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Customize.md - fixes on broken and wrong links #310

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12 changes: 6 additions & 6 deletions docs/reference/customize.md
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OpenDR is fully open-source and can be readily customized to meet the needs of several different application areas, since the source code for all the developed tools is provided.
Several ready-to-use examples, which are expected to cover a wide range of different needs, are provided.
For example, users can readily use the existing [ROS nodes](projects/opendr_ws), e.g., by including the required triggers or by combining several nodes into one to build custom nodes that will fit their needs.
Furthermore, note that several tools can be combined within a ROS node, as showcased in [face recognition ROS node](projects/opendr_ws/src/perception/scripts/face_recognition.py).
For example, users can readily use the existing [ROS nodes](../../projects/opendr_ws), e.g., by including the required triggers or by combining several nodes into one to build custom nodes that will fit their needs.
Furthermore, note that several tools can be combined within a ROS node, as showcased in [face recognition ROS node](../../projects/opendr_ws/src/perception/scripts/face_recognition.py).
You can use these nodes as a template for customizing the toolkit to your own needs.
The rest of this document includes instructions for:
1. [Building docker images using the provided docker files](#building-custom-docker-images)
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## Changing the behavior of ROS nodes
ROS nodes are provided as examples that demonstrate how various tools can be used.
As a result, customization might be needed in order to make them appropriate for your specific needs.
Currently, all nodes support changing the input/output topics.
Currently, all nodes support changing the input/output topics (please refer to the [README](../../projects/opendr_ws/src/perception/README.md) for more information for each node).
However, if you need to change anything else (e.g., load a custom model), then you should appropriately modify the source code of the nodes.
This is very easy, since the Python API of the OpenDR is used in all of the provided nodes.
This is very easy, since the Python API of OpenDR is used in all of the provided nodes.
You can refer to [Python API documentation](https://github.com/opendr-eu/opendr/blob/master/docs/reference/index.md) for more details for the tool that you are interested in.

### Loading a custom model
Loading a custom model in a ROS node is very easy.
First, locate the node that you want to modify (e.g., [pose estimation](../../projects/opendr_ws/src/perception/scripts/pose_estimation.py)).
Then, search for the line where the learner loads the model (i.e., calls the `load()` function).
For the aforementioned node, this happens at [line 63](../../projects/opendr_ws/src/perception/scripts/pose_estimation.py#L63).
For the aforementioned node, this happens at [line 76](../../projects/opendr_ws/src/perception/scripts/pose_estimation.py#L76).
Then, replace the path to the `load()` function with the path to your custom model.
You can also optionally remove the call to `download()` function (e.g., [line 62](../../projects/opendr_ws/src/perception/scripts/pose_estimation.py#L62)) to make the node start up faster.
You can also optionally remove the call to `download()` function (e.g., [line 75](../../projects/opendr_ws/src/perception/scripts/pose_estimation.py#L75)) to make the node start up faster.


## Building docker images that do not contain the whole toolkit
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