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Windows binaries #120

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eds89 opened this issue Jan 8, 2018 · 3 comments
Closed

Windows binaries #120

eds89 opened this issue Jan 8, 2018 · 3 comments

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@eds89
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eds89 commented Jan 8, 2018

Hello. Please can you make windows binaries available? I'm having difficulty in compiling it.

@nsubiron
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nsubiron commented Jan 8, 2018

Hi @eds89, although we plan to add it in the future, we currently do not support Windows as we too are having difficulties compiling it ;)

@eds89
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eds89 commented Jan 8, 2018 via email

@nsubiron
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nsubiron commented Jan 9, 2018

Hi @eds89,

Yes, it is possible to run CARLA on Windows, however it needs some extra work as we don't have an automated system yet. Please follow the discussion at #21.

The plugin contains most of the functionality of CARLA, without any of the assets (3D models, etc.). In principle, it can be added to any project and will provide the tools and base classes to build CARLA, say you wanted to build your own CARLA with your own assets. You wouldn't have any of the vehicles, but the base class with the controllers, autopilot and so on. In practice however, this would be a lot of work as there are many pieces to fit and we are still working on documenting everything. We recommend to get the whole project and modify it for your needs.

CARLA does not provide any data fusion algorithm, it just provides the API for you to retrieve the data. This is how it works, the CARLA server runs the simulation, renders the images, and produces all the measurements. We provide a Python API to communicate with the server: set up the simulation, control the car, and retrieve the data; but it's up to the user to code the actual functionality of the client. We have a minimal example of a client using the API at PythonClient/client_example.py.

And yes, if you wanted to add another post-processing effect you need to extend the SceneCaptureCamera. You create a new material as the ones in "Unreal/CarlaUE4/Plugins/Carla/Content/PostProcessingMaterials/", then load it at "SceneCaptureCamera.cpp" and apply it to the camera, just look at how the depth and semantic segmentation are done.

Cheers!

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