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fixup
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1 changed files with 2 additions and 3 deletions
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@ -19,8 +19,8 @@ def parse_args():
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parser = argparse.ArgumentParser(description="Output water depth image segmentation maps using a given pretrained mono model.")
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# parser.add_argument("--config", "-c", help="Filepath to the TOML config file to load.", required=True)
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parser.add_argument("--input", "-i", help="Path to input directory containing the .tfrecord(.gz) files to predict for. If a single file is passed instead, then only that file will be converted.", required=True)
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parser.add_argument("--reads-multiplier", help="Optional. The multiplier for the number of files we should read from at once. Defaults to 0. When using this start with 1.5, which means read ceil(NUMBER_OF_CORES * 1.5). Set to a higher number of systems with high read latency to avoid starving the GPU of data. SETTING THIS WILL SCRAMBLE THE ORDER OF THE DATASET.")
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parser.add_argument("--batch-size", help="Optional. The batch size to calculate statistics with. Can be larger than normal since we don't have a model loaded. Default: 1024")
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parser.add_argument("--reads-multiplier", help="Optional. The multiplier for the number of files we should read from at once. Defaults to 0. When using this start with 1.5, which means read ceil(NUMBER_OF_CORES * 1.5). Set to a higher number of systems with high read latency to avoid starving the GPU of data. SETTING THIS WILL SCRAMBLE THE ORDER OF THE DATASET.", type=int)
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parser.add_argument("--batch-size", help="Optional. The batch size to calculate statistics with. Can be larger than normal since we don't have a model loaded. Default: 1024", type=int)
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return parser
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def run(args):
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@ -30,7 +30,6 @@ def run(args):
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if (not hasattr(args, "batch_size")) or args.batch_size == None:
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args.batch_size = 1024
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sys.stderr.write(f"\n\n>>> This is TensorFlow {tf.__version__}\n\n\n")
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# Note that if using a directory of input files, the output order is NOT GUARANTEED TO BE THE SAME. In fact, it probably won't be (see dataset_mono for more details).
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