From b5672dd6fd3edc0055c9aef0c831667844ee8be4 Mon Sep 17 00:00:00 2001 From: Justin Kerr Date: Thu, 30 May 2024 12:34:27 -0700 Subject: [PATCH] params --- nerfstudio/configs/method_configs.py | 8 ++++---- nerfstudio/models/splatfacto.py | 8 ++++---- 2 files changed, 8 insertions(+), 8 deletions(-) diff --git a/nerfstudio/configs/method_configs.py b/nerfstudio/configs/method_configs.py index 0c8e76228..88d8e1369 100644 --- a/nerfstudio/configs/method_configs.py +++ b/nerfstudio/configs/method_configs.py @@ -602,7 +602,7 @@ method_configs["splatfacto"] = TrainerConfig( pipeline=VanillaPipelineConfig( datamanager=FullImageDatamanagerConfig( _target=FullImageDatamanager[DepthDataset], - dataparser=NerfstudioDataParserConfig(load_3D_points=True,depth_unit_scale_factor=1.0), + dataparser=NerfstudioDataParserConfig(load_3D_points=True,depth_unit_scale_factor=1.0,train_split_fraction=.5), cache_images_type="uint8", ), model=SplatfactoModelConfig( @@ -630,14 +630,14 @@ method_configs["splatfacto"] = TrainerConfig( "scheduler": None, }, "scales": { - "optimizer": AdamOptimizerConfig(lr=0.005, eps=1e-15), + "optimizer": AdamOptimizerConfig(lr=0.003, eps=1e-15), "scheduler": None, }, "quats": {"optimizer": AdamOptimizerConfig(lr=0.001, eps=1e-15), "scheduler": None}, "camera_opt": { - "optimizer": AdamOptimizerConfig(lr=2e-5, eps=1e-15), + "optimizer": AdamOptimizerConfig(lr=1e-5, eps=1e-15), "scheduler": ExponentialDecaySchedulerConfig( - lr_final=5e-7, max_steps=30000, warmup_steps=3000, lr_pre_warmup=0 + lr_final=5e-7, max_steps=30000, warmup_steps=6000, lr_pre_warmup=0 ), }, }, diff --git a/nerfstudio/models/splatfacto.py b/nerfstudio/models/splatfacto.py index 5c7053339..234aef047 100644 --- a/nerfstudio/models/splatfacto.py +++ b/nerfstudio/models/splatfacto.py @@ -145,7 +145,7 @@ class SplatfactoModelConfig(ModelConfig): """below this size, gaussians are *duplicated*, otherwise split""" n_split_samples: int = 2 """number of samples to split gaussians into""" - sh_degree_interval: int = 3000 + sh_degree_interval: int = 2000 """every n intervals turn on another sh degree""" split_screen_size: float = 0.05 """if a gaussian is more than this percent of screen space, split it""" @@ -820,7 +820,7 @@ class SplatfactoModel(Model): #convert to float32 mask = self._downscale_if_required(batch["mask"].float()) mask = mask.to(self.device) - mask[mask<1]=0.0 + mask[mask<1] = 0.0 assert mask.shape[:2] == gt_img.shape[:2] == pred_img.shape[:2] gt_img = gt_img * mask pred_img = pred_img * mask @@ -842,8 +842,8 @@ class SplatfactoModel(Model): if 'depth_image' in batch: gt_depth = self.get_gt_img(batch['depth_image']) ignores = gt_depth <= .001 - # if "mask" in batch: - # ignores = ignores | (mask == 0) + if "mask" in batch: + ignores = ignores | (mask == 0) depth_loss = (gt_depth - outputs['depth'])[~ignores].abs().mean() else: depth_loss = torch.tensor(0.0).to(self.device)