From a5d1dc8b83bc3d3c47635720ffbb2b6a4ec5477f Mon Sep 17 00:00:00 2001 From: bkerbl Date: Wed, 5 Jul 2023 15:58:51 +0200 Subject: [PATCH] Smaller headings --- README.md | 86 +++++++++++++++++++++++++++---------------------------- 1 file changed, 43 insertions(+), 43 deletions(-) diff --git a/README.md b/README.md index debca61..e2c6221 100644 --- a/README.md +++ b/README.md @@ -99,65 +99,65 @@ python train.py -s
Command Line Arguments for train.py - ### --source_path / -s + #### --source_path / -s Path to the source directory containing a COLMAP or Synthetic NeRF data set. - ### --model_path / -m + #### --model_path / -m Path where the trained model should be stored (```output/``` by default). - ### --images / -i + #### --images / -i Alternative subdirectory for COLMAP images (```images``` by default). - ### --eval + #### --eval Add this flag to use a MipNeRF360-style training/test split for evaluation. - ### --resolution / -r + #### --resolution / -r Changes the resolution of the loaded images before training. If provided ```1, 2, 4``` or ```8```, uses original, 1/2, 1/4 or 1/8 resolution, respectively. For all other values, rescales the width to the given number while maintaining image aspect. ```1``` by default. - ### --white_background / -w + #### --white_background / -w Add this flag to use white background instead of black (default), e.g., for evaluation of NeRF Synthetic dataset. - ### --sh_degree + #### --sh_degree Order of spherical harmonics to be used (no larger than 3). ```3``` by default. - ### --convert_SHs_python + #### --convert_SHs_python Flag to make pipeline compute forward and backward of SHs with PyTorch instead of ours. - ### --convert_cov3D_python + #### --convert_cov3D_python Flag to make pipeline compute forward and backward of the 3D covariance with PyTorch instead of ours. - ### --iterations + #### --iterations Number of total iterations to train for, ```30_000``` by default. - ### --feature_lr + #### --feature_lr Spherical harmonics features learning rate, ```0.0025``` by default. - ### --opacity_lr + #### --opacity_lr Opacity learning rate, ```0.05``` by default. - ### --scaling_lr + #### --scaling_lr Scaling learning rate, ```0.001``` by default. - ### --rotation_lr + #### --rotation_lr Rotation learning rate, ```0.001``` by default. - ### --position_lr_max_steps + #### --position_lr_max_steps Number of steps (from 0) where position learning rate goes from ```initial``` to ```final```. ```30_000``` by default. - ### --position_lr_init + #### --position_lr_init Initial 3D position learning rate, ```0.00016``` by default. - ### --position_lr_final + #### --position_lr_final Final 3D position learning rate, ```0.0000016``` by default. - ### --position_lr_delay_mult + #### --position_lr_delay_mult Position learning rate multiplier (cf. Plenoxels), ```0.01``` by default. - ### --densify_from_iter + #### --densify_from_iter Iteration where densification starts, ```500``` by default. - ### --densify_until_iter + #### --densify_until_iter Iteration where densification stops, ```15_000``` by default. - ### --densify_grad_threshold + #### --densify_grad_threshold Limit that decides if points should be densified based on 2D position gradient, ```0.0002``` by default. - ### --densification_interal + #### --densification_interal How frequently to densify, ```100``` (every 100 iterations) by default. - ### --opacity_reset_interval + #### --opacity_reset_interval How frequently to reset opacity, ```3_000``` by default. - ### --lambda_dssim + #### --lambda_dssim Influence of SSIM on total loss from 0 to 1, ```0.2``` by default. - ### --percent_dense + #### --percent_dense Percentage of scene extent (0--1) a point must exceed to be forcibly densified, ```0.1``` by default. - ### --ip + #### --ip IP to start GUI server on, ```127.0.0.1``` by default. - ### --port + #### --port Port to use for GUI server, ```6009``` by default. - ### --test_iterations + #### --test_iterations Space-separated iterations at which the training script computes L1 and PSNR over test set, ```7000 30000``` by default. - ### --save_iterations + #### --save_iterations Space-separated iterations at which the training script saves the Gaussian model, ```7000 30000 ``` by default. - ### --quiet + #### --quiet Flag to omit any text written to standard out pipe.
@@ -175,38 +175,38 @@ python metrics.py -m # Compute error metrics on renderin ```
- Command Line Arguments for render.py +Command Line Arguments for render.py - ### --model_path / -m + #### --model_path / -m Path where the trained model should be stored (```output/``` by default). - ### --skip_train + #### --skip_train Flag to skip rendering the training set. - ### --skip_test + #### --skip_test Flag to skip rendering the test set. - ### --quiet + #### --quiet Flag to omit any text written to standard out pipe. **The below parameters will be read automatically from the model path, based on what was used for training. However, you may override them by providing them explicitly on the command line.** - ### --source_path / -s + #### --source_path / -s Path to the source directory containing a COLMAP or Synthetic NeRF data set. - ### --images / -i + #### --images / -i Alternative subdirectory for COLMAP images (```images``` by default). - ### --eval + #### --eval Add this flag to use a MipNeRF360-style training/test split for evaluation. - ### --resolution / -r + #### --resolution / -r Changes the resolution of the loaded images before training. If provided ```1, 2, 4``` or ```8```, uses original, 1/2, 1/4 or 1/8 resolution, respectively. For all other values, rescales the width to the given number while maintaining image aspect. ```1``` by default. - ### --white_background / -w + #### --white_background / -w Add this flag to use white background instead of black (default), e.g., for evaluation of NeRF Synthetic dataset. - ### --convert_SHs_python + #### --convert_SHs_python Flag to make pipeline render with computed SHs from PyTorch instead of ours. - ### --convert_cov3D_python + #### --convert_cov3D_python Flag to make pipeline render with computed 3D covariance from PyTorch instead of ours.
- Command Line Arguments for metrics.py +Command Line Arguments for metrics.py ### --model_paths / -m Space-separated list of model paths for which metrics should be computed.