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25 lines
1.6 KiB
Bash
Executable File
25 lines
1.6 KiB
Bash
Executable File
#!/bin/bash
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echo "Evaluation for linearization then nerf pipeline"
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dataset_name=lab_downstairs_ns
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method_name=lantern-nerfacto
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root_dir=/mnt/data/nerfstudio_ds/real_data/lab_downstairs_data
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dataset_dir=$root_dir/$dataset_name/
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opensfm_dir=$root_dir/lab_downstairs_openSFM
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opensfm_file=$opensfm_dir/reconstruction.json
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echo "Step one of training"
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ns-train lantern-nerfacto --data $dataset_dir --viewer.websocket-port 8008 --pipeline.datamanager.train-num-images-to-sample-from 1800 \
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--pipeline.model.lantern_steps 1 --pipeline.datamanager.pixel-sampler.lantern_steps 1 \
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--pipeline.datamanager.camera-optimizer.mode off --viewer.quit-on-train-completion True --output-dir outputs --timestamp step_1
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echo "Step two of training"
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#ns-train lantern-nerfacto --data $dataset_dir --viewer.websocket-port 8008 --pipeline.datamanager.train-num-images-to-sample-from 1800 \
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#--pipeline.model.lantern_steps 2 --pipeline.datamanager.pixel-sampler.lantern_steps 2 --pipeline.model.apply_mu_law False \
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#--pipeline.datamanager.camera-optimizer.mode off --viewer.quit-on-train-completion True --load-dir outputs/$dataset_name/lantern-nerfacto/step_1/nerfstudio_models \
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#--output-dir outputs --timestamp step_2
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ns-train lantern-nerfacto --data $dataset_dir --viewer.websocket-port 8008 --pipeline.datamanager.train-num-images-to-sample-from 1800 \
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--pipeline.model.lantern_steps 2 --pipeline.datamanager.pixel-sampler.lantern_steps 2 \
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--pipeline.datamanager.camera-optimizer.mode off --load-dir outputs/$dataset_name/lantern-nerfacto/step_1/nerfstudio_models \
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--output-dir outputs --timestamp step_2 |