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Thanks for your interest in our work. We've modified the code. You can pull the recent release and refer to README.md. Specifically, it's required to implement the code to process your own dataset under the lib/dataset/ directory. You can refer to lib/dataset/shelf.py and rewrite the _get_db and _get_cam functions to take RGB images and camera params as input. Then modify the config file based on configs/shelf/jln64.yaml. Then you can adopt the same training strategy as what we use on the Campus and Shelf datasets, i.e. synthesizing training poses with Panoptic dataset.
How do I make predictions on my own dataset?
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