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53 lines
1.4 KiB
Python
53 lines
1.4 KiB
Python
"""
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Process the Mipnerf360 dataset.
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"""
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from nerfstudio.utils.scripts import run_command
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capture_names = [
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"Egypt",
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"person",
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"kitchen",
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"plane",
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"dozer",
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"floating-tree",
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"aspen",
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"stump",
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"sculpture",
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"Giannini-Hall",
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]
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table_rows = [
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("nerfacto", ""),
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("w/o-pose", "--pipeline.datamanager.camera-optimizer.mode off"),
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("w/o-app", "--pipeline.model.use-appearance-embedding False"),
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(
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"w/o-pose-app",
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"--pipeline.datamanager.camera-optimizer.mode off --pipeline.model.use-appearance-embedding False",
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),
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(
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"1-prop-network",
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"--pipeline.model.num-proposal-samples-per-ray \"256\" --pipeline.model.num_proposal_iterations 1",
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),
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]
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# 30K iterations
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for capture_name in capture_names:
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for table_row_name, table_row_command in table_rows:
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# TODO: find an available GPU
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gpu = 0
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command = " ".join(
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(
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# f"CUDA_VISIBLE_DEVICES={gpu}",
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f"ns-train nerfacto",
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"--vis wandb",
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f"--data data/nerfstudio/{capture_name}",
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"--pipeline.eval_optimize_cameras True --pipeline.eval_optimize_appearance True",
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f"--wandb-name {capture_name}-{table_row_name} --experiment-name {capture_name}-{table_row_name}",
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table_row_command,
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)
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)
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print(command)
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