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https://github.com/graphdeco-inria/gaussian-splatting
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add best last results..
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@ -21,7 +21,7 @@ fi
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python3.10 convert.py -s $1-data/ --camera SIMPLE_RADIAL --no_gpu #GPU produces worse results (?)
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python3.10 train.py -s $1-data/ -r 1 --model_path=$1-data/output/ --position_lr_init 0.000016 --position_lr_final 0.000001 --scaling_lr 0.001 --iterations 100000 #Test more training budget
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python3.10 train.py -s $1-data/ -r 1 --model_path=$1-data/output/ --position_lr_init 0.000016 --scaling_lr 0.001 --iterations 35000 #Test more training budget
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python3.10 3dgsconverter/3dgsconverter.py -i $1-data/output/point_cloud/iteration_30000/point_cloud.ply -o $1-data/output/point_cloud/iteration_30000/output_cc.ply -f cc --rgb --density_filter --remove_flyers
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python3.10 3dgsconverter/3dgsconverter.py -i $1-data/output/output/point_cloud/iteration_30000/output_cc.ply -o $1-data/output/output/point_cloud/iteration_30000/point_cloud_clean.ply -f 3dgs
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7
train.py
7
train.py
@ -29,6 +29,9 @@ except ImportError:
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TENSORBOARD_FOUND = False
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def training(dataset, opt, pipe, testing_iterations, saving_iterations, checkpoint_iterations, checkpoint, debug_from):
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bestLossEncountered = 1000000
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pickBetweenFinalNLosses = 10
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first_iter = 0
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tb_writer = prepare_output_and_logger(dataset)
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gaussians = GaussianModel(dataset.sh_degree)
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@ -103,6 +106,10 @@ def training(dataset, opt, pipe, testing_iterations, saving_iterations, checkpoi
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if iteration == opt.iterations:
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progress_bar.close()
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if (bestLossEncountered>ema_loss_for_log) and (pickBetweenFinalNLosses+iteration > opt.iterations):
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print("\n[ITER {}] Also remembering this iteration..".format(iteration))
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saving_iterations.append(iteration)
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# Log and save
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training_report(tb_writer, iteration, Ll1, loss, l1_loss, iter_start.elapsed_time(iter_end), testing_iterations, scene, render, (pipe, background))
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if (iteration in saving_iterations):
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