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Setup guide on GCP
Here are the steps to run gibson on GCP,
Use a similar configuration as the following to create a virtual machine, choose K80, P100 or V100 GPU. I choose c1-deeplearning-pytorch-0-4-cu92-20181009
image because it has CUDA and nvidia-docker already installed so requires minimal setup.
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Install nvidia-driver:
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Setup firewall rules to allow traffic (the web UI uses flask, the port is configurable)
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Download dataset and pull gibson docker:
wget https://storage.googleapis.com/gibson_scenes/dataset.tar.gz
tar -zxf dataset.tar.gz
docker pull xf1280/gibson:0.3.1
docker run --runtime=nvidia -ti -v <dataset root>:/root/mount/gibson/gibson/assets/dataset -p 5001:5001 xf1280/gibson:0.3.1
In docker container, open tmux
and run python examples/demo/benchmark_fps.py
in one tab and python gibson/utils/web_ui.py
in another.
To order to use web UI, you would need to change mode
into web_ui
in yaml file.
You should be visit gcp-external-ip:5001
to see the web UI rendered.