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https://github.com/nerfstudio-project/nerfstudio.git
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49 lines
1.5 KiB
Python
49 lines
1.5 KiB
Python
"""
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view_dataset.py
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"""
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import logging
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from datetime import timedelta
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import dcargs
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import torch
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import yaml
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from rich.console import Console
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from nerfactory.configs import base as cfg
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from nerfactory.viewer.server import viewer_utils
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logging.basicConfig(format="[%(filename)s:%(lineno)d] %(message)s", level=logging.DEBUG)
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DEFAULT_TIMEOUT = timedelta(minutes=30)
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# speedup for when input size to model doesn't change (much)
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torch.backends.cudnn.benchmark = True # type: ignore
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def main(config: cfg.Config) -> None:
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"""Main function."""
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if not config.viewer.enable:
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config.viewer.enable = True
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logging.info("Enabling viewer to view dataset")
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visualizer_state = viewer_utils.VisualizerState(config.viewer)
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datamanager = config.pipeline.datamanager.setup()
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visualizer_state.init_scene(dataset=datamanager.train_input_dataset, start_train=False)
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if __name__ == "__main__":
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console = Console(width=120)
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from nerfactory.configs.base_configs import base_configs
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SubcommandType = dcargs.extras.subcommand_type_from_defaults(base_configs)
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instantiated_config = dcargs.cli(SubcommandType)
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if instantiated_config.trainer.load_config:
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logging.info(f"Loading pre-set config from: {instantiated_config.trainer.load_config}")
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instantiated_config = yaml.load(instantiated_config.trainer.load_config.read_text(), Loader=yaml.Loader)
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console.rule("Config")
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console.print(instantiated_config)
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console.rule("")
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main(config=instantiated_config)
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