
* Update image_processing.facebox.markdown
* Remove ref to particular image file types
* ✏️ Minor tweaks
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layout | title | description | date | sidebar | comments | sharing | footer | logo | ha_category | featured | ha_release |
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page | Facebox | Detect and recognize faces with Facebox. | 2018-05-03 00:00 | true | false | true | true | machine-box.png | Image Processing | false | 0.70 |
The facebox
image processing platform allows you to detect and recognize faces in a camera image using Facebox. The state of the entity is the number of faces detected, and recognized faces are listed in the matched_faces
attribute. An image_processing.detect_face
event is fired for each recognized face, and the event data
provides the confidence
of recognition, the name
of the person, the image_id
of the image associated with the match, the bounding_box
that contains the face in the image, and the entity_id
that processing was performed on.
{% linkable_title Setup %}
Facebox runs in a Docker container and it is recommended that you run this container on a machine with a minimum of 2 GB RAM. On your machine with Docker, run the Facebox container with:
MB_KEY="INSERT-YOUR-KEY-HERE"
sudo docker run --name=facebox --restart=always -p 8080:8080 -e "MB_KEY=$MB_KEY" machinebox/facebox
If you only require face detection (number of faces) you can disable face recognition by adding -e "MB_FACEBOX_DISABLE_RECOGNITION=true"
to the docker run
command.
{% linkable_title Configuration %}
To enable this platform in your installation, add the following to your configuration.yaml
file:
# Example configuration.yaml entry
image_processing:
- platform: facebox
ip_address: 192.168.0.1
port: 8080
source:
- entity_id: camera.local_file
name: my_custom_name
{% configuration %}
ip_address:
description: The IP address of your machine hosting Facebox.
required: true
type: string
port:
description: The port which Facebox is exposed on.
required: true
type: string
source:
description: The list of image sources.
required: true
type: map
keys:
entity_id:
description: A camera entity id to get picture from.
required: true
type: string
name:
description: This parameter allows you to override the name of your image_processing
entity.
required: false
type: string
{% endconfiguration %}
{% linkable_title Automations %}
Use the image_processing.detect_face
events to trigger automations, and breakout the trigger.event.data
using a data_template. The following example automation sends a notification when Ringo Star is recognized:
{% raw %}
- id: '12345'
alias: Ringo Starr recognised
trigger:
platform: event
event_type: image_processing.detect_face
event_data:
name: 'Ringo_Starr'
action:
service: notify.platform
data_template:
message: Ringo_Starr recognised with probability {{ trigger.event.data.confidence }}
title: Door-cam notification
{% endraw %}
{% linkable_title Service facebox_teach_face
%}
The service facebox_teach_face
can be used to teach Facebox faces.
Service data attribute | Optional | Description |
---|---|---|
entity_id |
no | Entity ID of Facebox entity. |
name |
no | The name to associate with a face. |
file_path |
no | The path to the image file. |
A valid service data example:
{% raw %}
{
"entity_id": "image_processing.facebox_local_file",
"name": "superman",
"file_path": "/images/superman_1.jpeg"
}
{% endraw %}
An image_processing.teach_classifier
event is fired for each service call, providing feedback on whether teaching has been successful or unsuccessful. In the unsuccessful case, the message
field of the event_data
will contain information on the cause of failure, and a warning is also published in the logs. An automation can be used to receive alerts on teaching, for example, the following automation will send a notification with the teaching image and a message describing the status of the teaching:
- id: '11200961111'
alias: Send facebox teaching result
trigger:
platform: event
event_type: image_processing.teach_classifier
event_data:
classifier: facebox
action:
service: notify.platform
data_template:
title: Facebox teaching
message: Name {{ trigger.event.data.name }} teaching was successful? {{ trigger.event.data.success }}
data:
file: ' {{trigger.event.data.file_path}} '
{% linkable_title Optimising resources %}
Image processing components process the image from a camera at a fixed period given by the scan_interval
. This leads to excessive processing if the image on the camera hasn't changed, as the default scan_interval
is 10 seconds. You can override this by adding to your config scan_interval: 10000
(setting the interval to 10,000 seconds), and then call the image_processing.scan
service when you actually want to perform processing.