home-assistant.io/source/_integrations/doods.markdown

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---
title: DOODS - Dedicated Open Object Detection Service
description: Detect and recognize objects with DOODS.
ha_category:
- Image Processing
ha_iot_class: Local Polling
ha_release: '0.100'
ha_domain: doods
---
The `doods` image processing integration allows you to detect and recognize objects in a camera image using [DOODS](https://github.com/snowzach/doods/). The state of the entity is the number of objects detected and recognized objects are listed in the `summary` attribute along with quantity. The `matches` attribute provides the confidence `score` for recognition and the bounding `box` of the object for each detection category.
## Setup
The DOODS software needs to be running before this integration can be used. Options to run the DOODS software:
- Run as [Home Assistant add-on](https://github.com/snowzach/hassio-addons)
- Run as a [Docker container](https://hub.docker.com/r/snowzach/doods)
## Configuration
To enable this integration in your installation, add the following to your `configuration.yaml` file:
```yaml
# Example configuration.yaml entry
image_processing:
- platform: doods
url: "http://<my doods server>:8080"
detector: default
source:
- entity_id: camera.front_yard
```
{% configuration %}
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
url:
description: The URL of the DOODS server.
required: true
type: string
auth_key:
description: The authentication key as set in the DOODS configuration file or as a Docker environment variable (DOODS_AUTH_KEY)
required: false
type: string
timeout:
description: Timeout for requests (in seconds).
required: false
type: integer
default: 90
detector:
description: The DOODS detector to use.
required: true
type: string
confidence:
description: The default confidence for any detected objects where not explicitly set.
required: false
type: float
area:
description: Global detection area. Objects in this box will be reported. Top of image is 0, bottom is 1. Same left to right.
required: false
type: map
keys:
top:
description: Top line defined as % from top of image.
required: false
type: float
default: 0
left:
description: Left line defined as % from left of image.
required: false
type: float
default: 0
bottom:
description: Bottom line defined as % from top of image.
required: false
type: float
default: 1
right:
description: Right line defined as % from left of image.
required: false
type: float
default: 1
covers:
description: If true the detection must be fully in this box. If false any part of the detection in the box will trigger.
required: false
type: boolean
default: true
file_out:
description: A [template](/docs/configuration/templating/#processing-incoming-data) for the integration to save processed images including bounding boxes. `camera_entity` is available as the `entity_id` string of the triggered source camera.
required: false
type: list
labels:
description: Information about the selected labels model.
required: false
type: map
keys:
name:
description: The label of the object to select for detection.
required: true
type: string
confidence:
description: The minimum confidence for the selected label.
required: false
type: float
area:
description: Custom detection area. Only objects fully in this box will be reported. Top of image is 0, bottom is 1. Same left to right.
required: false
type: map
keys:
top:
description: Top line defined as % from top of image.
required: false
type: float
default: 0
left:
description: Left line defined as % from left of image.
required: false
type: float
default: 0
bottom:
description: Bottom line defined as % from top of image.
required: false
type: float
default: 1
right:
description: Right line defined as % from left of image.
required: false
type: float
default: 1
covers:
description: If true the detection must be fully in this box. If false any part of the detection in the box will trigger.
required: false
type: boolean
default: true
{% endconfiguration %}
## Supported labels
Both detectors "default" and "tensorflow" use the labels in [this file](https://raw.githubusercontent.com/amikelive/coco-labels/master/coco-labels-2014_2017.txt).
## Sample configuration
{% raw %}
```yaml
# Example advanced configuration.yaml entry
image_processing:
- platform: doods
scan_interval: 1000
url: "http://<my doods server>:8080"
timeout: 60
detector: default
auth_key: 2up3rL0ng4uthK3y
source:
- entity_id: camera.front_yard
file_out:
- "/tmp/{{ camera_entity.split('.')[1] }}_latest.jpg"
- "/tmp/{{ camera_entity.split('.')[1] }}_{{ now().strftime('%Y%m%d_%H%M%S') }}.jpg"
confidence: 50
# This global detection area is required for all labels
area:
# Exclude top 10% of image
top: 0.1
# Exclude right 5% of image
right: 0.95
# The entire detection must be inside this box
covers: true
labels:
- name: person
confidence: 40
area:
# Exclude top 10% of image
top: 0.1
# Exclude right 15% of image
right: 0.85
# Any part of the detection inside this area will trigger
covers: false
- car
- truck
```
{% endraw %}
## Optimizing resources
The [Image processing integration](/components/image_processing/) 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 configuration `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.
```yaml
# Example advanced configuration.yaml entry
image_processing:
- platform: doods
scan_interval: 10000
source:
- entity_id: camera.driveway
- entity_id: camera.backyard
```
```yaml
# Example advanced automations.yaml entry
- alias: "Doods scanning"
trigger:
- platform: state
entity_id:
- binary_sensor.driveway
action:
- service: image_processing.scan
target:
entity_id: image_processing.doods_camera_driveway
```