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name: On push | ||
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on: | ||
push: | ||
branches: | ||
- master | ||
- release-0.8.0 | ||
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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 |
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# Dependencies | ||
/node_modules | ||
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# Production | ||
/build | ||
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# Generated files | ||
.docusaurus | ||
.cache-loader | ||
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# Misc | ||
.DS_Store | ||
.env.local | ||
.env.development.local | ||
.env.test.local | ||
.env.production.local | ||
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npm-debug.log* | ||
yarn-debug.log* | ||
yarn-error.log* |
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# Website | ||
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This website is built using [Docusaurus 2](https://v2.docusaurus.io/), a modern static website generator. | ||
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## Installation | ||
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```console | ||
yarn install | ||
``` | ||
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## Local Development | ||
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```console | ||
yarn start | ||
``` | ||
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This command starts a local development server and open up a browser window. Most changes are reflected live without having to restart the server. | ||
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## Build | ||
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```console | ||
yarn build | ||
``` | ||
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This command generates static content into the `build` directory and can be served using any static contents hosting service. | ||
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## Deployment | ||
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```console | ||
GIT_USER=<Your GitHub username> USE_SSH=true yarn deploy | ||
``` | ||
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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. |
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module.exports = { | ||
presets: [require.resolve('@docusaurus/core/lib/babel/preset')], | ||
}; |
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--- | ||
id: advanced | ||
title: Advanced | ||
sidebar_label: Advanced | ||
--- | ||
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## Advanced configuration | ||
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### `motion` | ||
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Global motion detection config. These may also be defined at the camera level. | ||
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```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` | ||
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Global object detection settings. These may also be defined at the camera level. | ||
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```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 | ||
``` | ||
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### `logger` | ||
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Change the default log level for troubleshooting purposes. | ||
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```yaml | ||
logger: | ||
# Optional: default log level (default: shown below) | ||
default: info | ||
# Optional: module by module log level configuration | ||
logs: | ||
frigate.mqtt: error | ||
``` | ||
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Available log levels are: `debug`, `info`, `warning`, `error`, `critical` | ||
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Examples of available modules are: | ||
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- `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. | ||
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### `environment_vars` | ||
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This section can be used to set environment variables for those unable to modify the environment of the container (ie. within Hass.io) | ||
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```yaml | ||
environment_vars: | ||
EXAMPLE_VAR: value | ||
``` | ||
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### `database` | ||
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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. | ||
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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. | ||
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This may need to be in a custom location if network storage is used for clips. | ||
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```yaml | ||
database: | ||
path: /media/frigate/clips/frigate.db | ||
``` | ||
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### `detectors` | ||
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```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 | ||
``` | ||
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### `model` | ||
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```yaml | ||
model: | ||
# Required: height of the trained model | ||
height: 320 | ||
# Required: width of the trained model | ||
width: 320 | ||
``` | ||
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## Custom Models | ||
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Models for both CPU and EdgeTPU (Coral) are bundled in the image. You can use your own models with volume mounts: | ||
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- CPU Model: `/cpu_model.tflite` | ||
- EdgeTPU Model: `/edgetpu_model.tflite` | ||
- Labels: `/labelmap.txt` | ||
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You also need to update the model width/height in the config if they differ from the defaults. | ||
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### Customizing the Labelmap | ||
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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: | ||
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- 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 | ||
``` |
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