Workspace with Deeplab #16
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Instead of copying the template_ws and installing PyTorch inside it, I made several changes:
- Dockerfile:
- Changed the base image.
- I believe installing PyTorch is more challenging than ROS 2 Humble.
- Manually installed ROS 2 Humble.
- docker-compose:
- Enabled GPU access.
- Mounted shared memory.
- For communication between containers.
- Mounted PyTorch cache.
- Keep the models in the cache folder.
Add the CMakeLists.txt and package.xml files to the folder to indicate that it is a ROS package.
The original repository contains lots of training code and utility code. For our use here, we only need the code for inference.
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This is the DeepLab pipeline.