BiohazardVFX/4DGaussians
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fix-grid-lr-bug

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guanjunwu 2023-10-14 23:43:38 +08:00
parent d3fdb452e1
commit 4b181e2b34
7 changed files with 27 additions and 21 deletions
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4
.gitignore vendored
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@ -7,4 +7,6 @@ diff_rasterization/dist
tensorboard_3d tensorboard_3d
screenshots screenshots
data/ data/
data data
argument/
scripts/

2
README.md
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@ -4,9 +4,7 @@
### [Project Page](https://guanjunwu.github.io/4dgs/index.html)| [Arxiv Paper](https://arxiv.org/abs/2310.08528) ### [Project Page](https://guanjunwu.github.io/4dgs/index.html)| [Arxiv Paper](https://arxiv.org/abs/2310.08528)
<!-- | [Video](https://youtu.be/sROLfK_VkCk) -->
<!-- [Fast Dynamic Radiance Fields with Time-Aware Neural Voxels](https://jaminfong.cn/tineuvox) -->
[Guanjun Wu](https://guanjunwu.github.io/)<sup>1*</sup>, [Taoran Yi](https://github.com/taoranyi)<sup>2*</sup>, [Guanjun Wu](https://guanjunwu.github.io/)<sup>1*</sup>, [Taoran Yi](https://github.com/taoranyi)<sup>2*</sup>,
[Jiemin Fang](https://jaminfong.cn/)<sup>3</sup>, [Lingxi Xie](http://lingxixie.com/)<sup>3</sup>, </br>[Xiaopeng Zhang](https://sites.google.com/site/zxphistory/)<sup>3</sup>, [Wei Wei](https://www.eric-weiwei.com/)<sup>1</sup>,[Wenyu Liu](http://eic.hust.edu.cn/professor/liuwenyu/)<sup>2</sup>, [Qi Tian](https://scholar.google.com/citations?hl=en&user=61b6eYkAAAAJ)<sup>3</sup> , [Xinggang Wang](https://xinggangw.info/)<sup>2✉</sup> [Jiemin Fang](https://jaminfong.cn/)<sup>3</sup>, [Lingxi Xie](http://lingxixie.com/)<sup>3</sup>, </br>[Xiaopeng Zhang](https://sites.google.com/site/zxphistory/)<sup>3</sup>, [Wei Wei](https://www.eric-weiwei.com/)<sup>1</sup>,[Wenyu Liu](http://eic.hust.edu.cn/professor/liuwenyu/)<sup>2</sup>, [Qi Tian](https://scholar.google.com/citations?hl=en&user=61b6eYkAAAAJ)<sup>3</sup> , [Xinggang Wang](https://xinggangw.info/)<sup>2✉</sup>

6
arguments/dnerf_tv/dnerf_default.py
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@ -20,9 +20,9 @@ ModelHiddenParams = dict(
multires = [1, 2, 4, 8 ], multires = [1, 2, 4, 8 ],
defor_depth = 0, defor_depth = 0,
net_width = 64, net_width = 64,
# plane_tv_weight = 0, plane_tv_weight = 0.0002,
# time_smoothness_weight = 0, time_smoothness_weight = 0.001,
# l1_time_planes = 0, l1_time_planes = 0.001,
weight_decay_iteration=0, weight_decay_iteration=0,
bounds=1.6 bounds=1.6
) )

2
render.py
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@ -40,7 +40,7 @@ def render_set(model_path, name, iteration, views, gaussians, pipeline, backgrou
# torchvision.utils.save_image(rendering, os.path.join(render_path, '{0:05d}'.format(idx) + ".png")) # torchvision.utils.save_image(rendering, os.path.join(render_path, '{0:05d}'.format(idx) + ".png"))
render_images.append(to8b(rendering).transpose(1,2,0)) render_images.append(to8b(rendering).transpose(1,2,0))
# print(to8b(rendering).shape) # print(to8b(rendering).shape)
# render_list.append(rendering) render_list.append(rendering)
if name in ["train", "test"]: if name in ["train", "test"]:
gt = view.original_image[0:3, :, :] gt = view.original_image[0:3, :, :]
# torchvision.utils.save_image(gt, os.path.join(gts_path, '{0:05d}'.format(idx) + ".png")) # torchvision.utils.save_image(gt, os.path.join(gts_path, '{0:05d}'.format(idx) + ".png"))

13
scene/gaussian_model.py
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@ -18,7 +18,7 @@ from utils.system_utils import mkdir_p
from plyfile import PlyData, PlyElement from plyfile import PlyData, PlyElement
from random import randint from random import randint
from utils.sh_utils import RGB2SH from utils.sh_utils import RGB2SH
# from simple_knn._C import distCUDA2 from simple_knn._C import distCUDA2
from utils.graphics_utils import BasicPointCloud from utils.graphics_utils import BasicPointCloud
from utils.general_utils import strip_symmetric, build_scaling_rotation from utils.general_utils import strip_symmetric, build_scaling_rotation
from scene.deformation import deform_network from scene.deformation import deform_network
@ -143,7 +143,7 @@ class GaussianModel:
print("Number of points at initialisation : ", fused_point_cloud.shape[0]) print("Number of points at initialisation : ", fused_point_cloud.shape[0])
dist2 = torch.clamp_min(torch.from_numpy(np.asarray(pcd.points)).float().cuda()) dist2 = torch.clamp_min(distCUDA2(torch.from_numpy(np.asarray(pcd.points)).float().cuda()), 0.0000001)
scales = torch.log(torch.sqrt(dist2))[...,None].repeat(1, 3) scales = torch.log(torch.sqrt(dist2))[...,None].repeat(1, 3)
rots = torch.zeros((fused_point_cloud.shape[0], 4), device="cuda") rots = torch.zeros((fused_point_cloud.shape[0], 4), device="cuda")
rots[:, 0] = 1 rots[:, 0] = 1
@ -188,6 +188,10 @@ class GaussianModel:
lr_final=training_args.deformation_lr_final*self.spatial_lr_scale, lr_final=training_args.deformation_lr_final*self.spatial_lr_scale,
lr_delay_mult=training_args.deformation_lr_delay_mult, lr_delay_mult=training_args.deformation_lr_delay_mult,
max_steps=training_args.position_lr_max_steps) max_steps=training_args.position_lr_max_steps)
self.grid_scheduler_args = get_expon_lr_func(lr_init=training_args.grid_lr_init*self.spatial_lr_scale,
lr_final=training_args.grid_lr_final*self.spatial_lr_scale,
lr_delay_mult=training_args.deformation_lr_delay_mult,
max_steps=training_args.position_lr_max_steps)
def update_learning_rate(self, iteration): def update_learning_rate(self, iteration):
''' Learning rate scheduling per step ''' ''' Learning rate scheduling per step '''
@ -196,7 +200,10 @@ class GaussianModel:
lr = self.xyz_scheduler_args(iteration) lr = self.xyz_scheduler_args(iteration)
param_group['lr'] = lr param_group['lr'] = lr
# return lr # return lr
if "grid" in param_group["name"]:
lr = self.grid_scheduler_args(iteration)
param_group['lr'] = lr
# return lr
elif param_group["name"] == "deformation": elif param_group["name"] == "deformation":
lr = self.deformation_scheduler_args(iteration) lr = self.deformation_scheduler_args(iteration)
param_group['lr'] = lr param_group['lr'] = lr

16
scripts/process_dnerf.sh
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@ -17,26 +17,26 @@ echo "Done"
exp_name1=$1 exp_name1=$1
export CUDA_VISIBLE_DEVICES=2&&python render.py --model_path "output/$exp_name1/standup/" --skip_train --configs arguments/$exp_name1/standup.py & export CUDA_VISIBLE_DEVICES=0&&python render.py --model_path "output/$exp_name1/standup/" --skip_train --configs arguments/$exp_name1/standup.py &
export CUDA_VISIBLE_DEVICES=3&&python render.py --model_path "output/$exp_name1/jumpingjacks/" --skip_train --configs arguments/$exp_name1/jumpingjacks.py & export CUDA_VISIBLE_DEVICES=1&&python render.py --model_path "output/$exp_name1/jumpingjacks/" --skip_train --configs arguments/$exp_name1/jumpingjacks.py &
export CUDA_VISIBLE_DEVICES=2&&python render.py --model_path "output/$exp_name1/bouncingballs/" --skip_train --configs arguments/$exp_name1/bouncingballs.py & export CUDA_VISIBLE_DEVICES=2&&python render.py --model_path "output/$exp_name1/bouncingballs/" --skip_train --configs arguments/$exp_name1/bouncingballs.py &
export CUDA_VISIBLE_DEVICES=3&&python render.py --model_path "output/$exp_name1/lego/" --skip_train --configs arguments/$exp_name1/lego.py & export CUDA_VISIBLE_DEVICES=3&&python render.py --model_path "output/$exp_name1/lego/" --skip_train --configs arguments/$exp_name1/lego.py &
wait wait
export CUDA_VISIBLE_DEVICES=2&&python render.py --model_path "output/$exp_name1/hellwarrior/" --skip_train --configs arguments/$exp_name1/hellwarrior.py & export CUDA_VISIBLE_DEVICES=0&&python render.py --model_path "output/$exp_name1/hellwarrior/" --skip_train --configs arguments/$exp_name1/hellwarrior.py &
export CUDA_VISIBLE_DEVICES=3&&python render.py --model_path "output/$exp_name1/hook/" --skip_train --configs arguments/$exp_name1/hook.py & export CUDA_VISIBLE_DEVICES=1&&python render.py --model_path "output/$exp_name1/hook/" --skip_train --configs arguments/$exp_name1/hook.py &
export CUDA_VISIBLE_DEVICES=2&&python render.py --model_path "output/$exp_name1/trex/" --skip_train --configs arguments/$exp_name1/trex.py & export CUDA_VISIBLE_DEVICES=2&&python render.py --model_path "output/$exp_name1/trex/" --skip_train --configs arguments/$exp_name1/trex.py &
export CUDA_VISIBLE_DEVICES=3&&python render.py --model_path "output/$exp_name1/mutant/" --skip_train --configs arguments/$exp_name1/mutant.py & export CUDA_VISIBLE_DEVICES=3&&python render.py --model_path "output/$exp_name1/mutant/" --skip_train --configs arguments/$exp_name1/mutant.py &
# wait # wait
echo "Done" echo "Done"
exp_name1=$1 exp_name1=$1
export CUDA_VISIBLE_DEVICES=2&&python metrics.py --model_path "output/$exp_name1/standup/" & export CUDA_VISIBLE_DEVICES=0&&python metrics.py --model_path "output/$exp_name1/standup/" &
export CUDA_VISIBLE_DEVICES=3&&python metrics.py --model_path "output/$exp_name1/jumpingjacks/" & export CUDA_VISIBLE_DEVICES=1&&python metrics.py --model_path "output/$exp_name1/jumpingjacks/" &
export CUDA_VISIBLE_DEVICES=2&&python metrics.py --model_path "output/$exp_name1/bouncingballs/" & export CUDA_VISIBLE_DEVICES=2&&python metrics.py --model_path "output/$exp_name1/bouncingballs/" &
export CUDA_VISIBLE_DEVICES=3&&python metrics.py --model_path "output/$exp_name1/lego/" export CUDA_VISIBLE_DEVICES=3&&python metrics.py --model_path "output/$exp_name1/lego/"
export CUDA_VISIBLE_DEVICES=2&&python metrics.py --model_path "output/$exp_name1/hellwarrior/" & export CUDA_VISIBLE_DEVICES=0&&python metrics.py --model_path "output/$exp_name1/hellwarrior/" &
export CUDA_VISIBLE_DEVICES=3&&python metrics.py --model_path "output/$exp_name1/hook/" & export CUDA_VISIBLE_DEVICES=1&&python metrics.py --model_path "output/$exp_name1/hook/" &
export CUDA_VISIBLE_DEVICES=2&&python metrics.py --model_path "output/$exp_name1/trex/" & export CUDA_VISIBLE_DEVICES=2&&python metrics.py --model_path "output/$exp_name1/trex/" &
export CUDA_VISIBLE_DEVICES=3&&python metrics.py --model_path "output/$exp_name1/mutant/" & export CUDA_VISIBLE_DEVICES=3&&python metrics.py --model_path "output/$exp_name1/mutant/" &
wait wait

5
scripts/read_all_metrics.py
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@ -1,8 +1,7 @@
import json import json
import os import os
exp_name = ["dnerf_gridlarge","dnerf_gridsmall","dnerf_gridsmaller","dnerf_mlplarge","dnerf_mlplarger","dnerf_nocoarse","dnerf_silm","dnerf_imageloss", exp_name = ["dnerf_tv_test"]
"dnerf_3dgs","dnerf_tv","dnerf_noboth","dnerf_nogrid"] scene_name = ["bouncingballs","jumpingjacks","lego","standup","hook","mutant","hellwarrior","trex"]
scene_name = ["bouncingball","jumpingjack","lego","standup","hook","mutant","hellwarrior","trex"]
json_name = "results.json" json_name = "results.json"
result_json = {"SSIM":0,"PSNR":0,"LPIPS":0} result_json = {"SSIM":0,"PSNR":0,"LPIPS":0}
exp_json = {} exp_json = {}