips_config.post_capture)
                     Event.create(
                         id=event_data['id'],
                         label=event_data['label'],
@@ -194,9 +193,7 @@ class EventProcessor(threading.Thread):
                         top_score=event_data['top_score'],
                         false_positive=event_data['false_positive'],
                         zones=list(event_data['entered_zones']),
-                        thumbnail=event_data['thumbnail'],
-                        has_clip=clip_created,
-                        has_snapshot=event_data['has_snapshot'],
+                        thumbnail=event_data['thumbnail']
                     )
                 del self.events_in_process[event_data['id']]
                 self.event_processed_queue.put((event_data['id'], camera))
@@ -207,86 +204,7 @@ class EventCleanup(threading.Thread):
         self.name = 'event_cleanup'
         self.config = config
         self.stop_event = stop_event
-        self.camera_keys = list(self.config.cameras.keys())
 
-    def expire(self, media):
-        ## Expire events from unlisted cameras based on the global config
-        if media == 'clips':
-            retain_config = self.config.clips.retain
-            file_extension = 'mp4'
-            update_params = {'has_clip': False}
-        else:
-            retain_config = self.config.snapshots.retain
-            file_extension = 'jpg'
-            update_params = {'has_snapshot': False}
-        
-        distinct_labels = (Event.select(Event.label)
-                    .where(Event.camera.not_in(self.camera_keys))
-                    .distinct())
-        
-        # loop over object types in db
-        for l in distinct_labels:
-            # get expiration time for this label
-            expire_days = retain_config.objects.get(l.label, retain_config.default)
-            expire_after = (datetime.datetime.now() - datetime.timedelta(days=expire_days)).timestamp()
-            # grab all events after specific time
-            expired_events = (
-                Event.select()
-                    .where(Event.camera.not_in(self.camera_keys), 
-                        Event.start_time < expire_after, 
-                        Event.label == l.label)
-            )
-            # delete the media from disk
-            for event in expired_events:
-                media_name = f"{event.camera}-{event.id}"
-                media = Path(f"{os.path.join(CLIPS_DIR, media_name)}.{file_extension}")
-                media.unlink(missing_ok=True)
-            # update the clips attribute for the db entry
-            update_query = (
-                Event.update(update_params)
-                    .where(Event.camera.not_in(self.camera_keys), 
-                        Event.start_time < expire_after, 
-                        Event.label == l.label)
-            )
-            update_query.execute()
-
-        ## Expire events from cameras based on the camera config
-        for name, camera in self.config.cameras.items():
-            if media == 'clips':
-                retain_config = camera.clips.retain
-            else:
-                retain_config = camera.snapshots.retain
-            # get distinct objects in database for this camera
-            distinct_labels = (Event.select(Event.label)
-                    .where(Event.camera == name)
-                    .distinct())
-
-            # loop over object types in db
-            for l in distinct_labels:
-                # get expiration time for this label
-                expire_days = retain_config.objects.get(l.label, retain_config.default)
-                expire_after = (datetime.datetime.now() - datetime.timedelta(days=expire_days)).timestamp()
-                # grab all events after specific time
-                expired_events = (
-                    Event.select()
-                        .where(Event.camera == name, 
-                            Event.start_time < expire_after, 
-                            Event.label == l.label)
-                )
-                # delete the grabbed clips from disk
-                for event in expired_events:
-                    media_name = f"{event.camera}-{event.id}"
-                    media = Path(f"{os.path.join(CLIPS_DIR, media_name)}.{file_extension}")
-                    media.unlink(missing_ok=True)
-                # update the clips attribute for the db entry
-                update_query = (
-                    Event.update(update_params)
-                        .where( Event.camera == name, 
-                            Event.start_time < expire_after, 
-                            Event.label == l.label)
-                )
-                update_query.execute()
-    
     def run(self):
         counter = 0
         while(True):
@@ -301,13 +219,71 @@ class EventCleanup(threading.Thread):
                 continue
             counter = 0
 
-            self.expire('clips')
-            self.expire('snapshots')
+            camera_keys = list(self.config.cameras.keys())
 
-            # drop events from db where has_clip and has_snapshot are false
-            delete_query = (
-                Event.delete()
-                    .where( Event.has_clip == False, 
-                        Event.has_snapshot == False)
-            )
-            delete_query.execute()
+            # Expire events from unlisted cameras based on the global config
+            retain_config = self.config.save_clips.retain
+            
+            distinct_labels = (Event.select(Event.label)
+                        .where(Event.camera.not_in(camera_keys))
+                        .distinct())
+            
+            # loop over object types in db
+            for l in distinct_labels:
+                # get expiration time for this label
+                expire_days = retain_config.objects.get(l.label, retain_config.default)
+                expire_after = (datetime.datetime.now() - datetime.timedelta(days=expire_days)).timestamp()
+                # grab all events after specific time
+                expired_events = (
+                    Event.select()
+                        .where(Event.camera.not_in(camera_keys), 
+                            Event.start_time < expire_after, 
+                            Event.label == l.label)
+                )
+                # delete the grabbed clips from disk
+                for event in expired_events:
+                    clip_name = f"{event.camera}-{event.id}"
+                    clip = Path(f"{os.path.join(CLIPS_DIR, clip_name)}.mp4")
+                    clip.unlink(missing_ok=True)
+                # delete the event for this type from the db
+                delete_query = (
+                    Event.delete()
+                        .where(Event.camera.not_in(camera_keys), 
+                            Event.start_time < expire_after, 
+                            Event.label == l.label)
+                )
+                delete_query.execute()
+
+            # Expire events from cameras based on the camera config
+            for name, camera in self.config.cameras.items():
+                retain_config = camera.save_clips.retain
+                # get distinct objects in database for this camera
+                distinct_labels = (Event.select(Event.label)
+                        .where(Event.camera == name)
+                        .distinct())
+
+                # loop over object types in db
+                for l in distinct_labels:
+                    # get expiration time for this label
+                    expire_days = retain_config.objects.get(l.label, retain_config.default)
+                    expire_after = (datetime.datetime.now() - datetime.timedelta(days=expire_days)).timestamp()
+                    # grab all events after specific time
+                    expired_events = (
+                        Event.select()
+                            .where(Event.camera == name, 
+                                Event.start_time < expire_after, 
+                                Event.label == l.label)
+                    )
+                    # delete the grabbed clips from disk
+                    for event in expired_events:
+                        clip_name = f"{event.camera}-{event.id}"
+                        clip = Path(f"{os.path.join(CLIPS_DIR, clip_name)}.mp4")
+                        clip.unlink(missing_ok=True)
+                    # delete the event for this type from the db
+                    delete_query = (
+                        Event.delete()
+                            .where( Event.camera == name, 
+                                Event.start_time < expire_after, 
+                                Event.label == l.label)
+                    )
+                    delete_query.execute()

frigate/http.py

@@ -12,9 +12,7 @@ from flask import (Blueprint, Flask, Response, current_app, jsonify,
 from peewee import SqliteDatabase, operator, fn, DoesNotExist
 from playhouse.shortcuts import model_to_dict
 
-from frigate.const import CLIPS_DIR
 from frigate.models import Event
-from frigate.stats import stats_snapshot
 from frigate.util import calculate_region
 from frigate.version import VERSION
 
@@ -22,7 +20,7 @@ logger = logging.getLogger(__name__)
 
 bp = Blueprint('frigate', __name__)
 
-def create_app(frigate_config, database: SqliteDatabase, stats_tracking, detected_frames_processor):
+def create_app(frigate_config, database: SqliteDatabase, camera_metrics, detectors, detected_frames_processor):
     app = Flask(__name__)
 
     @app.before_request
@@ -35,9 +33,10 @@ def create_app(frigate_config, database: SqliteDatabase, stats_tracking, detecte
             database.close()
 
     app.frigate_config = frigate_config
-    app.stats_tracking = stats_tracking
+    app.camera_metrics = camera_metrics
+    app.detectors = detectors
     app.detected_frames_processor = detected_frames_processor
-
+    
     app.register_blueprint(bp)
 
     return app
@@ -48,33 +47,18 @@ def is_healthy():
 
 @bp.route('/events/summary')
 def events_summary():
-    has_clip = request.args.get('has_clip', type=int)
-    has_snapshot = request.args.get('has_snapshot', type=int)
-
-    clauses = []
-
-    if not has_clip is None:
-        clauses.append((Event.has_clip == has_clip))
-
-    if not has_snapshot is None:
-        clauses.append((Event.has_snapshot == has_snapshot))
-
-    if len(clauses) == 0:
-        clauses.append((1 == 1))
-
     groups = (
         Event
             .select(
-                Event.camera,
-                Event.label,
-                fn.strftime('%Y-%m-%d', fn.datetime(Event.start_time, 'unixepoch', 'localtime')).alias('day'),
+                Event.camera, 
+                Event.label, 
+                fn.strftime('%Y-%m-%d', fn.datetime(Event.start_time, 'unixepoch', 'localtime')).alias('day'), 
                 Event.zones,
                 fn.COUNT(Event.id).alias('count')
             )
-            .where(reduce(operator.and_, clauses))
             .group_by(
-                Event.camera,
-                Event.label,
+                Event.camera, 
+                Event.label, 
                 fn.strftime('%Y-%m-%d', fn.datetime(Event.start_time, 'unixepoch', 'localtime')),
                 Event.zones
             )
@@ -89,8 +73,8 @@ def event(id):
     except DoesNotExist:
         return "Event not found", 404
 
-@bp.route('/events/<id>/thumbnail.jpg')
-def event_thumbnail(id):
+@bp.route('/events/<id>/snapshot.jpg')
+def event_snapshot(id):
     format = request.args.get('format', 'ios')
     thumbnail_bytes = None
     try:
@@ -103,96 +87,51 @@ def event_thumbnail(id):
                 if id in camera_state.tracked_objects:
                     tracked_obj = camera_state.tracked_objects.get(id)
                     if not tracked_obj is None:
-                        thumbnail_bytes = tracked_obj.get_thumbnail()
+                        thumbnail_bytes = tracked_obj.get_jpg_bytes()
         except:
             return "Event not found", 404
-
+    
     if thumbnail_bytes is None:
         return "Event not found", 404
-
+    
     # android notifications prefer a 2:1 ratio
     if format == 'android':
         jpg_as_np = np.frombuffer(thumbnail_bytes, dtype=np.uint8)
         img = cv2.imdecode(jpg_as_np, flags=1)
         thumbnail = cv2.copyMakeBorder(img, 0, 0, int(img.shape[1]*0.5), int(img.shape[1]*0.5), cv2.BORDER_CONSTANT, (0,0,0))
-        ret, jpg = cv2.imencode('.jpg', thumbnail)
+        ret, jpg = cv2.imencode('.jpg', thumbnail)    
         thumbnail_bytes = jpg.tobytes()
-
+    
     response = make_response(thumbnail_bytes)
     response.headers['Content-Type'] = 'image/jpg'
     return response
 
-@bp.route('/events/<id>/snapshot.jpg')
-def event_snapshot(id):
-    jpg_bytes = None
-    try:
-        event = Event.get(Event.id == id)
-        if not event.has_snapshot:
-            return "Snapshot not available", 404
-        # read snapshot from disk
-        with open(os.path.join(CLIPS_DIR, f"{event.camera}-{id}.jpg"), 'rb') as image_file:
-            jpg_bytes = image_file.read()
-    except DoesNotExist:
-        # see if the object is currently being tracked
-        try:
-            for camera_state in current_app.detected_frames_processor.camera_states.values():
-                if id in camera_state.tracked_objects:
-                    tracked_obj = camera_state.tracked_objects.get(id)
-                    if not tracked_obj is None:
-                        jpg_bytes = tracked_obj.get_jpg_bytes(
-                            timestamp=request.args.get('timestamp', type=int),
-                            bounding_box=request.args.get('bbox', type=int),
-                            crop=request.args.get('crop', type=int),
-                            height=request.args.get('h', type=int)
-                        )
-        except:
-            return "Event not found", 404
-    except:
-        return "Event not found", 404
-
-    response = make_response(jpg_bytes)
-    response.headers['Content-Type'] = 'image/jpg'
-    return response
-
 @bp.route('/events')
 def events():
     limit = request.args.get('limit', 100)
     camera = request.args.get('camera')
     label = request.args.get('label')
     zone = request.args.get('zone')
-    after = request.args.get('after', type=float)
-    before = request.args.get('before', type=float)
-    has_clip = request.args.get('has_clip', type=int)
-    has_snapshot = request.args.get('has_snapshot', type=int)
-    include_thumbnails = request.args.get('include_thumbnails', default=1, type=int)
+    after = request.args.get('after', type=int)
+    before = request.args.get('before', type=int)
 
     clauses = []
-    excluded_fields = []
-
+    
     if camera:
         clauses.append((Event.camera == camera))
-
+    
     if label:
         clauses.append((Event.label == label))
-
+    
     if zone:
         clauses.append((Event.zones.cast('text') % f"*\"{zone}\"*"))
-
+    
     if after:
         clauses.append((Event.start_time >= after))
-
+    
     if before:
         clauses.append((Event.start_time <= before))
 
-    if not has_clip is None:
-        clauses.append((Event.has_clip == has_clip))
-
-    if not has_snapshot is None:
-        clauses.append((Event.has_snapshot == has_snapshot))
-
-    if not include_thumbnails:
-        excluded_fields.append(Event.thumbnail)
-
     if len(clauses) == 0:
         clauses.append((1 == 1))
 
@@ -201,7 +140,7 @@ def events():
                 .order_by(Event.start_time.desc())
                 .limit(limit))
 
-    return jsonify([model_to_dict(e, exclude=excluded_fields) for e in events])
+    return jsonify([model_to_dict(e) for e in events])
 
 @bp.route('/config')
 def config():
@@ -213,7 +152,31 @@ def version():
 
 @bp.route('/stats')
 def stats():
-    stats = stats_snapshot(current_app.stats_tracking)
+    camera_metrics = current_app.camera_metrics
+    stats = {}
+
+    total_detection_fps = 0
+
+    for name, camera_stats in camera_metrics.items():
+        total_detection_fps += camera_stats['detection_fps'].value
+        stats[name] = {
+            'camera_fps': round(camera_stats['camera_fps'].value, 2),
+            'process_fps': round(camera_stats['process_fps'].value, 2),
+            'skipped_fps': round(camera_stats['skipped_fps'].value, 2),
+            'detection_fps': round(camera_stats['detection_fps'].value, 2),
+            'pid': camera_stats['process'].pid,
+            'capture_pid': camera_stats['capture_process'].pid
+        }
+    
+    stats['detectors'] = {}
+    for name, detector in current_app.detectors.items():
+        stats['detectors'][name] = {
+            'inference_speed': round(detector.avg_inference_speed.value*1000, 2),
+            'detection_start': detector.detection_start.value,
+            'pid': detector.detect_process.pid
+        }
+    stats['detection_fps'] = round(total_detection_fps, 2)
+
     return jsonify(stats)
 
 @bp.route('/<camera_name>/<label>/best.jpg')
@@ -225,13 +188,13 @@ def best(camera_name, label):
             best_frame = np.zeros((720,1280,3), np.uint8)
         else:
             best_frame = cv2.cvtColor(best_frame, cv2.COLOR_YUV2BGR_I420)
-
+        
         crop = bool(request.args.get('crop', 0, type=int))
         if crop:
             box = best_object.get('box', (0,0,300,300))
             region = calculate_region(best_frame.shape, box[0], box[1], box[2], box[3], 1.1)
             best_frame = best_frame[region[1]:region[3], region[0]:region[2]]
-
+        
         height = int(request.args.get('h', str(best_frame.shape[0])))
         width = int(height*best_frame.shape[1]/best_frame.shape[0])
 
@@ -289,7 +252,7 @@ def latest_frame(camera_name):
         return response
     else:
         return "Camera named {} not found".format(camera_name), 404
-
+        
 def imagestream(detected_frames_processor, camera_name, fps, height, draw_options):
     while True:
         # max out at specified FPS

frigate/log.py

@@ -6,8 +6,6 @@ import signal
 import queue
 import multiprocessing as mp
 from logging import handlers
-from setproctitle import setproctitle
-from collections import deque
 
 
 def listener_configurer():
@@ -33,7 +31,6 @@ def log_process(log_queue):
     signal.signal(signal.SIGINT, receiveSignal)
 
     threading.current_thread().name = f"logger"
-    setproctitle("frigate.logger")
     listener_configurer()
     while True:
         if stop_event.is_set() and log_queue.empty():
@@ -55,7 +52,6 @@ class LogPipe(threading.Thread):
         self.daemon = False
         self.logger = logging.getLogger(log_name)
         self.level = level
-        self.deque = deque(maxlen=100)
         self.fdRead, self.fdWrite = os.pipe()
         self.pipeReader = os.fdopen(self.fdRead)
         self.start()
@@ -69,15 +65,11 @@ class LogPipe(threading.Thread):
         """Run the thread, logging everything.
         """
         for line in iter(self.pipeReader.readline, ''):
-            self.deque.append(line.strip('\n'))
+            self.logger.log(self.level, line.strip('\n'))
 
         self.pipeReader.close()
-    
-    def dump(self):
-        while len(self.deque) > 0:
-            self.logger.log(self.level, self.deque.popleft())
 
     def close(self):
         """Close the write end of the pipe.
         """
-        os.close(self.fdWrite)
+        os.close(self.fdWrite)

frigate/models.py

@@ -12,5 +12,3 @@ class Event(Model):
     false_positive = BooleanField()
     zones = JSONField()
     thumbnail = TextField()
-    has_clip = BooleanField(default=True)
-    has_snapshot = BooleanField(default=True)

frigate/motion.py

@@ -5,7 +5,7 @@ from frigate.config import MotionConfig
 
 
 class MotionDetector():
-    def __init__(self, frame_shape, config: MotionConfig):
+    def __init__(self, frame_shape, mask, config: MotionConfig):
         self.config = config
         self.frame_shape = frame_shape
         self.resize_factor = frame_shape[0]/config.frame_height
@@ -14,7 +14,7 @@ class MotionDetector():
         self.avg_delta = np.zeros(self.motion_frame_size, np.float)
         self.motion_frame_count = 0
         self.frame_counter = 0
-        resized_mask = cv2.resize(config.mask, dsize=(self.motion_frame_size[1], self.motion_frame_size[0]), interpolation=cv2.INTER_LINEAR)
+        resized_mask = cv2.resize(mask, dsize=(self.motion_frame_size[1], self.motion_frame_size[0]), interpolation=cv2.INTER_LINEAR)
         self.mask = np.where(resized_mask==[0])
 
     def detect(self, frame):

frigate/mqtt.py

@@ -3,81 +3,12 @@ import threading
 
 import paho.mqtt.client as mqtt
 
-from frigate.config import FrigateConfig
+from frigate.config import MqttConfig
 
 logger = logging.getLogger(__name__)
 
-def create_mqtt_client(config: FrigateConfig, camera_metrics):
-    mqtt_config = config.mqtt
-
-    def on_clips_command(client, userdata, message):
-        payload = message.payload.decode()
-        logger.debug(f"on_clips_toggle: {message.topic} {payload}")
-
-        camera_name = message.topic.split('/')[-3]
-
-        clips_settings = config.cameras[camera_name].clips
-
-        if payload == 'ON':
-            if not clips_settings.enabled:
-                logger.info(f"Turning on clips for {camera_name} via mqtt")
-                clips_settings._enabled = True
-        elif payload == 'OFF':
-            if clips_settings.enabled:
-                logger.info(f"Turning off clips for {camera_name} via mqtt")
-                clips_settings._enabled = False
-        else:
-            logger.warning(f"Received unsupported value at {message.topic}: {payload}")
-
-        state_topic = f"{message.topic[:-4]}/state"
-        client.publish(state_topic, payload, retain=True)
-
-    def on_snapshots_command(client, userdata, message):
-        payload = message.payload.decode()
-        logger.debug(f"on_snapshots_toggle: {message.topic} {payload}")
-
-        camera_name = message.topic.split('/')[-3]
-
-        snapshots_settings = config.cameras[camera_name].snapshots
-
-        if payload == 'ON':
-            if not snapshots_settings.enabled:
-                logger.info(f"Turning on snapshots for {camera_name} via mqtt")
-                snapshots_settings._enabled = True
-        elif payload == 'OFF':
-            if snapshots_settings.enabled:
-                logger.info(f"Turning off snapshots for {camera_name} via mqtt")
-                snapshots_settings._enabled = False
-        else:
-            logger.warning(f"Received unsupported value at {message.topic}: {payload}")
-
-        state_topic = f"{message.topic[:-4]}/state"
-        client.publish(state_topic, payload, retain=True)
-    
-    def on_detect_command(client, userdata, message):
-        payload = message.payload.decode()
-        logger.debug(f"on_detect_toggle: {message.topic} {payload}")
-
-        camera_name = message.topic.split('/')[-3]
-
-        detect_settings = config.cameras[camera_name].detect
-
-        if payload == 'ON':
-            if not camera_metrics[camera_name]["detection_enabled"].value:
-                logger.info(f"Turning on detection for {camera_name} via mqtt")
-                camera_metrics[camera_name]["detection_enabled"].value = True
-                detect_settings._enabled = True
-        elif payload == 'OFF':
-            if camera_metrics[camera_name]["detection_enabled"].value:
-                logger.info(f"Turning off detection for {camera_name} via mqtt")
-                camera_metrics[camera_name]["detection_enabled"].value = False
-                detect_settings._enabled = False
-        else:
-            logger.warning(f"Received unsupported value at {message.topic}: {payload}")
-
-        state_topic = f"{message.topic[:-4]}/state"
-        client.publish(state_topic, payload, retain=True)
-
+def create_mqtt_client(config: MqttConfig):
+    client = mqtt.Client(client_id=config.client_id)
     def on_connect(client, userdata, flags, rc):
         threading.current_thread().name = "mqtt"
         if rc != 0:
@@ -91,35 +22,15 @@ def create_mqtt_client(config: FrigateConfig, camera_metrics):
                 logger.error("Unable to connect to MQTT: Connection refused. Error code: " + str(rc))
             
         logger.info("MQTT connected")
-        client.publish(mqtt_config.topic_prefix+'/available', 'online', retain=True)   
-
-    client = mqtt.Client(client_id=mqtt_config.client_id)    
+        client.publish(config.topic_prefix+'/available', 'online', retain=True)       
     client.on_connect = on_connect
-    client.will_set(mqtt_config.topic_prefix+'/available', payload='offline', qos=1, retain=True)
-    
-    # register callbacks
-    for name in config.cameras.keys():
-        client.message_callback_add(f"{mqtt_config.topic_prefix}/{name}/clips/set", on_clips_command)
-        client.message_callback_add(f"{mqtt_config.topic_prefix}/{name}/snapshots/set", on_snapshots_command)
-        client.message_callback_add(f"{mqtt_config.topic_prefix}/{name}/detect/set", on_detect_command)
-
-    if not mqtt_config.user is None:
-        client.username_pw_set(mqtt_config.user, password=mqtt_config.password)
+    client.will_set(config.topic_prefix+'/available', payload='offline', qos=1, retain=True)
+    if not config.user is None:
+        client.username_pw_set(config.user, password=config.password)
     try:
-        client.connect(mqtt_config.host, mqtt_config.port, 60)
+        client.connect(config.host, config.port, 60)
     except Exception as e:
         logger.error(f"Unable to connect to MQTT server: {e}")
         raise
-
     client.loop_start()
-
-    for name in config.cameras.keys():
-        client.publish(f"{mqtt_config.topic_prefix}/{name}/clips/state", 'ON' if config.cameras[name].clips.enabled else 'OFF', retain=True)
-        client.publish(f"{mqtt_config.topic_prefix}/{name}/snapshots/state", 'ON' if config.cameras[name].snapshots.enabled else 'OFF', retain=True)
-        client.publish(f"{mqtt_config.topic_prefix}/{name}/detect/state", 'ON' if config.cameras[name].detect.enabled else 'OFF', retain=True)
-
-    client.subscribe(f"{mqtt_config.topic_prefix}/+/clips/set")
-    client.subscribe(f"{mqtt_config.topic_prefix}/+/snapshots/set")
-    client.subscribe(f"{mqtt_config.topic_prefix}/+/detect/set")
-
     return client

frigate/object_processing.py

@@ -54,11 +54,11 @@ def is_better_thumbnail(current_thumb, new_obj, frame_shape) -> bool:
     # if the score is better by more than 5%
     if new_obj['score'] > current_thumb['score']+.05:
         return True
-
+    
     # if the area is 10% larger
     if new_obj['area'] > current_thumb['area']*1.1:
         return True
-
+    
     return False
 
 class TrackedObject():
@@ -72,10 +72,11 @@ class TrackedObject():
         self.false_positive = True
         self.top_score = self.computed_score = 0.0
         self.thumbnail_data = None
-        self.last_updated = 0
-        self.last_published = 0
         self.frame = None
         self.previous = self.to_dict()
+        self._snapshot_jpg_time = 0
+        ret, jpg = cv2.imencode('.jpg', np.zeros((300,300,3), np.uint8))
+        self._snapshot_jpg = jpg.tobytes()
 
         # start the score history
         self.score_history = [self.obj_data['score']]
@@ -96,7 +97,7 @@ class TrackedObject():
         if len(scores) < 3:
             scores += [0.0]*(3 - len(scores))
         return median(scores)
-
+    
     def update(self, current_frame_time, obj_data):
         significant_update = False
         self.obj_data.update(obj_data)
@@ -118,7 +119,7 @@ class TrackedObject():
         if not self.false_positive:
             # determine if this frame is a better thumbnail
             if (
-                self.thumbnail_data is None
+                self.thumbnail_data is None 
                 or is_better_thumbnail(self.thumbnail_data, self.obj_data, self.camera_config.frame_shape)
             ):
                 self.thumbnail_data = {
@@ -129,7 +130,7 @@ class TrackedObject():
                     'score': self.obj_data['score']
                 }
                 significant_update = True
-
+        
         # check zones
         current_zones = []
         bottom_center = (self.obj_data['centroid'][0], self.obj_data['box'][3])
@@ -142,14 +143,14 @@ class TrackedObject():
                 if name in self.current_zones or not zone_filtered(self, zone.filters):
                     current_zones.append(name)
                     self.entered_zones.add(name)
-
+        
         # if the zones changed, signal an update
         if not self.false_positive and set(self.current_zones) != set(current_zones):
             significant_update = True
 
         self.current_zones = current_zones
         return significant_update
-
+    
     def to_dict(self, include_thumbnail: bool = False):
         return {
             'id': self.obj_data['id'],
@@ -166,62 +167,54 @@ class TrackedObject():
             'region': self.obj_data['region'],
             'current_zones': self.current_zones.copy(),
             'entered_zones': list(self.entered_zones).copy(),
-            'thumbnail': base64.b64encode(self.get_thumbnail()).decode('utf-8') if include_thumbnail else None
+            'thumbnail': base64.b64encode(self.get_jpg_bytes()).decode('utf-8') if include_thumbnail else None
         }
-
-    def get_thumbnail(self):
-        if self.thumbnail_data is None or not self.thumbnail_data['frame_time'] in self.frame_cache:
-            ret, jpg = cv2.imencode('.jpg', np.zeros((175,175,3), np.uint8))
-
-        jpg_bytes = self.get_jpg_bytes(timestamp=False, bounding_box=False, crop=True, height=175)
-
-        if jpg_bytes:
-            return jpg_bytes
-        else:
-            ret, jpg = cv2.imencode('.jpg', np.zeros((175,175,3), np.uint8))
-            return jpg.tobytes()
     
-    def get_jpg_bytes(self, timestamp=False, bounding_box=False, crop=False, height=None):
-        if self.thumbnail_data is None:
-            return None
-            
-        try:
-            best_frame = cv2.cvtColor(self.frame_cache[self.thumbnail_data['frame_time']], cv2.COLOR_YUV2BGR_I420)
-        except KeyError:
-            logger.warning(f"Unable to create jpg because frame {self.thumbnail_data['frame_time']} is not in the cache")
-            return None
- 
-        if bounding_box:
+    def get_jpg_bytes(self):
+        if self.thumbnail_data is None or self._snapshot_jpg_time == self.thumbnail_data['frame_time']:
+            return self._snapshot_jpg
+        
+        if not self.thumbnail_data['frame_time'] in self.frame_cache:
+            logger.error(f"Unable to create thumbnail for {self.obj_data['id']}")
+            logger.error(f"Looking for frame_time of {self.thumbnail_data['frame_time']}")
+            logger.error(f"Thumbnail frames: {','.join([str(k) for k in self.frame_cache.keys()])}")
+            return self._snapshot_jpg
+
+        # TODO: crop first to avoid converting the entire frame?
+        snapshot_config = self.camera_config.snapshots
+        best_frame = cv2.cvtColor(self.frame_cache[self.thumbnail_data['frame_time']], cv2.COLOR_YUV2BGR_I420)
+
+        if snapshot_config.draw_bounding_boxes:
             thickness = 2
             color = COLOR_MAP[self.obj_data['label']]
-
-            # draw the bounding boxes on the frame
             box = self.thumbnail_data['box']
-            draw_box_with_label(best_frame, box[0], box[1], box[2], box[3], self.obj_data['label'], f"{int(self.thumbnail_data['score']*100)}% {int(self.thumbnail_data['area'])}", thickness=thickness, color=color)
-
-        if crop:
+            draw_box_with_label(best_frame, box[0], box[1], box[2], box[3], self.obj_data['label'], 
+                f"{int(self.thumbnail_data['score']*100)}% {int(self.thumbnail_data['area'])}", thickness=thickness, color=color)
+            
+        if snapshot_config.crop_to_region:
             box = self.thumbnail_data['box']
             region = calculate_region(best_frame.shape, box[0], box[1], box[2], box[3], 1.1)
             best_frame = best_frame[region[1]:region[3], region[0]:region[2]]
 
-        if height:
+        if snapshot_config.height: 
+            height = snapshot_config.height
             width = int(height*best_frame.shape[1]/best_frame.shape[0])
             best_frame = cv2.resize(best_frame, dsize=(width, height), interpolation=cv2.INTER_AREA)
-
-        if timestamp:
+        
+        if snapshot_config.show_timestamp:
             time_to_show = datetime.datetime.fromtimestamp(self.thumbnail_data['frame_time']).strftime("%m/%d/%Y %H:%M:%S")
             size = cv2.getTextSize(time_to_show, cv2.FONT_HERSHEY_SIMPLEX, fontScale=1, thickness=2)
             text_width = size[0][0]
             desired_size = max(150, 0.33*best_frame.shape[1])
             font_scale = desired_size/text_width
-            cv2.putText(best_frame, time_to_show, (5, best_frame.shape[0]-7), cv2.FONT_HERSHEY_SIMPLEX,
+            cv2.putText(best_frame, time_to_show, (5, best_frame.shape[0]-7), cv2.FONT_HERSHEY_SIMPLEX, 
                 fontScale=font_scale, color=(255, 255, 255), thickness=2)
 
         ret, jpg = cv2.imencode('.jpg', best_frame)
         if ret:
-            return jpg.tobytes()
-        else:
-            return None
+            self._snapshot_jpg = jpg.tobytes()
+        
+        return self._snapshot_jpg
 
 def zone_filtered(obj: TrackedObject, object_config):
     object_name = obj.obj_data['label']
@@ -233,7 +226,7 @@ def zone_filtered(obj: TrackedObject, object_config):
         # detected object, don't add it to detected objects
         if obj_settings.min_area > obj.obj_data['area']:
             return True
-
+        
         # if the detected object is larger than the
         # max area, don't add it to detected objects
         if obj_settings.max_area < obj.obj_data['area']:
@@ -242,7 +235,7 @@ def zone_filtered(obj: TrackedObject, object_config):
         # if the score is lower than the threshold, skip
         if obj_settings.threshold > obj.computed_score:
             return True
-
+        
     return False
 
 # Maintains the state of a camera
@@ -260,8 +253,6 @@ class CameraState():
         self._current_frame = np.zeros(self.camera_config.frame_shape_yuv, np.uint8)
         self.current_frame_lock = threading.Lock()
         self.current_frame_time = 0.0
-        self.motion_boxes = []
-        self.regions = []
         self.previous_frame_id = None
         self.callbacks = defaultdict(lambda: [])
 
@@ -272,7 +263,7 @@ class CameraState():
             tracked_objects = {k: v.to_dict() for k,v in self.tracked_objects.items()}
             motion_boxes = self.motion_boxes.copy()
             regions = self.regions.copy()
-
+        
         frame_copy = cv2.cvtColor(frame_copy, cv2.COLOR_YUV2BGR_I420)
         # draw on the frame
         if draw_options.get('bounding_boxes'):
@@ -280,7 +271,7 @@ class CameraState():
             for obj in tracked_objects.values():
                 thickness = 2
                 color = COLOR_MAP[obj['label']]
-
+                
                 if obj['frame_time'] != frame_time:
                     thickness = 1
                     color = (255,0,0)
@@ -288,28 +279,28 @@ class CameraState():
                 # draw the bounding boxes on the frame
                 box = obj['box']
                 draw_box_with_label(frame_copy, box[0], box[1], box[2], box[3], obj['label'], f"{int(obj['score']*100)}% {int(obj['area'])}", thickness=thickness, color=color)
-
+        
         if draw_options.get('regions'):
             for region in regions:
                 cv2.rectangle(frame_copy, (region[0], region[1]), (region[2], region[3]), (0,255,0), 2)
+        
+        if draw_options.get('timestamp'):
+            time_to_show = datetime.datetime.fromtimestamp(frame_time).strftime("%m/%d/%Y %H:%M:%S")
+            cv2.putText(frame_copy, time_to_show, (10, 30), cv2.FONT_HERSHEY_SIMPLEX, fontScale=.8, color=(255, 255, 255), thickness=2)
 
         if draw_options.get('zones'):
             for name, zone in self.camera_config.zones.items():
                 thickness = 8 if any([name in obj['current_zones'] for obj in tracked_objects.values()]) else 2
                 cv2.drawContours(frame_copy, [zone.contour], -1, zone.color, thickness)
-
+        
         if draw_options.get('mask'):
-            mask_overlay = np.where(self.camera_config.motion.mask==[0])
+            mask_overlay = np.where(self.camera_config.mask==[0])
             frame_copy[mask_overlay] = [0,0,0]
-
+        
         if draw_options.get('motion_boxes'):
             for m_box in motion_boxes:
                 cv2.rectangle(frame_copy, (m_box[0], m_box[1]), (m_box[2], m_box[3]), (0,0,255), 2)
 
-        if draw_options.get('timestamp'):
-            time_to_show = datetime.datetime.fromtimestamp(frame_time).strftime("%m/%d/%Y %H:%M:%S")
-            cv2.putText(frame_copy, time_to_show, (10, 30), cv2.FONT_HERSHEY_SIMPLEX, fontScale=.8, color=(255, 255, 255), thickness=2)
-
         return frame_copy
 
     def finished(self, obj_id):
@@ -338,7 +329,7 @@ class CameraState():
             # call event handlers
             for c in self.callbacks['start']:
                 c(self.name, new_obj, frame_time)
-
+        
         for id in updated_ids:
             updated_obj = self.tracked_objects[id]
             significant_update = updated_obj.update(frame_time, current_detections[id])
@@ -347,17 +338,11 @@ class CameraState():
                 # ensure this frame is stored in the cache
                 if updated_obj.thumbnail_data['frame_time'] == frame_time and frame_time not in self.frame_cache:
                     self.frame_cache[frame_time] = np.copy(current_frame)
-                
-                updated_obj.last_updated = frame_time
-                
-            # if it has been more than 5 seconds since the last publish
-            # and the last update is greater than the last publish
-            if frame_time - updated_obj.last_published > 5 and updated_obj.last_updated > updated_obj.last_published:
+
                 # call event handlers
                 for c in self.callbacks['update']:
                     c(self.name, updated_obj, frame_time)
-                updated_obj.last_published = frame_time
-
+        
         for id in removed_ids:
             # publish events to mqtt
             removed_obj = self.tracked_objects[id]
@@ -376,9 +361,9 @@ class CameraState():
             if object_type in self.best_objects:
                 current_best = self.best_objects[object_type]
                 now = datetime.datetime.now().timestamp()
-                # if the object is a higher score than the current best score
+                # if the object is a higher score than the current best score 
                 # or the current object is older than desired, use the new object
-                if (is_better_thumbnail(current_best.thumbnail_data, obj.thumbnail_data, self.camera_config.frame_shape)
+                if (is_better_thumbnail(current_best.thumbnail_data, obj.thumbnail_data, self.camera_config.frame_shape) 
                     or (now - current_best.thumbnail_data['frame_time']) > self.camera_config.best_image_timeout):
                     self.best_objects[object_type] = obj
                     for c in self.callbacks['snapshot']:
@@ -387,13 +372,13 @@ class CameraState():
                 self.best_objects[object_type] = obj
                 for c in self.callbacks['snapshot']:
                     c(self.name, self.best_objects[object_type], frame_time)
-
+        
         # update overall camera state for each object type
         obj_counter = Counter()
         for obj in self.tracked_objects.values():
             if not obj.false_positive:
                 obj_counter[obj.obj_data['label']] += 1
-
+                
         # report on detected objects
         for obj_name, count in obj_counter.items():
             if count != self.object_counts[obj_name]:
@@ -409,14 +394,14 @@ class CameraState():
                 c(self.name, obj_name, 0)
             for c in self.callbacks['snapshot']:
                 c(self.name, self.best_objects[obj_name], frame_time)
-
+        
         # cleanup thumbnail frame cache
         current_thumb_frames = set([obj.thumbnail_data['frame_time'] for obj in self.tracked_objects.values() if not obj.false_positive])
         current_best_frames = set([obj.thumbnail_data['frame_time'] for obj in self.best_objects.values()])
         thumb_frames_to_delete = [t for t in self.frame_cache.keys() if not t in current_thumb_frames and not t in current_best_frames]
         for t in thumb_frames_to_delete:
             del self.frame_cache[t]
-
+        
         with self.current_frame_lock:
             self._current_frame = current_frame
             if not self.previous_frame_id is None:
@@ -442,40 +427,18 @@ class TrackedObjectProcessor(threading.Thread):
 
         def update(camera, obj: TrackedObject, current_frame_time):
             after = obj.to_dict()
-            message = { 'before': obj.previous, 'after': after, 'type': 'new' if obj.previous['false_positive'] else 'update' }
+            message = { 'before': obj.previous, 'after': after }
             self.client.publish(f"{self.topic_prefix}/events", json.dumps(message), retain=False)
             obj.previous = after
 
         def end(camera, obj: TrackedObject, current_frame_time):
-            snapshot_config = self.config.cameras[camera].snapshots
-            event_data = obj.to_dict(include_thumbnail=True)
-            event_data['has_snapshot'] = False
             if not obj.false_positive:
-                message = { 'before': obj.previous, 'after': obj.to_dict(), 'type': 'end' }
+                message = { 'before': obj.previous, 'after': obj.to_dict() }
                 self.client.publish(f"{self.topic_prefix}/events", json.dumps(message), retain=False)
-                # write snapshot to disk if enabled
-                if snapshot_config.enabled:
-                    jpg_bytes = obj.get_jpg_bytes(
-                        timestamp=snapshot_config.timestamp,
-                        bounding_box=snapshot_config.bounding_box,
-                        crop=snapshot_config.crop,
-                        height=snapshot_config.height
-                    )
-                    with open(os.path.join(CLIPS_DIR, f"{camera}-{obj.obj_data['id']}.jpg"), 'wb') as j:
-                        j.write(jpg_bytes)
-                    event_data['has_snapshot'] = True
-            self.event_queue.put(('end', camera, event_data))
+            self.event_queue.put(('end', camera, obj.to_dict(include_thumbnail=True)))
         
         def snapshot(camera, obj: TrackedObject, current_frame_time):
-            mqtt_config = self.config.cameras[camera].mqtt
-            if mqtt_config.enabled:
-                jpg_bytes = obj.get_jpg_bytes(
-                    timestamp=mqtt_config.timestamp,
-                    bounding_box=mqtt_config.bounding_box,
-                    crop=mqtt_config.crop,
-                    height=mqtt_config.height
-                )
-                self.client.publish(f"{self.topic_prefix}/{camera}/{obj.obj_data['label']}/snapshot", jpg_bytes, retain=True)
+            self.client.publish(f"{self.topic_prefix}/{camera}/{obj.obj_data['label']}/snapshot", obj.get_jpg_bytes(), retain=True)
         
         def object_status(camera, object_name, status):
             self.client.publish(f"{self.topic_prefix}/{camera}/{object_name}", status, retain=False)
@@ -498,7 +461,7 @@ class TrackedObjectProcessor(threading.Thread):
         #   }
         # }
         self.zone_data = defaultdict(lambda: defaultdict(lambda: {}))
-
+        
     def get_best(self, camera, label):
         # TODO: need a lock here
         camera_state = self.camera_states[camera]
@@ -509,7 +472,7 @@ class TrackedObjectProcessor(threading.Thread):
             return best
         else:
             return {}
-
+    
     def get_current_frame(self, camera, draw_options={}):
         return self.camera_states[camera].get_current_frame(draw_options)
 
@@ -536,7 +499,7 @@ class TrackedObjectProcessor(threading.Thread):
                 for obj in camera_state.tracked_objects.values():
                     if zone in obj.current_zones and not obj.false_positive:
                         obj_counter[obj.obj_data['label']] += 1
-
+                
                 # update counts and publish status
                 for label in set(list(self.zone_data[zone].keys()) + list(obj_counter.keys())):
                     # if we have previously published a count for this zone/label

frigate/record.py

@@ -45,9 +45,9 @@ class RecordingMaintainer(threading.Thread):
 
         files_in_use = []
         for process in psutil.process_iter():
+            if process.name() != 'ffmpeg':
+                continue
             try:
-                if process.name() != 'ffmpeg':
-                    continue
                 flist = process.open_files()
                 if flist:
                     for nt in flist:

frigate/stats.py

@@ -1,70 +0,0 @@
-import json
-import logging
-import threading
-import time
-
-from frigate.config import FrigateConfig
-from frigate.version import VERSION
-
-logger = logging.getLogger(__name__)
-
-def stats_init(camera_metrics, detectors):
-    stats_tracking = {
-        'camera_metrics': camera_metrics,
-        'detectors': detectors,
-        'started': int(time.time())
-    }
-    return stats_tracking
-
-def stats_snapshot(stats_tracking):
-    camera_metrics = stats_tracking['camera_metrics']
-    stats = {}
-
-    total_detection_fps = 0
-
-    for name, camera_stats in camera_metrics.items():
-        total_detection_fps += camera_stats['detection_fps'].value
-        stats[name] = {
-            'camera_fps': round(camera_stats['camera_fps'].value, 2),
-            'process_fps': round(camera_stats['process_fps'].value, 2),
-            'skipped_fps': round(camera_stats['skipped_fps'].value, 2),
-            'detection_fps': round(camera_stats['detection_fps'].value, 2),
-            'pid': camera_stats['process'].pid,
-            'capture_pid': camera_stats['capture_process'].pid
-        }
-
-    stats['detectors'] = {}
-    for name, detector in stats_tracking["detectors"].items():
-        stats['detectors'][name] = {
-            'inference_speed': round(detector.avg_inference_speed.value * 1000, 2),
-            'detection_start': detector.detection_start.value,
-            'pid': detector.detect_process.pid
-        }
-    stats['detection_fps'] = round(total_detection_fps, 2)
-
-    stats['service'] = {
-        'uptime': (int(time.time()) - stats_tracking['started']),
-        'version': VERSION
-    }
-
-    return stats
-
-class StatsEmitter(threading.Thread):
-    def __init__(self, config: FrigateConfig, stats_tracking, mqtt_client, topic_prefix, stop_event):
-        threading.Thread.__init__(self)
-        self.name = 'frigate_stats_emitter'
-        self.config = config
-        self.stats_tracking = stats_tracking
-        self.mqtt_client = mqtt_client
-        self.topic_prefix = topic_prefix
-        self.stop_event = stop_event
-
-    def run(self):
-        time.sleep(10)
-        while True:
-            if self.stop_event.is_set():
-                logger.info(f"Exiting watchdog...")
-                break
-            stats = stats_snapshot(self.stats_tracking)
-            self.mqtt_client.publish(f"{self.topic_prefix}/stats", json.dumps(stats), retain=False)
-            time.sleep(self.config.mqtt.stats_interval)

frigate/test/test_config.py

@@ -191,12 +191,12 @@ class TestConfig(TestCase):
         frigate_config = FrigateConfig(config=config)
         assert('-re' in frigate_config.cameras['back'].ffmpeg_cmds[0]['cmd'])
     
-    def test_inherit_clips_retention(self):
+    def test_inherit_save_clips_retention(self):
         config = {
             'mqtt': {
                 'host': 'mqtt'
             },
-            'clips': {
+            'save_clips': {
                 'retain': {
                     'default': 20,
                     'objects': {
@@ -217,14 +217,14 @@ class TestConfig(TestCase):
             }
         }
         frigate_config = FrigateConfig(config=config)
-        assert(frigate_config.cameras['back'].clips.retain.objects['person'] == 30)
+        assert(frigate_config.cameras['back'].save_clips.retain.objects['person'] == 30)
     
     def test_roles_listed_twice_throws_error(self):
         config = {
             'mqtt': {
                 'host': 'mqtt'
             },
-            'clips': {
+            'save_clips': {
                 'retain': {
                     'default': 20,
                     'objects': {
@@ -252,7 +252,7 @@ class TestConfig(TestCase):
             'mqtt': {
                 'host': 'mqtt'
             },
-            'clips': {
+            'save_clips': {
                 'retain': {
                     'default': 20,
                     'objects': {
@@ -279,12 +279,12 @@ class TestConfig(TestCase):
         }
         self.assertRaises(vol.MultipleInvalid, lambda: FrigateConfig(config=config))
     
-    def test_clips_should_default_to_global_objects(self):
+    def test_save_clips_should_default_to_global_objects(self):
         config = {
             'mqtt': {
                 'host': 'mqtt'
             },
-            'clips': {
+            'save_clips': {
                 'retain': {
                     'default': 20,
                     'objects': {
@@ -304,14 +304,16 @@ class TestConfig(TestCase):
                     },
                     'height': 1080,
                     'width': 1920,
-                    'clips': {
+                    'save_clips': {
                         'enabled': True
                     }
                 }
             }
         }
         config = FrigateConfig(config=config)
-        assert(config.cameras['back'].clips.objects is None)
+        assert(len(config.cameras['back'].save_clips.objects) == 2)
+        assert('dog' in config.cameras['back'].save_clips.objects)
+        assert('person' in config.cameras['back'].save_clips.objects)
     
     def test_role_assigned_but_not_enabled(self):
         json_config = {
@@ -323,7 +325,7 @@ class TestConfig(TestCase):
                     'ffmpeg': {
                         'inputs': [
                             { 'path': 'rtsp://10.0.0.1:554/video', 'roles': ['detect', 'rtmp'] },
-                            { 'path': 'rtsp://10.0.0.1:554/record', 'roles': ['record'] }
+                            { 'path': 'rtsp://10.0.0.1:554/clips', 'roles': ['clips'] }
                         ]
                     },
                     'height': 1080,

frigate/util.py

@@ -2,7 +2,6 @@ import collections
 import datetime
 import hashlib
 import json
-import logging
 import signal
 import subprocess as sp
 import threading
@@ -16,8 +15,6 @@ import cv2
 import matplotlib.pyplot as plt
 import numpy as np
 
-logger = logging.getLogger(__name__)
-
 
 def draw_box_with_label(frame, x_min, y_min, x_max, y_max, label, info, thickness=2, color=None, position='ul'):
     if color is None:
@@ -291,24 +288,6 @@ def print_stack(sig, frame):
 def listen():
     signal.signal(signal.SIGUSR1, print_stack)
 
-def create_mask(frame_shape, mask):
-    mask_img = np.zeros(frame_shape, np.uint8)
-    mask_img[:] = 255
-
-    if isinstance(mask, list):
-        for m in mask:
-            add_mask(m, mask_img)
-
-    elif isinstance(mask, str):
-        add_mask(mask, mask_img)
-
-    return mask_img
-
-def add_mask(mask, mask_img):
-    points = mask.split(',')
-    contour =  np.array([[int(points[i]), int(points[i+1])] for i in range(0, len(points), 2)])
-    cv2.fillPoly(mask_img, pts=[contour], color=(0))
-
 class FrameManager(ABC):
     @abstractmethod
     def create(self, name, size) -> AnyStr:

frigate/video.py

@@ -13,7 +13,6 @@ import signal
 import threading
 import time
 from collections import defaultdict
-from setproctitle import setproctitle
 from typing import Dict, List
 
 import cv2
@@ -31,7 +30,7 @@ from frigate.util import (EventsPerSecond, FrameManager,
 
 logger = logging.getLogger(__name__)
 
-def filtered(obj, objects_to_track, object_filters):
+def filtered(obj, objects_to_track, object_filters, mask=None):
     object_name = obj[0]
 
     if not object_name in objects_to_track:
@@ -54,15 +53,14 @@ def filtered(obj, objects_to_track, object_filters):
         if obj_settings.min_score > obj[1]:
             return True
     
-        if not obj_settings.mask is None:
-            # compute the coordinates of the object and make sure
-            # the location isnt outside the bounds of the image (can happen from rounding)
-            y_location = min(int(obj[2][3]), len(obj_settings.mask)-1)
-            x_location = min(int((obj[2][2]-obj[2][0])/2.0)+obj[2][0], len(obj_settings.mask[0])-1)
+        # compute the coordinates of the object and make sure
+        # the location isnt outside the bounds of the image (can happen from rounding)
+        y_location = min(int(obj[2][3]), len(mask)-1)
+        x_location = min(int((obj[2][2]-obj[2][0])/2.0)+obj[2][0], len(mask[0])-1)
 
-            # if the object is in a masked location, don't add it to detected objects
-            if obj_settings.mask[y_location][x_location] == 0:
-                return True
+        # if the object is in a masked location, don't add it to detected objects
+        if (not mask is None) and (mask[y_location][x_location] == 0):
+            return True
         
     return False
 
@@ -181,7 +179,6 @@ class CameraWatchdog(threading.Thread):
             now = datetime.datetime.now().timestamp()
 
             if not self.capture_thread.is_alive():
-                self.logpipe.dump()
                 self.start_ffmpeg_detect()
             elif now - self.capture_thread.current_frame.value > 20:
                 self.logger.info(f"No frames received from {self.camera_name} in 20 seconds. Exiting ffmpeg...")
@@ -198,7 +195,6 @@ class CameraWatchdog(threading.Thread):
                 poll = p['process'].poll()
                 if poll == None:
                     continue
-                p['logpipe'].dump()
                 p['process'] = start_or_restart_ffmpeg(p['cmd'], self.logger, p['logpipe'], ffmpeg_process=p['process'])
             
             # wait a bit before checking again
@@ -253,17 +249,16 @@ def track_camera(name, config: CameraConfig, model_shape, detection_queue, resul
     signal.signal(signal.SIGINT, receiveSignal)
 
     threading.current_thread().name = f"process:{name}"
-    setproctitle(f"frigate.process:{name}")
     listen()
 
     frame_queue = process_info['frame_queue']
-    detection_enabled = process_info['detection_enabled']
 
     frame_shape = config.frame_shape
     objects_to_track = config.objects.track
     object_filters = config.objects.filters
+    mask = config.mask
 
-    motion_detector = MotionDetector(frame_shape, config.motion)
+    motion_detector = MotionDetector(frame_shape, mask, config.motion)
     object_detector = RemoteObjectDetector(name, '/labelmap.txt', detection_queue, result_connection, model_shape)
 
     object_tracker = ObjectTracker(config.detect)
@@ -271,7 +266,7 @@ def track_camera(name, config: CameraConfig, model_shape, detection_queue, resul
     frame_manager = SharedMemoryFrameManager()
 
     process_frames(name, frame_queue, frame_shape, model_shape, frame_manager, motion_detector, object_detector,
-        object_tracker, detected_objects_queue, process_info, objects_to_track, object_filters, detection_enabled, stop_event)
+        object_tracker, detected_objects_queue, process_info, objects_to_track, object_filters, mask, stop_event)
 
     logger.info(f"{name}: exiting subprocess")
 
@@ -281,7 +276,7 @@ def reduce_boxes(boxes):
     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 detect(object_detector, frame, model_shape, region, objects_to_track, object_filters):
+def detect(object_detector, frame, model_shape, region, objects_to_track, object_filters, mask):
     tensor_input = create_tensor_input(frame, model_shape, region)
 
     detections = []
@@ -299,7 +294,7 @@ def detect(object_detector, frame, model_shape, region, objects_to_track, object
             (x_max-x_min)*(y_max-y_min),
             region)
         # apply object filters
-        if filtered(det, objects_to_track, object_filters):
+        if filtered(det, objects_to_track, object_filters, mask):
             continue
         detections.append(det)
     return detections
@@ -308,7 +303,7 @@ def process_frames(camera_name: str, frame_queue: mp.Queue, frame_shape, model_s
     frame_manager: FrameManager, motion_detector: MotionDetector, 
     object_detector: RemoteObjectDetector, object_tracker: ObjectTracker,
     detected_objects_queue: mp.Queue, process_info: Dict,
-    objects_to_track: List[str], object_filters, detection_enabled: mp.Value, stop_event,
+    objects_to_track: List[str], object_filters, mask, stop_event,
     exit_on_empty: bool = False):
     
     fps = process_info['process_fps']
@@ -339,14 +334,6 @@ def process_frames(camera_name: str, frame_queue: mp.Queue, frame_shape, model_s
             logger.info(f"{camera_name}: frame {frame_time} is not in memory store.")
             continue
 
-        if not detection_enabled.value:
-            fps.value = fps_tracker.eps()
-            object_tracker.match_and_update(frame_time, [])
-            detected_objects_queue.put((camera_name, frame_time, object_tracker.tracked_objects, [], []))
-            detection_fps.value = object_detector.fps.eps()
-            frame_manager.close(f"{camera_name}{frame_time}")
-            continue
-
         # look for motion
         motion_boxes = motion_detector.detect(frame)
 
@@ -369,7 +356,7 @@ def process_frames(camera_name: str, frame_queue: mp.Queue, frame_shape, model_s
         # resize regions and detect
         detections = []
         for region in regions:
-            detections.extend(detect(object_detector, frame, model_shape, region, objects_to_track, object_filters))
+            detections.extend(detect(object_detector, frame, model_shape, region, objects_to_track, object_filters, mask))
         
         #########
         # merge objects, check for clipped objects and look again up to 4 times
@@ -404,7 +391,7 @@ def process_frames(camera_name: str, frame_queue: mp.Queue, frame_shape, model_s
 
                         regions.append(region)
                         
-                        selected_objects.extend(detect(object_detector, frame, model_shape, region, objects_to_track, object_filters))
+                        selected_objects.extend(detect(object_detector, frame, model_shape, region, objects_to_track, object_filters, mask))
 
                         refining = True
                     else:
@@ -421,11 +408,11 @@ def process_frames(camera_name: str, frame_queue: mp.Queue, frame_shape, model_s
 
         # add to the queue if not full
         if(detected_objects_queue.full()):
-            frame_manager.delete(f"{camera_name}{frame_time}")
-            continue
+          frame_manager.delete(f"{camera_name}{frame_time}")
+          continue
         else:
-            fps_tracker.update()
-            fps.value = fps_tracker.eps()
-            detected_objects_queue.put((camera_name, frame_time, object_tracker.tracked_objects, motion_boxes, regions))
-            detection_fps.value = object_detector.fps.eps()
-            frame_manager.close(f"{camera_name}{frame_time}")
+          fps_tracker.update()
+          fps.value = fps_tracker.eps()
+          detected_objects_queue.put((camera_name, frame_time, object_tracker.tracked_objects, motion_boxes, regions))
+          detection_fps.value = object_detector.fps.eps()
+          frame_manager.close(f"{camera_name}{frame_time}")

frigate/watchdog.py

@@ -2,8 +2,6 @@ import datetime
 import logging
 import threading
 import time
-import os
-import signal
 
 logger = logging.getLogger(__name__)
 
@@ -34,5 +32,5 @@ class FrigateWatchdog(threading.Thread):
                     logger.info("Detection appears to be stuck. Restarting detection process")
                     detector.start_or_restart()
                 elif not detector.detect_process.is_alive():
-                    logger.info("Detection appears to have stopped. Restarting frigate")
-                    os.kill(os.getpid(), signal.SIGTERM)
+                    logger.info("Detection appears to have stopped. Restarting detection process")
+                    detector.start_or_restart()

migrations/001_create_events_table.py

@@ -1,41 +0,0 @@
-"""Peewee migrations -- 001_create_events_table.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 decimal import ROUND_HALF_EVEN
-
-try:
-    import playhouse.postgres_ext as pw_pext
-except ImportError:
-    pass
-
-SQL = pw.SQL
-
-def migrate(migrator, database, fake=False, **kwargs):
-    migrator.sql('CREATE TABLE IF NOT EXISTS "event" ("id" VARCHAR(30) NOT NULL PRIMARY KEY, "label" VARCHAR(20) NOT NULL, "camera" VARCHAR(20) NOT NULL, "start_time" DATETIME NOT NULL, "end_time" DATETIME NOT NULL, "top_score" REAL NOT NULL, "false_positive" INTEGER NOT NULL, "zones" JSON NOT NULL, "thumbnail" TEXT NOT NULL)')
-    migrator.sql('CREATE INDEX IF NOT EXISTS "event_label" ON "event" ("label")')
-    migrator.sql('CREATE INDEX IF NOT EXISTS "event_camera" ON "event" ("camera")')
-
-def rollback(migrator, database, fake=False, **kwargs):
-    pass

migrations/002_add_clip_snapshot.py

@@ -1,41 +0,0 @@
-"""Peewee migrations -- 002_add_clip_snapshot.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 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.add_fields(Event, has_clip=pw.BooleanField(default=True), has_snapshot=pw.BooleanField(default=True))
-
-def rollback(migrator, database, fake=False, **kwargs):
-    migrator.remove_fields(Event, ['has_clip', 'has_snapshot'])

nginx/nginx.conf

@@ -23,12 +23,6 @@ http {
 
     keepalive_timeout  65;
 
-    gzip on;
-    gzip_comp_level 6;
-    gzip_types text/plain text/css application/json application/x-javascript application/javascript text/javascript image/svg+xml image/x-icon image/bmp image/png image/gif image/jpeg image/jpg;
-    gzip_proxied no-cache no-store private expired auth;
-    gzip_vary on;
-
     upstream frigate_api {
       server localhost:5001;
       keepalive 1024;
@@ -102,36 +96,13 @@ http {
             root /media/frigate;
         }
 
-        location /api/ {
-            add_header 'Access-Control-Allow-Origin' '*';
-            add_header Cache-Control "no-store";
+        location / {
             proxy_pass http://frigate_api/;
             proxy_pass_request_headers on;
             proxy_set_header Host $host;
             proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
             proxy_set_header X-Forwarded-Proto $scheme;
         }
-
-
-        location / {
-            add_header Cache-Control "no-cache";
-
-            location ~* \.(?:js|css|svg|ico|png)$ {
-                access_log off;
-                expires 1y;
-                add_header Cache-Control "public";
-            }
-
-            sub_filter 'href="/' 'href="$http_x_ingress_path/';
-            sub_filter 'url(/' 'url($http_x_ingress_path/';
-            sub_filter '"/js/' '"$http_x_ingress_path/js/';
-            sub_filter '<body>' '<body><script>window.baseUrl="$http_x_ingress_path";</script>';
-            sub_filter_types text/css application/javascript;
-            sub_filter_once off;
-
-            root /opt/frigate/web;
-            try_files $uri $uri/ /index.html;
-        }
     }
 }
 
@@ -148,4 +119,4 @@ rtmp {
             meta copy;
         }
     }
-}
+}

web/.dockerignore

@@ -1 +0,0 @@
-node_modules

web/README.md

@@ -1,8 +0,0 @@
-# Frigate Web UI
-
-## Development
-
-1. Build the docker images in the root of the repository `make amd64_all` (or appropriate for your system)
-2. Create a config file in `config/`
-3. Run the container: `docker run --rm --name frigate --privileged -v $PWD/config:/config:ro -v /etc/localtime:/etc/localtime:ro -p 5000:5000 frigate`
-4. Run the dev ui: `cd web && npm run start`

web/package.json

@@ -1,24 +0,0 @@
-{
-  "name": "frigate",
-  "private": true,
-  "scripts": {
-    "start": "cross-env SNOWPACK_PUBLIC_API_HOST=http://localhost:5000 snowpack dev",
-    "prebuild": "rimraf build",
-    "build": "snowpack build"
-  },
-  "dependencies": {
-    "@prefresh/snowpack": "^3.0.1",
-    "@snowpack/plugin-postcss": "^1.1.0",
-    "@snowpack/plugin-webpack": "^2.3.0",
-    "autoprefixer": "^10.2.1",
-    "cross-env": "^7.0.3",
-    "immer": "^8.0.1",
-    "postcss": "^8.2.2",
-    "postcss-cli": "^8.3.1",
-    "preact": "^10.5.9",
-    "preact-router": "^3.2.1",
-    "rimraf": "^3.0.2",
-    "snowpack": "^3.0.11",
-    "tailwindcss": "^2.0.2"
-  }
-}

web/postcss.config.js

@@ -1,8 +0,0 @@
-'use strict';
-
-module.exports = {
-  plugins: [
-    require('tailwindcss'),
-    require('autoprefixer'),
-  ],
-};

web/public/index.html

@@ -1,21 +0,0 @@
-<!DOCTYPE html>
-<html lang="en">
-  <head>
-    <meta charset="utf-8" />
-    <meta name="viewport" content="width=device-width, initial-scale=1" />
-    <link rel="icon" href="/favicon.ico" />
-    <title>Frigate</title>
-    <link rel="apple-touch-icon" sizes="180x180" href="/apple-touch-icon.png" />
-    <link rel="icon" type="image/png" sizes="32x32" href="/favicon-32x32.png" />
-    <link rel="icon" type="image/png" sizes="16x16" href="/favicon-16x16.png" />
-    <link rel="manifest" href="/site.webmanifest" />
-    <link rel="mask-icon" href="/safari-pinned-tab.svg" color="#3b82f7" />
-    <meta name="msapplication-TileColor" content="#3b82f7" />
-    <meta name="theme-color" content="#ff0000" />
-  </head>
-  <body>
-    <div id="root"></div>
-    <noscript>You need to enable JavaScript to run this app.</noscript>
-    <script type="module" src="/dist/index.js"></script>
-  </body>
-</html>

web/public/safari-pinned-tab.svg

@@ -1,46 +0,0 @@
-<?xml version="1.0" standalone="no"?>
-<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 20010904//EN"
- "http://www.w3.org/TR/2001/REC-SVG-20010904/DTD/svg10.dtd">
-<svg version="1.0" xmlns="http://www.w3.org/2000/svg"
- width="888.000000pt" height="888.000000pt" viewBox="0 0 888.000000 888.000000"
- preserveAspectRatio="xMidYMid meet">
-<metadata>
-Created by potrace 1.11, written by Peter Selinger 2001-2013
-</metadata>
-<g transform="translate(0.000000,888.000000) scale(0.100000,-0.100000)"
-fill="#000000" stroke="none">
-<path d="M8228 8865 c-2 -2 -25 -6 -53 -9 -38 -5 -278 -56 -425 -91 -33 -7
--381 -98 -465 -121 -49 -14 -124 -34 -165 -45 -67 -18 -485 -138 -615 -176
--50 -14 -106 -30 -135 -37 -8 -2 -35 -11 -60 -19 -25 -8 -85 -27 -135 -42 -49
--14 -101 -31 -115 -36 -14 -5 -34 -11 -45 -13 -11 -3 -65 -19 -120 -36 -55
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-21 -47 39 -87 39 -90 0 -7 217 -438 261 -521 109 -201 293 -501 347 -564 11
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-75 61 78 64 302 229 426 313 248 169 483 297 600 326 53 14 205 6 365 -17 33
--5 155 -8 270 -6 179 3 226 7 316 28 58 13 140 25 182 26 82 2 120 6 217 22
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-69 -6 132 -8 715 -20 484 -11 620 -8 729 16 85 19 131 63 98 96 -25 26 -104
-34 -302 32 -373 -2 -408 -1 -471 26 -90 37 2 102 171 120 33 3 76 8 95 10 19
-2 71 7 115 10 243 17 267 20 338 37 145 36 47 102 -203 137 -136 19 -262 25
--490 22 -124 -2 -362 -4 -530 -4 l-305 -1 -56 26 c-65 31 -171 109 -238 176
--52 51 -141 173 -141 191 0 6 -6 22 -14 34 -18 27 -54 165 -64 244 -12 98 -6
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-10 83 2 13 7 53 11 90 3 37 8 74 9 83 22 118 22 279 -1 464 -20 172 -20 172
-70 238 108 79 426 248 666 355 25 11 77 34 115 52 92 42 443 191 570 242 55
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-225 95 237 100 333 143 490 220 229 113 348 191 337 223 -3 10 -70 20 -79 12z"/>
-</g>
-</svg>

web/public/site.webmanifest

@@ -1,19 +0,0 @@
-{
-    "name": "",
-    "short_name": "",
-    "icons": [
-        {
-            "src": "/android-chrome-192x192.png",
-            "sizes": "192x192",
-            "type": "image/png"
-        },
-        {
-            "src": "/android-chrome-512x512.png",
-            "sizes": "512x512",
-            "type": "image/png"
-        }
-    ],
-    "theme_color": "#ff0000",
-    "background_color": "#ff0000",
-    "display": "standalone"
-}

web/snowpack.config.js

@@ -1,25 +0,0 @@
-'use strict';
-
-module.exports = {
-  mount: {
-    public: { url: '/', static: true },
-    src: { url: '/dist' },
-  },
-  plugins: [
-    '@snowpack/plugin-postcss',
-    '@prefresh/snowpack',
-    [
-      '@snowpack/plugin-webpack',
-      {
-        sourceMap: true,
-      },
-    ],
-  ],
-  routes: [{ match: 'routes', src: '.*', dest: '/index.html' }],
-  packageOptions: {
-    sourcemap: false,
-  },
-  buildOptions: {
-    sourcemap: true,
-  },
-};

web/src/App.jsx

@@ -1,34 +0,0 @@
-import { h } from 'preact';
-import ActivityIndicator from './components/ActivityIndicator';
-import Camera from './Camera';
-import CameraMap from './CameraMap';
-import Cameras from './Cameras';
-import Debug from './Debug';
-import Event from './Event';
-import Events from './Events';
-import { Router } from 'preact-router';
-import Sidebar from './Sidebar';
-import Api, { FetchStatus, useConfig } from './api';
-
-export default function App() {
-  const { data, status } = useConfig();
-  return status !== FetchStatus.LOADED ? (
-    <div className="flex flex-grow-1 min-h-screen justify-center items-center">
-      <ActivityIndicator />
-    </div>
-  ) : (
-    <div className="md:flex flex-col md:flex-row md:min-h-screen w-full bg-gray-100 dark:bg-gray-800 text-gray-900 dark:text-white">
-      <Sidebar />
-      <div className="flex-auto p-2 md:p-4 lg:pl-8 lg:pr-8 min-w-0">
-        <Router>
-          <CameraMap path="/cameras/:camera/editor" />
-          <Camera path="/cameras/:camera" />
-          <Event path="/events/:eventId" />
-          <Events path="/events" />
-          <Debug path="/debug" />
-          <Cameras default path="/" />
-        </Router>
-      </div>
-    </div>
-  );
-}

web/src/Camera.jsx

@@ -1,68 +0,0 @@
-import { h } from 'preact';
-import AutoUpdatingCameraImage from './components/AutoUpdatingCameraImage';
-import Box from './components/Box';
-import Heading from './components/Heading';
-import Link from './components/Link';
-import Switch from './components/Switch';
-import { route } from 'preact-router';
-import { useCallback, useContext } from 'preact/hooks';
-import { useApiHost, useConfig } from './api';
-
-export default function Camera({ camera, url }) {
-  const { data: config } = useConfig();
-  const apiHost = useApiHost();
-
-  if (!config) {
-    return <div>{`No camera named ${camera}`}</div>;
-  }
-
-  const cameraConfig = config.cameras[camera];
-
-  const { pathname, searchParams } = new URL(`${window.location.protocol}//${window.location.host}${url}`);
-  const searchParamsString = searchParams.toString();
-
-  const handleSetOption = useCallback(
-    (id, value) => {
-      searchParams.set(id, value ? 1 : 0);
-      route(`${pathname}?${searchParams.toString()}`, true);
-    },
-    [searchParams]
-  );
-
-  function getBoolean(id) {
-    return Boolean(parseInt(searchParams.get(id), 10));
-  }
-
-  return (
-    <div className="space-y-4">
-      <Heading size="2xl">{camera}</Heading>
-      <Box>
-        <AutoUpdatingCameraImage camera={camera} searchParams={searchParamsString} />
-      </Box>
-
-      <Box className="grid grid-cols-2 md:grid-cols-3 lg:grid-cols-4 gap-4 p-4">
-        <Switch checked={getBoolean('bbox')} id="bbox" label="Bounding box" onChange={handleSetOption} />
-        <Switch checked={getBoolean('timestamp')} id="timestamp" label="Timestamp" onChange={handleSetOption} />
-        <Switch checked={getBoolean('zones')} id="zones" label="Zones" onChange={handleSetOption} />
-        <Switch checked={getBoolean('mask')} id="mask" label="Masks" onChange={handleSetOption} />
-        <Switch checked={getBoolean('motion')} id="motion" label="Motion boxes" onChange={handleSetOption} />
-        <Switch checked={getBoolean('regions')} id="regions" label="Regions" onChange={handleSetOption} />
-        <Link href={`/cameras/${camera}/editor`}>Mask & Zone creator</Link>
-      </Box>
-
-      <div className="space-y-4">
-        <Heading size="sm">Tracked objects</Heading>
-        <div className="grid grid-cols-3 md:grid-cols-4 gap-4">
-          {cameraConfig.objects.track.map((objectType) => {
-            return (
-              <Box key={objectType} hover href={`/events?camera=${camera}&label=${objectType}`}>
-                <Heading size="sm">{objectType}</Heading>
-                <img src={`${apiHost}/api/${camera}/${objectType}/best.jpg?crop=1&h=150`} />
-              </Box>
-            );
-          })}
-        </div>
-      </div>
-    </div>
-  );
-}

web/src/CameraMap.jsx

@@ -1,640 +0,0 @@
-import { h } from 'preact';
-import Box from './components/Box';
-import Button from './components/Button';
-import Heading from './components/Heading';
-import Switch from './components/Switch';
-import { route } from 'preact-router';
-import { useCallback, useContext, useEffect, useMemo, useRef, useState } from 'preact/hooks';
-import { useApiHost, useConfig } from './api';
-
-export default function CameraMasks({ camera, url }) {
-  const { data: config } = useConfig();
-  const apiHost = useApiHost();
-  const imageRef = useRef(null);
-  const [imageScale, setImageScale] = useState(1);
-  const [snap, setSnap] = useState(true);
-
-  if (!(camera in config.cameras)) {
-    return <div>{`No camera named ${camera}`}</div>;
-  }
-
-  const cameraConfig = config.cameras[camera];
-  const {
-    width,
-    height,
-    motion: { mask: motionMask },
-    objects: { filters: objectFilters },
-    zones,
-  } = cameraConfig;
-
-  const resizeObserver = useMemo(
-    () =>
-      new ResizeObserver((entries) => {
-        window.requestAnimationFrame(() => {
-          if (Array.isArray(entries) && entries.length) {
-            const scaledWidth = entries[0].contentRect.width;
-            const scale = scaledWidth / width;
-            setImageScale(scale);
-          }
-        });
-      }),
-    [camera, width, setImageScale]
-  );
-
-  useEffect(() => {
-    if (!imageRef.current) {
-      return;
-    }
-    resizeObserver.observe(imageRef.current);
-  }, [resizeObserver, imageRef.current]);
-
-  const [motionMaskPoints, setMotionMaskPoints] = useState(
-    Array.isArray(motionMask)
-      ? motionMask.map((mask) => getPolylinePoints(mask))
-      : motionMask
-      ? [getPolylinePoints(motionMask)]
-      : []
-  );
-
-  const [zonePoints, setZonePoints] = useState(
-    Object.keys(zones).reduce((memo, zone) => ({ ...memo, [zone]: getPolylinePoints(zones[zone].coordinates) }), {})
-  );
-
-  const [objectMaskPoints, setObjectMaskPoints] = useState(
-    Object.keys(objectFilters).reduce(
-      (memo, name) => ({
-        ...memo,
-        [name]: Array.isArray(objectFilters[name].mask)
-          ? objectFilters[name].mask.map((mask) => getPolylinePoints(mask))
-          : objectFilters[name].mask
-          ? [getPolylinePoints(objectFilters[name].mask)]
-          : [],
-      }),
-      {}
-    )
-  );
-
-  const [editing, setEditing] = useState({ set: motionMaskPoints, key: 0, fn: setMotionMaskPoints });
-
-  const handleUpdateEditable = useCallback(
-    (newPoints) => {
-      let newSet;
-      if (Array.isArray(editing.set)) {
-        newSet = [...editing.set];
-        newSet[editing.key] = newPoints;
-      } else if (editing.subkey !== undefined) {
-        newSet = { ...editing.set };
-        newSet[editing.key][editing.subkey] = newPoints;
-      } else {
-        newSet = { ...editing.set, [editing.key]: newPoints };
-      }
-      editing.set = newSet;
-      editing.fn(newSet);
-    },
-    [editing]
-  );
-
-  const handleSelectEditable = useCallback(
-    (name) => {
-      setEditing(name);
-    },
-    [setEditing]
-  );
-
-  const handleRemoveEditable = useCallback(
-    (name) => {
-      const filteredZonePoints = Object.keys(zonePoints)
-        .filter((zoneName) => zoneName !== name)
-        .reduce((memo, name) => {
-          memo[name] = zonePoints[name];
-          return memo;
-        }, {});
-      setZonePoints(filteredZonePoints);
-    },
-    [zonePoints, setZonePoints]
-  );
-
-  // Motion mask methods
-  const handleAddMask = useCallback(() => {
-    const newMotionMaskPoints = [...motionMaskPoints, []];
-    setMotionMaskPoints(newMotionMaskPoints);
-    setEditing({ set: newMotionMaskPoints, key: newMotionMaskPoints.length - 1, fn: setMotionMaskPoints });
-  }, [motionMaskPoints, setMotionMaskPoints]);
-
-  const handleEditMask = useCallback(
-    (key) => {
-      setEditing({ set: motionMaskPoints, key, fn: setMotionMaskPoints });
-    },
-    [setEditing, motionMaskPoints, setMotionMaskPoints]
-  );
-
-  const handleRemoveMask = useCallback(
-    (key) => {
-      const newMotionMaskPoints = [...motionMaskPoints];
-      newMotionMaskPoints.splice(key, 1);
-      setMotionMaskPoints(newMotionMaskPoints);
-    },
-    [motionMaskPoints, setMotionMaskPoints]
-  );
-
-  const handleCopyMotionMasks = useCallback(async () => {
-    await window.navigator.clipboard.writeText(`  motion:
-    mask:
-${motionMaskPoints.map((mask, i) => `      - ${polylinePointsToPolyline(mask)}`).join('\n')}`);
-  }, [motionMaskPoints]);
-
-  // Zone methods
-  const handleEditZone = useCallback(
-    (key) => {
-      setEditing({ set: zonePoints, key, fn: setZonePoints });
-    },
-    [setEditing, zonePoints, setZonePoints]
-  );
-
-  const handleAddZone = useCallback(() => {
-    const n = Object.keys(zonePoints).filter((name) => name.startsWith('zone_')).length;
-    const zoneName = `zone_${n}`;
-    const newZonePoints = { ...zonePoints, [zoneName]: [] };
-    setZonePoints(newZonePoints);
-    setEditing({ set: newZonePoints, key: zoneName, fn: setZonePoints });
-  }, [zonePoints, setZonePoints]);
-
-  const handleRemoveZone = useCallback(
-    (key) => {
-      const newZonePoints = { ...zonePoints };
-      delete newZonePoints[key];
-      setZonePoints(newZonePoints);
-    },
-    [zonePoints, setZonePoints]
-  );
-
-  const handleCopyZones = useCallback(async () => {
-    await window.navigator.clipboard.writeText(`  zones:
-${Object.keys(zonePoints)
-  .map(
-    (zoneName) => `    ${zoneName}:
-      coordinates: ${polylinePointsToPolyline(zonePoints[zoneName])}`
-  )
-  .join('\n')}`);
-  }, [zonePoints]);
-
-  // Object methods
-  const handleEditObjectMask = useCallback(
-    (key, subkey) => {
-      setEditing({ set: objectMaskPoints, key, subkey, fn: setObjectMaskPoints });
-    },
-    [setEditing, objectMaskPoints, setObjectMaskPoints]
-  );
-
-  const handleAddObjectMask = useCallback(() => {
-    const n = Object.keys(objectMaskPoints).filter((name) => name.startsWith('object_')).length;
-    const newObjectName = `object_${n}`;
-    const newObjectMaskPoints = { ...objectMaskPoints, [newObjectName]: [[]] };
-    setObjectMaskPoints(newObjectMaskPoints);
-    setEditing({ set: newObjectMaskPoints, key: newObjectName, subkey: 0, fn: setObjectMaskPoints });
-  }, [objectMaskPoints, setObjectMaskPoints, setEditing]);
-
-  const handleRemoveObjectMask = useCallback(
-    (key, subkey) => {
-      const newObjectMaskPoints = { ...objectMaskPoints };
-      delete newObjectMaskPoints[key][subkey];
-      setObjectMaskPoints(newObjectMaskPoints);
-    },
-    [objectMaskPoints, setObjectMaskPoints]
-  );
-
-  const handleCopyObjectMasks = useCallback(async () => {
-    await window.navigator.clipboard.writeText(`  objects:
-    filters:
-${Object.keys(objectMaskPoints)
-  .map((objectName) =>
-    objectMaskPoints[objectName].length
-      ? `      ${objectName}:
-        mask: ${polylinePointsToPolyline(objectMaskPoints[objectName])}`
-      : ''
-  )
-  .filter(Boolean)
-  .join('\n')}`);
-  }, [objectMaskPoints]);
-
-  const handleAddToObjectMask = useCallback(
-    (key) => {
-      const newObjectMaskPoints = { ...objectMaskPoints, [key]: [...objectMaskPoints[key], []] };
-      setObjectMaskPoints(newObjectMaskPoints);
-      setEditing({
-        set: newObjectMaskPoints,
-        key,
-        subkey: newObjectMaskPoints[key].length - 1,
-        fn: setObjectMaskPoints,
-      });
-    },
-    [objectMaskPoints, setObjectMaskPoints, setEditing]
-  );
-
-  const handleChangeSnap = useCallback(
-    (id, value) => {
-      setSnap(value);
-    },
-    [setSnap]
-  );
-
-  return (
-    <div class="flex-col space-y-4">
-      <Heading size="2xl">{camera} mask & zone creator</Heading>
-
-      <Box>
-        <p>
-          This tool can help you create masks & zones for your {camera} camera. When done, copy each mask configuration
-          into your <code className="font-mono">config.yml</code> file restart your Frigate instance to save your
-          changes.
-        </p>
-      </Box>
-
-      <Box className="space-y-4">
-        <div className="relative">
-          <img ref={imageRef} src={`${apiHost}/api/${camera}/latest.jpg`} />
-          <EditableMask
-            onChange={handleUpdateEditable}
-            points={'subkey' in editing ? editing.set[editing.key][editing.subkey] : editing.set[editing.key]}
-            scale={imageScale}
-            snap={snap}
-            width={width}
-            height={height}
-          />
-        </div>
-        <Switch checked={snap} label="Snap to edges" onChange={handleChangeSnap} />
-      </Box>
-
-      <div class="flex-col space-y-4">
-        <MaskValues
-          editing={editing}
-          title="Motion masks"
-          onCopy={handleCopyMotionMasks}
-          onCreate={handleAddMask}
-          onEdit={handleEditMask}
-          onRemove={handleRemoveMask}
-          points={motionMaskPoints}
-          yamlPrefix={'motion:\n  mask:'}
-          yamlKeyPrefix={maskYamlKeyPrefix}
-        />
-
-        <MaskValues
-          editing={editing}
-          title="Zones"
-          onCopy={handleCopyZones}
-          onCreate={handleAddZone}
-          onEdit={handleEditZone}
-          onRemove={handleRemoveZone}
-          points={zonePoints}
-          yamlPrefix="zones:"
-          yamlKeyPrefix={zoneYamlKeyPrefix}
-        />
-
-        <MaskValues
-          isMulti
-          editing={editing}
-          title="Object masks"
-          onAdd={handleAddToObjectMask}
-          onCopy={handleCopyObjectMasks}
-          onCreate={handleAddObjectMask}
-          onEdit={handleEditObjectMask}
-          onRemove={handleRemoveObjectMask}
-          points={objectMaskPoints}
-          yamlPrefix={'objects:\n  filters:'}
-          yamlKeyPrefix={objectYamlKeyPrefix}
-        />
-      </div>
-    </div>
-  );
-}
-
-function maskYamlKeyPrefix(points) {
-  return `    - `;
-}
-
-function zoneYamlKeyPrefix(points, key) {
-  return `  ${key}:
-    coordinates: `;
-}
-
-function objectYamlKeyPrefix(points, key, subkey) {
-  return `        - `;
-}
-
-const MaskInset = 20;
-
-function EditableMask({ onChange, points, scale, snap, width, height }) {
-  if (!points) {
-    return null;
-  }
-  const boundingRef = useRef(null);
-
-  function boundedSize(value, maxValue) {
-    const newValue = Math.min(Math.max(0, Math.round(value)), maxValue);
-    if (snap) {
-      if (newValue <= MaskInset) {
-        return 0;
-      } else if (maxValue - newValue <= MaskInset) {
-        return maxValue;
-      }
-    }
-
-    return newValue;
-  }
-
-  const handleMovePoint = useCallback(
-    (index, newX, newY) => {
-      if (newX < 0 && newY < 0) {
-        return;
-      }
-      let x = boundedSize(newX / scale, width, snap);
-      let y = boundedSize(newY / scale, height, snap);
-
-      const newPoints = [...points];
-      newPoints[index] = [x, y];
-      onChange(newPoints);
-    },
-    [scale, points, snap]
-  );
-
-  // Add a new point between the closest two other points
-  const handleAddPoint = useCallback(
-    (event) => {
-      const { offsetX, offsetY } = event;
-      const scaledX = boundedSize((offsetX - MaskInset) / scale, width, snap);
-      const scaledY = boundedSize((offsetY - MaskInset) / scale, height, snap);
-      const newPoint = [scaledX, scaledY];
-
-      let closest;
-      const { index } = points.reduce(
-        (result, point, i) => {
-          const nextPoint = points.length === i + 1 ? points[0] : points[i + 1];
-          const distance0 = Math.sqrt(Math.pow(point[0] - newPoint[0], 2) + Math.pow(point[1] - newPoint[1], 2));
-          const distance1 = Math.sqrt(Math.pow(point[0] - nextPoint[0], 2) + Math.pow(point[1] - nextPoint[1], 2));
-          const distance = distance0 + distance1;
-          return distance < result.distance ? { distance, index: i } : result;
-        },
-        { distance: Infinity, index: -1 }
-      );
-      const newPoints = [...points];
-      newPoints.splice(index, 0, newPoint);
-      onChange(newPoints);
-    },
-    [scale, points, onChange, snap]
-  );
-
-  const handleRemovePoint = useCallback(
-    (index) => {
-      const newPoints = [...points];
-      newPoints.splice(index, 1);
-      onChange(newPoints);
-    },
-    [points, onChange]
-  );
-
-  const scaledPoints = useMemo(() => scalePolylinePoints(points, scale), [points, scale]);
-
-  return (
-    <div className="absolute" style={`inset: -${MaskInset}px`}>
-      {!scaledPoints
-        ? null
-        : scaledPoints.map(([x, y], i) => (
-            <PolyPoint
-              boundingRef={boundingRef}
-              index={i}
-              onMove={handleMovePoint}
-              onRemove={handleRemovePoint}
-              x={x + MaskInset}
-              y={y + MaskInset}
-            />
-          ))}
-      <div className="absolute inset-0 right-0 bottom-0" onclick={handleAddPoint} ref={boundingRef} />
-      <svg width="100%" height="100%" className="absolute pointer-events-none" style={`inset: ${MaskInset}px`}>
-        {!scaledPoints ? null : (
-          <g>
-            <polyline points={polylinePointsToPolyline(scaledPoints)} fill="rgba(244,0,0,0.5)" />
-          </g>
-        )}
-      </svg>
-    </div>
-  );
-}
-
-function MaskValues({
-  isMulti = false,
-  editing,
-  title,
-  onAdd,
-  onCopy,
-  onCreate,
-  onEdit,
-  onRemove,
-  points,
-  yamlPrefix,
-  yamlKeyPrefix,
-}) {
-  const [showButtons, setShowButtons] = useState(false);
-
-  const handleMousein = useCallback(() => {
-    setShowButtons(true);
-  }, [setShowButtons]);
-
-  const handleMouseout = useCallback(
-    (event) => {
-      const el = event.toElement || event.relatedTarget;
-      if (!el || el.parentNode === event.target) {
-        return;
-      }
-      setShowButtons(false);
-    },
-    [setShowButtons]
-  );
-
-  const handleEdit = useCallback(
-    (event) => {
-      const { key, subkey } = event.target.dataset;
-      onEdit(key, subkey);
-    },
-    [onEdit]
-  );
-
-  const handleRemove = useCallback(
-    (event) => {
-      const { key, subkey } = event.target.dataset;
-      onRemove(key, subkey);
-    },
-    [onRemove]
-  );
-
-  const handleAdd = useCallback(
-    (event) => {
-      const { key } = event.target.dataset;
-      onAdd(key);
-    },
-    [onAdd]
-  );
-
-  return (
-    <Box className="overflow-hidden" onmouseover={handleMousein} onmouseout={handleMouseout}>
-      <div class="flex space-x-4">
-        <Heading className="flex-grow self-center" size="base">
-          {title}
-        </Heading>
-        <Button onClick={onCopy}>Copy</Button>
-        <Button onClick={onCreate}>Add</Button>
-      </div>
-      <pre class="relative overflow-auto font-mono text-gray-900 dark:text-gray-100 rounded bg-gray-100 dark:bg-gray-800 p-2">
-        {yamlPrefix}
-        {Object.keys(points).map((mainkey) => {
-          if (isMulti) {
-            return (
-              <div>
-                {`    ${mainkey}:\n      mask:\n`}
-                {onAdd && showButtons ? (
-                  <Button className="absolute -mt-12 right-0 font-sans" data-key={mainkey} onClick={handleAdd}>
-                    {`Add to ${mainkey}`}
-                  </Button>
-                ) : null}
-                {points[mainkey].map((item, subkey) => (
-                  <Item
-                    mainkey={mainkey}
-                    subkey={subkey}
-                    editing={editing}
-                    handleEdit={handleEdit}
-                    handleRemove={handleRemove}
-                    points={item}
-                    showButtons={showButtons}
-                    yamlKeyPrefix={yamlKeyPrefix}
-                  />
-                ))}
-              </div>
-            );
-          } else {
-            return (
-              <Item
-                mainkey={mainkey}
-                editing={editing}
-                handleAdd={onAdd ? handleAdd : undefined}
-                handleEdit={handleEdit}
-                handleRemove={handleRemove}
-                points={points[mainkey]}
-                showButtons={showButtons}
-                yamlKeyPrefix={yamlKeyPrefix}
-              />
-            );
-          }
-        })}
-      </pre>
-    </Box>
-  );
-}
-
-function Item({ mainkey, subkey, editing, handleEdit, points, showButtons, handleAdd, handleRemove, yamlKeyPrefix }) {
-  return (
-    <span
-      data-key={mainkey}
-      data-subkey={subkey}
-      className={`block hover:text-blue-400 cursor-pointer relative ${
-        editing.key === mainkey && editing.subkey === subkey ? 'text-blue-800 dark:text-blue-600' : ''
-      }`}
-      onClick={handleEdit}
-      title="Click to edit"
-    >
-      {`${yamlKeyPrefix(points, mainkey, subkey)}${polylinePointsToPolyline(points)}`}
-      {showButtons ? (
-        <Button
-          className="absolute top-0 right-0"
-          color="red"
-          data-key={mainkey}
-          data-subkey={subkey}
-          onClick={handleRemove}
-        >
-          Remove
-        </Button>
-      ) : null}
-    </span>
-  );
-}
-
-function getPolylinePoints(polyline) {
-  if (!polyline) {
-    return;
-  }
-
-  return polyline.split(',').reduce((memo, point, i) => {
-    if (i % 2) {
-      memo[memo.length - 1].push(parseInt(point, 10));
-    } else {
-      memo.push([parseInt(point, 10)]);
-    }
-    return memo;
-  }, []);
-}
-
-function scalePolylinePoints(polylinePoints, scale) {
-  if (!polylinePoints) {
-    return;
-  }
-
-  return polylinePoints.map(([x, y]) => [Math.round(x * scale), Math.round(y * scale)]);
-}
-
-function polylinePointsToPolyline(polylinePoints) {
-  if (!polylinePoints) {
-    return;
-  }
-  return polylinePoints.reduce((memo, [x, y]) => `${memo}${x},${y},`, '').replace(/,$/, '');
-}
-
-const PolyPointRadius = 10;
-function PolyPoint({ boundingRef, index, x, y, onMove, onRemove }) {
-  const [hidden, setHidden] = useState(false);
-
-  const handleDragOver = useCallback(
-    (event) => {
-      if (
-        !boundingRef.current ||
-        (event.target !== boundingRef.current && !boundingRef.current.contains(event.target))
-      ) {
-        return;
-      }
-      onMove(index, event.layerX - PolyPointRadius * 2, event.layerY - PolyPointRadius * 2);
-    },
-    [onMove, index, boundingRef.current]
-  );
-
-  const handleDragStart = useCallback(() => {
-    boundingRef.current && boundingRef.current.addEventListener('dragover', handleDragOver, false);
-    setHidden(true);
-  }, [setHidden, boundingRef.current, handleDragOver]);
-
-  const handleDragEnd = useCallback(() => {
-    boundingRef.current && boundingRef.current.removeEventListener('dragover', handleDragOver);
-    setHidden(false);
-  }, [setHidden, boundingRef.current, handleDragOver]);
-
-  const handleRightClick = useCallback(
-    (event) => {
-      event.preventDefault();
-      onRemove(index);
-    },
-    [onRemove, index]
-  );
-
-  const handleClick = useCallback((event) => {
-    event.stopPropagation();
-    event.preventDefault();
-  }, []);
-
-  return (
-    <div
-      className={`${hidden ? 'opacity-0' : ''} bg-gray-900 rounded-full absolute z-20`}
-      style={`top: ${y - PolyPointRadius}px; left: ${x - PolyPointRadius}px; width: 20px; height: 20px;`}
-      draggable
-      onclick={handleClick}
-      oncontextmenu={handleRightClick}
-      ondragstart={handleDragStart}
-      ondragend={handleDragEnd}
-    />
-  );
-}

web/src/Cameras.jsx

@@ -1,38 +0,0 @@
-import { h } from 'preact';
-import ActivityIndicator from './components/ActivityIndicator';
-import Box from './components/Box';
-import CameraImage from './components/CameraImage';
-import Events from './Events';
-import Heading from './components/Heading';
-import { route } from 'preact-router';
-import { useConfig } from './api';
-
-export default function Cameras() {
-  const { data: config, status } = useConfig();
-
-  if (!config) {
-    return <p>loading…</p>;
-  }
-
-  return (
-    <div className="grid lg:grid-cols-2 md:grid-cols-1 gap-4">
-      {Object.keys(config.cameras).map((camera) => (
-        <Camera name={camera} />
-      ))}
-    </div>
-  );
-}
-
-function Camera({ name }) {
-  const href = `/cameras/${name}`;
-
-  return (
-    <Box
-      className="bg-white dark:bg-gray-700 shadow-lg rounded-lg p-4 hover:bg-gray-300 hover:dark:bg-gray-500 dark:hover:text-gray-900 dark:hover:text-gray-900"
-      href={href}
-    >
-      <Heading size="base">{name}</Heading>
-      <CameraImage camera={name} />
-    </Box>
-  );
-}

web/src/Debug.jsx

@@ -1,112 +0,0 @@
-import { h } from 'preact';
-import ActivityIndicator from './components/ActivityIndicator';
-import Box from './components/Box';
-import Button from './components/Button';
-import Heading from './components/Heading';
-import Link from './components/Link';
-import { FetchStatus, useConfig, useStats } from './api';
-import { Table, Tbody, Thead, Tr, Th, Td } from './components/Table';
-import { useCallback, useEffect, useState } from 'preact/hooks';
-
-export default function Debug() {
-  const config = useConfig();
-
-  const [timeoutId, setTimeoutId] = useState(null);
-
-  const forceUpdate = useCallback(async () => {
-    setTimeoutId(setTimeout(forceUpdate, 1000));
-  }, []);
-
-  useEffect(() => {
-    forceUpdate();
-  }, []);
-
-  useEffect(() => {
-    return () => {
-      clearTimeout(timeoutId);
-    };
-  }, [timeoutId]);
-  const { data: stats, status } = useStats(null, timeoutId);
-
-  if (stats === null && (status === FetchStatus.LOADING || status === FetchStatus.NONE)) {
-    return <ActivityIndicator />;
-  }
-
-  const { detectors, detection_fps, service, ...cameras } = stats;
-
-  const detectorNames = Object.keys(detectors);
-  const detectorDataKeys = Object.keys(detectors[detectorNames[0]]);
-
-  const cameraNames = Object.keys(cameras);
-  const cameraDataKeys = Object.keys(cameras[cameraNames[0]]);
-
-  const handleCopyConfig = useCallback(async () => {
-    await window.navigator.clipboard.writeText(JSON.stringify(config, null, 2));
-  }, [config]);
-
-  return (
-    <div class="space-y-4">
-      <Heading>
-        Debug <span className="text-sm">{service.version}</span>
-      </Heading>
-
-      <Box>
-        <Table className="w-full">
-          <Thead>
-            <Tr>
-              <Th>detector</Th>
-              {detectorDataKeys.map((name) => (
-                <Th>{name.replace('_', ' ')}</Th>
-              ))}
-            </Tr>
-          </Thead>
-          <Tbody>
-            {detectorNames.map((detector, i) => (
-              <Tr index={i}>
-                <Td>{detector}</Td>
-                {detectorDataKeys.map((name) => (
-                  <Td key={`${name}-${detector}`}>{detectors[detector][name]}</Td>
-                ))}
-              </Tr>
-            ))}
-          </Tbody>
-        </Table>
-      </Box>
-
-      <Box>
-        <Table className="w-full">
-          <Thead>
-            <Tr>
-              <Th>camera</Th>
-              {cameraDataKeys.map((name) => (
-                <Th>{name.replace('_', ' ')}</Th>
-              ))}
-            </Tr>
-          </Thead>
-          <Tbody>
-            {cameraNames.map((camera, i) => (
-              <Tr index={i}>
-                <Td>
-                  <Link href={`/cameras/${camera}`}>{camera}</Link>
-                </Td>
-                {cameraDataKeys.map((name) => (
-                  <Td key={`${name}-${camera}`}>{cameras[camera][name]}</Td>
-                ))}
-              </Tr>
-            ))}
-          </Tbody>
-        </Table>
-      </Box>
-
-      <Box className="relative">
-        <Heading size="sm">Config</Heading>
-        <Button className="absolute top-4 right-8" onClick={handleCopyConfig}>
-          Copy to Clipboard
-        </Button>
-        <pre className="overflow-auto font-mono text-gray-900 dark:text-gray-100 rounded bg-gray-100 dark:bg-gray-800 p-2 max-h-96">
-          {JSON.stringify(config, null, 2)}
-        </pre>
-      </Box>
-    </div>
-  );
-}

web/src/Event.jsx

@@ -1,81 +0,0 @@
-import { h, Fragment } from 'preact';
-import ActivityIndicator from './components/ActivityIndicator';
-import Box from './components/Box';
-import Heading from './components/Heading';
-import Link from './components/Link';
-import { FetchStatus, useApiHost, useEvent } from './api';
-import { Table, Thead, Tbody, Tfoot, Th, Tr, Td } from './components/Table';
-
-export default function Event({ eventId }) {
-  const apiHost = useApiHost();
-  const { data, status } = useEvent(eventId);
-
-  if (status !== FetchStatus.LOADED) {
-    return <ActivityIndicator />;
-  }
-
-  const startime = new Date(data.start_time * 1000);
-  const endtime = new Date(data.end_time * 1000);
-
-  return (
-    <div className="space-y-4">
-      <Heading>
-        {data.camera} {data.label} <span className="text-sm">{startime.toLocaleString()}</span>
-      </Heading>
-
-      <Box>
-        {data.has_clip ? (
-          <Fragment>
-            <Heading size="sm">Clip</Heading>
-            <video className="w-100" src={`${apiHost}/clips/${data.camera}-${eventId}.mp4`} controls />
-          </Fragment>
-        ) : (
-          <p>No clip available</p>
-        )}
-      </Box>
-
-      <Box>
-        <Heading size="sm">{data.has_snapshot ? 'Best image' : 'Thumbnail'}</Heading>
-        <img
-          src={
-            data.has_snapshot
-              ? `${apiHost}/clips/${data.camera}-${eventId}.jpg`
-              : `data:image/jpeg;base64,${data.thumbnail}`
-          }
-          alt={`${data.label} at ${(data.top_score * 100).toFixed(1)}% confidence`}
-        />
-      </Box>
-
-      <Box>
-        <Table>
-          <Thead>
-            <Th>Key</Th>
-            <Th>Value</Th>
-          </Thead>
-          <Tbody>
-            <Tr>
-              <Td>Camera</Td>
-              <Td>
-                <Link href={`/cameras/${data.camera}`}>{data.camera}</Link>
-              </Td>
-            </Tr>
-            <Tr index={1}>
-              <Td>Timeframe</Td>
-              <Td>
-                {startime.toLocaleString()} – {endtime.toLocaleString()}
-              </Td>
-            </Tr>
-            <Tr>
-              <Td>Score</Td>
-              <Td>{(data.top_score * 100).toFixed(2)}%</Td>
-            </Tr>
-            <Tr index={1}>
-              <Td>Zones</Td>
-              <Td>{data.zones.join(', ')}</Td>
-            </Tr>
-          </Tbody>
-        </Table>
-      </Box>
-    </div>
-  );
-}

web/src/Events.jsx

@@ -1,300 +0,0 @@
-import { h } from 'preact';
-import ActivityIndicator from './components/ActivityIndicator';
-import Box from './components/Box';
-import Heading from './components/Heading';
-import Link from './components/Link';
-import produce from 'immer';
-import { route } from 'preact-router';
-import { FetchStatus, useApiHost, useConfig, useEvents } from './api';
-import { Table, Thead, Tbody, Tfoot, Th, Tr, Td } from './components/Table';
-import { useCallback, useContext, useEffect, useMemo, useRef, useReducer, useState } from 'preact/hooks';
-
-const API_LIMIT = 25;
-
-const initialState = Object.freeze({ events: [], reachedEnd: false, searchStrings: {} });
-const reducer = (state = initialState, action) => {
-  switch (action.type) {
-    case 'APPEND_EVENTS': {
-      const {
-        meta: { searchString },
-        payload,
-      } = action;
-      return produce(state, (draftState) => {
-        draftState.searchStrings[searchString] = true;
-        draftState.events.push(...payload);
-      });
-    }
-
-    case 'REACHED_END': {
-      const {
-        meta: { searchString },
-      } = action;
-      return produce(state, (draftState) => {
-        draftState.reachedEnd = true;
-        draftState.searchStrings[searchString] = true;
-      });
-    }
-
-    case 'RESET':
-      return initialState;
-
-    default:
-      return state;
-  }
-};
-
-const defaultSearchString = `include_thumbnails=0&limit=${API_LIMIT}`;
-function removeDefaultSearchKeys(searchParams) {
-  searchParams.delete('limit');
-  searchParams.delete('include_thumbnails');
-  searchParams.delete('before');
-}
-
-export default function Events({ path: pathname } = {}) {
-  const apiHost = useApiHost();
-  const [{ events, reachedEnd, searchStrings }, dispatch] = useReducer(reducer, initialState);
-  const { searchParams: initialSearchParams } = new URL(window.location);
-  const [searchString, setSearchString] = useState(`${defaultSearchString}&${initialSearchParams.toString()}`);
-  const { data, status } = useEvents(searchString);
-
-  useEffect(() => {
-    if (data && !(searchString in searchStrings)) {
-      dispatch({ type: 'APPEND_EVENTS', payload: data, meta: { searchString } });
-    }
-    if (Array.isArray(data) && data.length < API_LIMIT) {
-      dispatch({ type: 'REACHED_END', meta: { searchString } });
-    }
-  }, [data]);
-
-  const observer = useRef(
-    new IntersectionObserver((entries, observer) => {
-      window.requestAnimationFrame(() => {
-        if (entries.length === 0) {
-          return;
-        }
-        // under certain edge cases, a ref may be applied / in memory twice
-        // avoid fetching twice by grabbing the last observed entry only
-        const entry = entries[entries.length - 1];
-        if (entry.isIntersecting) {
-          const { startTime } = entry.target.dataset;
-          const { searchParams } = new URL(window.location);
-          searchParams.set('before', parseFloat(startTime) - 0.0001);
-
-          setSearchString(`${defaultSearchString}&${searchParams.toString()}`);
-        }
-      });
-    })
-  );
-
-  const lastCellRef = useCallback(
-    (node) => {
-      if (node !== null) {
-        observer.current.disconnect();
-        if (!reachedEnd) {
-          observer.current.observe(node);
-        }
-      }
-    },
-    [observer.current, reachedEnd]
-  );
-
-  const handleFilter = useCallback(
-    (searchParams) => {
-      dispatch({ type: 'RESET' });
-      removeDefaultSearchKeys(searchParams);
-      setSearchString(`${defaultSearchString}&${searchParams.toString()}`);
-      route(`${pathname}?${searchParams.toString()}`);
-    },
-    [pathname, setSearchString]
-  );
-
-  const searchParams = useMemo(() => new URLSearchParams(searchString), [searchString]);
-
-  return (
-    <div className="space-y-4 w-full">
-      <Heading>Events</Heading>
-
-      <Filters onChange={handleFilter} searchParams={searchParams} />
-
-      <Box className="min-w-0 overflow-auto">
-        <Table className="min-w-full table-fixed">
-          <Thead>
-            <Tr>
-              <Th></Th>
-              <Th>Camera</Th>
-              <Th>Label</Th>
-              <Th>Score</Th>
-              <Th>Zones</Th>
-              <Th>Date</Th>
-              <Th>Start</Th>
-              <Th>End</Th>
-            </Tr>
-          </Thead>
-          <Tbody>
-            {events.map(
-              (
-                { camera, id, label, start_time: startTime, end_time: endTime, thumbnail, top_score: score, zones },
-                i
-              ) => {
-                const start = new Date(parseInt(startTime * 1000, 10));
-                const end = new Date(parseInt(endTime * 1000, 10));
-                const ref = i === events.length - 1 ? lastCellRef : undefined;
-                return (
-                  <Tr key={id} index={i}>
-                    <Td className="w-40">
-                      <a href={`/events/${id}`} ref={ref} data-start-time={startTime} data-reached-end={reachedEnd}>
-                        <img
-                          width="150"
-                          height="150"
-                          style="min-height: 48px; min-width: 48px;"
-                          src={`${apiHost}/api/events/${id}/thumbnail.jpg`}
-                        />
-                      </a>
-                    </Td>
-                    <Td>
-                      <Filterable
-                        onFilter={handleFilter}
-                        pathname={pathname}
-                        searchParams={searchParams}
-                        paramName="camera"
-                        name={camera}
-                      />
-                    </Td>
-                    <Td>
-                      <Filterable
-                        onFilter={handleFilter}
-                        pathname={pathname}
-                        searchParams={searchParams}
-                        paramName="label"
-                        name={label}
-                      />
-                    </Td>
-                    <Td>{(score * 100).toFixed(2)}%</Td>
-                    <Td>
-                      <ul>
-                        {zones.map((zone) => (
-                          <li>
-                            <Filterable
-                              onFilter={handleFilter}
-                              pathname={pathname}
-                              searchParams={searchString}
-                              paramName="zone"
-                              name={zone}
-                            />
-                          </li>
-                        ))}
-                      </ul>
-                    </Td>
-                    <Td>{start.toLocaleDateString()}</Td>
-                    <Td>{start.toLocaleTimeString()}</Td>
-                    <Td>{end.toLocaleTimeString()}</Td>
-                  </Tr>
-                );
-              }
-            )}
-          </Tbody>
-          <Tfoot>
-            <Tr>
-              <Td className="text-center p-4" colspan="8">
-                {status === FetchStatus.LOADING ? <ActivityIndicator /> : reachedEnd ? 'No more events' : null}
-              </Td>
-            </Tr>
-          </Tfoot>
-        </Table>
-      </Box>
-    </div>
-  );
-}
-
-function Filterable({ onFilter, pathname, searchParams, paramName, name }) {
-  const href = useMemo(() => {
-    const params = new URLSearchParams(searchParams.toString());
-    params.set(paramName, name);
-    removeDefaultSearchKeys(params);
-    return `${pathname}?${params.toString()}`;
-  }, [searchParams]);
-
-  const handleClick = useCallback(
-    (event) => {
-      event.preventDefault();
-      route(href, true);
-      const params = new URLSearchParams(searchParams.toString());
-      params.set(paramName, name);
-      onFilter(params);
-    },
-    [href, searchParams]
-  );
-
-  return (
-    <Link href={href} onclick={handleClick}>
-      {name}
-    </Link>
-  );
-}
-
-function Filters({ onChange, searchParams }) {
-  const { data } = useConfig();
-
-  const cameras = useMemo(() => Object.keys(data.cameras), [data]);
-
-  const zones = useMemo(
-    () =>
-      Object.values(data.cameras)
-        .reduce((memo, camera) => {
-          memo = memo.concat(Object.keys(camera.zones));
-          return memo;
-        }, [])
-        .filter((value, i, self) => self.indexOf(value) === i),
-    [data]
-  );
-
-  const labels = useMemo(() => {
-    return Object.values(data.cameras)
-      .reduce((memo, camera) => {
-        memo = memo.concat(camera.objects?.track || []);
-        return memo;
-      }, data.objects?.track || [])
-      .filter((value, i, self) => self.indexOf(value) === i);
-  }, [data]);
-
-  return (
-    <Box className="flex space-y-0 space-x-8 flex-wrap">
-      <Filter onChange={onChange} options={cameras} paramName="camera" searchParams={searchParams} />
-      <Filter onChange={onChange} options={zones} paramName="zone" searchParams={searchParams} />
-      <Filter onChange={onChange} options={labels} paramName="label" searchParams={searchParams} />
-    </Box>
-  );
-}
-
-function Filter({ onChange, searchParams, paramName, options }) {
-  const handleSelect = useCallback(
-    (event) => {
-      const newParams = new URLSearchParams(searchParams.toString());
-      const value = event.target.value;
-      if (value) {
-        newParams.set(paramName, event.target.value);
-      } else {
-        newParams.delete(paramName);
-      }
-
-      onChange(newParams);
-    },
-    [searchParams, paramName, onChange]
-  );
-
-  return (
-    <label>
-      <span className="block uppercase text-sm">{paramName}</span>
-      <select className="border-solid border border-gray-500 rounded dark:text-gray-900" onChange={handleSelect}>
-        <option>All</option>
-        {options.map((opt) => {
-          return (
-            <option value={opt} selected={searchParams.get(paramName) === opt}>
-              {opt}
-            </option>
-          );
-        })}
-      </select>
-    </label>
-  );
-}

web/src/Sidebar.jsx

@@ -1,87 +0,0 @@
-import { h } from 'preact';
-import Link from './components/Link';
-import { Link as RouterLink } from 'preact-router/match';
-import { useCallback, useState } from 'preact/hooks';
-
-function HamburgerIcon() {
-  return (
-    <svg fill="currentColor" viewBox="0 0 20 20" className="w-6 h-6">
-      <path
-        fill-rule="evenodd"
-        d="M3 5a1 1 0 011-1h12a1 1 0 110 2H4a1 1 0 01-1-1zM3 10a1 1 0 011-1h12a1 1 0 110 2H4a1 1 0 01-1-1zM9 15a1 1 0 011-1h6a1 1 0 110 2h-6a1 1 0 01-1-1z"
-        clip-rule="evenodd"
-      ></path>
-    </svg>
-  );
-}
-
-function CloseIcon() {
-  return (
-    <svg fill="currentColor" viewBox="0 0 20 20" className="w-6 h-6">
-      <path
-        fill-rule="evenodd"
-        d="M4.293 4.293a1 1 0 011.414 0L10 8.586l4.293-4.293a1 1 0 111.414 1.414L11.414 10l4.293 4.293a1 1 0 01-1.414 1.414L10 11.414l-4.293 4.293a1 1 0 01-1.414-1.414L8.586 10 4.293 5.707a1 1 0 010-1.414z"
-        clip-rule="evenodd"
-      ></path>
-    </svg>
-  );
-}
-
-function NavLink({ className = '', href, text }) {
-  const external = href.startsWith('http');
-  const El = external ? Link : RouterLink;
-  const props = external ? { rel: 'noopener nofollow', target: '_blank' } : {};
-  return (
-    <El
-      activeClassName="bg-gray-200 dark:bg-gray-700 dark:hover:bg-gray-600 dark:focus:bg-gray-600 dark:focus:text-white dark:hover:text-white dark:text-gray-200"
-      className={`block px-4 py-2 mt-2 text-sm font-semibold text-gray-900 bg-transparent rounded-lg dark:bg-transparent dark:hover:bg-gray-600 dark:focus:bg-gray-600 dark:focus:text-white dark:hover:text-white dark:text-gray-200 hover:text-gray-900 focus:text-gray-900 hover:bg-gray-200 focus:bg-gray-200 focus:outline-none focus:shadow-outline self-end ${className}`}
-      href={href}
-      {...props}
-    >
-      {text}
-    </El>
-  );
-}
-
-export default function Sidebar() {
-  const [open, setOpen] = useState(false);
-
-  const handleToggle = useCallback(() => {
-    setOpen(!open);
-  }, [open, setOpen]);
-
-  return (
-    <div className="flex flex-col w-full md:w-64 text-gray-700 bg-white dark:text-gray-200 dark:bg-gray-700 flex-shrink-0">
-      <div className="flex-shrink-0 px-8 py-4 flex flex-row items-center justify-between">
-        <a
-          href="#"
-          className="text-lg font-semibold tracking-widest text-gray-900 uppercase rounded-lg dark:text-white focus:outline-none focus:shadow-outline"
-        >
-          Frigate
-        </a>
-        <button
-          className="rounded-lg md:hidden rounded-lg focus:outline-none focus:shadow-outline"
-          onClick={handleToggle}
-        >
-          {open ? <CloseIcon /> : <HamburgerIcon />}
-        </button>
-      </div>
-      <nav
-        className={`flex-col flex-grow md:block overflow-hidden px-4 pb-4 md:pb-0 md:overflow-y-auto ${
-          !open ? 'md:h-0 hidden' : ''
-        }`}
-      >
-        <NavLink href="/" text="Cameras" />
-        <NavLink href="/events" text="Events" />
-        <NavLink href="/debug" text="Debug" />
-        <hr className="border-solid border-gray-500 mt-2" />
-        <NavLink
-          className="self-end"
-          href="https://blakeblackshear.github.io/frigate"
-          text="Documentation"
-        />
-        <NavLink className="self-end" href="https://github.com/blakeblackshear/frigate" text="GitHub" />
-      </nav>
-    </div>
-  );
-}

web/src/api/index.jsx

@@ -1,108 +0,0 @@
-import { h, createContext } from 'preact';
-import produce from 'immer';
-import { useCallback, useContext, useEffect, useMemo, useRef, useReducer, useState } from 'preact/hooks';
-
-export const ApiHost = createContext(import.meta.env.SNOWPACK_PUBLIC_API_HOST || window.baseUrl || '');
-
-export const FetchStatus = {
-  NONE: 'none',
-  LOADING: 'loading',
-  LOADED: 'loaded',
-  ERROR: 'error',
-};
-
-const initialState = Object.freeze({
-  host: import.meta.env.SNOWPACK_PUBLIC_API_HOST || window.baseUrl || '',
-  queries: {},
-});
-export const Api = createContext(initialState);
-export default Api;
-
-function reducer(state, { type, payload, meta }) {
-  switch (type) {
-    case 'REQUEST': {
-      const { url, request } = payload;
-      const data = state.queries[url]?.data || null;
-      return produce(state, (draftState) => {
-        draftState.queries[url] = { status: FetchStatus.LOADING, data };
-      });
-    }
-
-    case 'RESPONSE': {
-      const { url, ok, data } = payload;
-      return produce(state, (draftState) => {
-        draftState.queries[url] = { status: ok ? FetchStatus.LOADED : FetchStatus.ERROR, data };
-      });
-    }
-
-    default:
-      return state;
-  }
-}
-
-export const ApiProvider = ({ children }) => {
-  const [state, dispatch] = useReducer(reducer, initialState);
-  return <Api.Provider value={{ state, dispatch }}>{children}</Api.Provider>;
-};
-
-function shouldFetch(state, url, forceRefetch = false) {
-  if (forceRefetch || !(url in state.queries)) {
-    return true;
-  }
-  const { status } = state.queries[url];
-
-  return status !== FetchStatus.LOADING && status !== FetchStatus.LOADED;
-}
-
-export function useFetch(url, forceRefetch) {
-  const { state, dispatch } = useContext(Api);
-
-  useEffect(() => {
-    if (!shouldFetch(state, url, forceRefetch)) {
-      return;
-    }
-
-    async function fetchConfig() {
-      await dispatch({ type: 'REQUEST', payload: { url } });
-      const response = await fetch(`${state.host}${url}`);
-      const data = await response.json();
-      await dispatch({ type: 'RESPONSE', payload: { url, ok: response.ok, data } });
-    }
-
-    fetchConfig();
-  }, [url, forceRefetch]);
-
-  if (!(url in state.queries)) {
-    return { data: null, status: FetchStatus.NONE };
-  }
-
-  const data = state.queries[url].data || null;
-  const status = state.queries[url].status;
-
-  return { data, status };
-}
-
-export function useApiHost() {
-  const { state, dispatch } = useContext(Api);
-  return state.host;
-}
-
-export function useEvents(searchParams, forceRefetch) {
-  const url = `/api/events${searchParams ? `?${searchParams.toString()}` : ''}`;
-  return useFetch(url, forceRefetch);
-}
-
-export function useEvent(eventId, forceRefetch) {
-  const url = `/api/events/${eventId}`;
-  return useFetch(url, forceRefetch);
-}
-
-export function useConfig(searchParams, forceRefetch) {
-  const url = `/api/config${searchParams ? `?${searchParams.toString()}` : ''}`;
-  return useFetch(url, forceRefetch);
-}
-
-export function useStats(searchParams, forceRefetch) {
-  const url = `/api/stats${searchParams ? `?${searchParams.toString()}` : ''}`;
-  return useFetch(url, forceRefetch);
-}

web/src/components/ActivityIndicator.jsx

@@ -1,15 +0,0 @@
-import { h } from 'preact';
-
-const sizes = {
-  sm: 'h-4 w-4 border-2 border-t-2',
-  md: 'h-8 w-8 border-4 border-t-4',
-  lg: 'h-16 w-16 border-8 border-t-8',
-};
-
-export default function ActivityIndicator({ size = 'md' }) {
-  return (
-    <div className="w-full flex items-center justify-center" aria-label="Loading…">
-      <div className={`activityindicator ease-in rounded-full border-gray-200 text-blue-500 ${sizes[size]}`} />
-    </div>
-  );
-}