From 6189b96a304e9851e374b3cdbf1d800f4c3731e5 Mon Sep 17 00:00:00 2001 From: Krishna Murthy Date: Thu, 16 Apr 2020 20:51:51 -0400 Subject: [PATCH] Fix headings Signed-off-by: Krishna Murthy --- README.md | 8 ++++++-- 1 file changed, 6 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 1c74769..a20ea24 100644 --- a/README.md +++ b/README.md @@ -32,7 +32,7 @@ The current implementation is **_blazing fast!_** (**~5-9x faster** than the [or ## Sample results from the repo -#### On synthetic data +### On synthetic data

@@ -80,6 +80,8 @@ conda env create conda activate nerf ``` +### Run training! + Once everything is setup, to run experiments, first edit `config/lego.yml` to specify your own parameters. The training script can be invoked by running @@ -87,12 +89,14 @@ The training script can be invoked by running python train_nerf.py --config config/lego.yml ``` +### Optional: Resume training from a checkpoint + Optionally, if resuming training from a previous checkpoint, run ```bash python train_nerf.py --config config/lego.yml --load-checkpoint path/to/checkpoint.ckpt ``` -### Cache rays from the dataset (Optional) +### Optional: Cache rays from the dataset An optional, yet simple preprocessing step of caching rays from the dataset results in substantial compute time savings (reduced carbon footprint, yay!), especially when running multiple experiments. It's super-simple: run ```bash