mirror of
https://github.com/nerfstudio-project/nerfstudio.git
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acd126c1ef
* Set dcargs accent color * Bump required dcargs version * color -> colour * Bump dcargs to 0.3.6
52 lines
1.6 KiB
Python
Executable File
52 lines
1.6 KiB
Python
Executable File
#!/usr/bin/env python
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"""
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view_dataset.py
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"""
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import logging
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import time
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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.configs.base_configs import AnnotatedBaseConfigUnion
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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.INFO)
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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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viewer_state = viewer_utils.ViewerState(config.viewer)
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datamanager = config.pipeline.datamanager.setup()
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viewer_state.init_scene(dataset=datamanager.train_input_dataset, start_train=False)
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logging.info("Please refresh and load page at: %s", viewer_state.viewer_url)
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time.sleep(30) # allowing time to refresh page
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if __name__ == "__main__":
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console = Console(width=120)
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dcargs.extras.set_accent_color("bright_yellow")
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instantiated_config = dcargs.cli(AnnotatedBaseConfigUnion)
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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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