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Add note about TensorFlow only available on Core (#17907)

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Franck Nijhof 2021-05-20 17:38:04 +02:00 committed by GitHub
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@ -8,11 +8,16 @@ ha_release: 0.82
ha_domain: tensorflow
---
The `tensorflow` image processing platform allows you to detect and recognize objects in a camera image using [TensorFlow](https://www.tensorflow.org/). 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.
The TensorFlow image processing platform allows you to detect and recognize objects in a camera image using [TensorFlow](https://www.tensorflow.org/). 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.
{% details "Notes for Home Assistant Core Installations" %}
<div class='note'>
This integration is only available on Home Assistant Core installation types. Unfortunately, it cannot be used with Home Assistant OS, Supervised or Container.
</div>
## Prerequisites
The following packages must be installed on Debian before following the setup for the integration to work:
`sudo apt-get install libatlas-base-dev libopenjp2-7 libtiff5`
It is possible that Home Assistant is unable to install the Python TensorFlow bindings. If that is the case,
@ -24,8 +29,6 @@ See [the official install guide](https://www.tensorflow.org/install/) for other
Furthermore, the official Python TensorFlow wheels by Google, require your CPU to support the `avx` extension.
If your CPU lacks those capabilities, Home Assistant will crash when using TensorFlow, without any message.
{% enddetails %}
## Preparation
This integration requires files to be downloaded, compiled on your computer, and added to the Home Assistant configuration directory. These steps can be performed by cloning [this repository](https://github.com/hunterjm/hass-tensorflow) into your configuration directory. Alternatively, if you wish to perform the process manually, the process is as follows: