fix-grid-lr-bug
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guanjunwu
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@ -7,4 +7,6 @@ diff_rasterization/dist
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tensorboard_3d
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screenshots
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data/
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data
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data
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argument/
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scripts/
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@ -4,9 +4,7 @@
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### [Project Page](https://guanjunwu.github.io/4dgs/index.html)| [Arxiv Paper](https://arxiv.org/abs/2310.08528)
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<!-- | [Video](https://youtu.be/sROLfK_VkCk) -->
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<!-- [Fast Dynamic Radiance Fields with Time-Aware Neural Voxels](https://jaminfong.cn/tineuvox) -->
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[Guanjun Wu](https://guanjunwu.github.io/)<sup>1*</sup>, [Taoran Yi](https://github.com/taoranyi)<sup>2*</sup>,
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[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>
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@ -20,9 +20,9 @@ ModelHiddenParams = dict(
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multires = [1, 2, 4, 8 ],
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defor_depth = 0,
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net_width = 64,
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# plane_tv_weight = 0,
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# time_smoothness_weight = 0,
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# l1_time_planes = 0,
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plane_tv_weight = 0.0002,
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time_smoothness_weight = 0.001,
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l1_time_planes = 0.001,
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weight_decay_iteration=0,
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bounds=1.6
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)
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@ -40,7 +40,7 @@ def render_set(model_path, name, iteration, views, gaussians, pipeline, backgrou
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# torchvision.utils.save_image(rendering, os.path.join(render_path, '{0:05d}'.format(idx) + ".png"))
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render_images.append(to8b(rendering).transpose(1,2,0))
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# print(to8b(rendering).shape)
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# render_list.append(rendering)
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render_list.append(rendering)
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if name in ["train", "test"]:
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gt = view.original_image[0:3, :, :]
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# torchvision.utils.save_image(gt, os.path.join(gts_path, '{0:05d}'.format(idx) + ".png"))
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@ -18,7 +18,7 @@ from utils.system_utils import mkdir_p
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from plyfile import PlyData, PlyElement
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from random import randint
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from utils.sh_utils import RGB2SH
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# from simple_knn._C import distCUDA2
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from simple_knn._C import distCUDA2
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from utils.graphics_utils import BasicPointCloud
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from utils.general_utils import strip_symmetric, build_scaling_rotation
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from scene.deformation import deform_network
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@ -143,7 +143,7 @@ class GaussianModel:
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print("Number of points at initialisation : ", fused_point_cloud.shape[0])
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dist2 = torch.clamp_min(torch.from_numpy(np.asarray(pcd.points)).float().cuda())
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dist2 = torch.clamp_min(distCUDA2(torch.from_numpy(np.asarray(pcd.points)).float().cuda()), 0.0000001)
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scales = torch.log(torch.sqrt(dist2))[...,None].repeat(1, 3)
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rots = torch.zeros((fused_point_cloud.shape[0], 4), device="cuda")
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rots[:, 0] = 1
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@ -188,6 +188,10 @@ class GaussianModel:
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lr_final=training_args.deformation_lr_final*self.spatial_lr_scale,
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lr_delay_mult=training_args.deformation_lr_delay_mult,
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max_steps=training_args.position_lr_max_steps)
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self.grid_scheduler_args = get_expon_lr_func(lr_init=training_args.grid_lr_init*self.spatial_lr_scale,
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lr_final=training_args.grid_lr_final*self.spatial_lr_scale,
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lr_delay_mult=training_args.deformation_lr_delay_mult,
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max_steps=training_args.position_lr_max_steps)
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def update_learning_rate(self, iteration):
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''' Learning rate scheduling per step '''
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@ -196,7 +200,10 @@ class GaussianModel:
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lr = self.xyz_scheduler_args(iteration)
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param_group['lr'] = lr
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# return lr
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if "grid" in param_group["name"]:
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lr = self.grid_scheduler_args(iteration)
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param_group['lr'] = lr
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# return lr
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elif param_group["name"] == "deformation":
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lr = self.deformation_scheduler_args(iteration)
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param_group['lr'] = lr
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@ -17,26 +17,26 @@ echo "Done"
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exp_name1=$1
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export CUDA_VISIBLE_DEVICES=2&&python render.py --model_path "output/$exp_name1/standup/" --skip_train --configs arguments/$exp_name1/standup.py &
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export CUDA_VISIBLE_DEVICES=3&&python render.py --model_path "output/$exp_name1/jumpingjacks/" --skip_train --configs arguments/$exp_name1/jumpingjacks.py &
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export CUDA_VISIBLE_DEVICES=0&&python render.py --model_path "output/$exp_name1/standup/" --skip_train --configs arguments/$exp_name1/standup.py &
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export CUDA_VISIBLE_DEVICES=1&&python render.py --model_path "output/$exp_name1/jumpingjacks/" --skip_train --configs arguments/$exp_name1/jumpingjacks.py &
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export CUDA_VISIBLE_DEVICES=2&&python render.py --model_path "output/$exp_name1/bouncingballs/" --skip_train --configs arguments/$exp_name1/bouncingballs.py &
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export CUDA_VISIBLE_DEVICES=3&&python render.py --model_path "output/$exp_name1/lego/" --skip_train --configs arguments/$exp_name1/lego.py &
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wait
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export CUDA_VISIBLE_DEVICES=2&&python render.py --model_path "output/$exp_name1/hellwarrior/" --skip_train --configs arguments/$exp_name1/hellwarrior.py &
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export CUDA_VISIBLE_DEVICES=3&&python render.py --model_path "output/$exp_name1/hook/" --skip_train --configs arguments/$exp_name1/hook.py &
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export CUDA_VISIBLE_DEVICES=0&&python render.py --model_path "output/$exp_name1/hellwarrior/" --skip_train --configs arguments/$exp_name1/hellwarrior.py &
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export CUDA_VISIBLE_DEVICES=1&&python render.py --model_path "output/$exp_name1/hook/" --skip_train --configs arguments/$exp_name1/hook.py &
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export CUDA_VISIBLE_DEVICES=2&&python render.py --model_path "output/$exp_name1/trex/" --skip_train --configs arguments/$exp_name1/trex.py &
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export CUDA_VISIBLE_DEVICES=3&&python render.py --model_path "output/$exp_name1/mutant/" --skip_train --configs arguments/$exp_name1/mutant.py &
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# wait
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echo "Done"
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exp_name1=$1
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export CUDA_VISIBLE_DEVICES=2&&python metrics.py --model_path "output/$exp_name1/standup/" &
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export CUDA_VISIBLE_DEVICES=3&&python metrics.py --model_path "output/$exp_name1/jumpingjacks/" &
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export CUDA_VISIBLE_DEVICES=0&&python metrics.py --model_path "output/$exp_name1/standup/" &
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export CUDA_VISIBLE_DEVICES=1&&python metrics.py --model_path "output/$exp_name1/jumpingjacks/" &
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export CUDA_VISIBLE_DEVICES=2&&python metrics.py --model_path "output/$exp_name1/bouncingballs/" &
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export CUDA_VISIBLE_DEVICES=3&&python metrics.py --model_path "output/$exp_name1/lego/"
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export CUDA_VISIBLE_DEVICES=2&&python metrics.py --model_path "output/$exp_name1/hellwarrior/" &
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export CUDA_VISIBLE_DEVICES=3&&python metrics.py --model_path "output/$exp_name1/hook/" &
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export CUDA_VISIBLE_DEVICES=0&&python metrics.py --model_path "output/$exp_name1/hellwarrior/" &
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export CUDA_VISIBLE_DEVICES=1&&python metrics.py --model_path "output/$exp_name1/hook/" &
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export CUDA_VISIBLE_DEVICES=2&&python metrics.py --model_path "output/$exp_name1/trex/" &
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export CUDA_VISIBLE_DEVICES=3&&python metrics.py --model_path "output/$exp_name1/mutant/" &
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wait
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@ -1,8 +1,7 @@
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import json
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import os
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exp_name = ["dnerf_gridlarge","dnerf_gridsmall","dnerf_gridsmaller","dnerf_mlplarge","dnerf_mlplarger","dnerf_nocoarse","dnerf_silm","dnerf_imageloss",
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"dnerf_3dgs","dnerf_tv","dnerf_noboth","dnerf_nogrid"]
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scene_name = ["bouncingball","jumpingjack","lego","standup","hook","mutant","hellwarrior","trex"]
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exp_name = ["dnerf_tv_test"]
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scene_name = ["bouncingballs","jumpingjacks","lego","standup","hook","mutant","hellwarrior","trex"]
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json_name = "results.json"
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result_json = {"SSIM":0,"PSNR":0,"LPIPS":0}
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exp_json = {}
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