python train.py --config configs/deblur_vm96.txt --datadir=./data/real_defocus_blur/defocustools --expname=test
Namespace(L1_weight_inital=0.0, L1_weight_rest=0, N_vis=-1, N_voxel_final_coarse=110592000, N_voxel_final_fine=110592000, N_voxel_init_coarse=614125, N_voxel_init_fine=614125, Ortho_weight=0.0, TV_weight_app=1.0, TV_weight_density
=1.0, accumulate_decay=0.998, add_timestamp=0, alpha_mask_thre=0.0001, basedir='./log', batch_size=4096, c2f=False, ckpt=None, config='configs/deblur_vm96.txt', data_dim_color=27, datadir='./data/real_defocus_blur/defocustools', d
ataset_name='llff', density_shift=-10, distance_scale=25, downsample_test=1.0, downsample_train=1.0, expname='test', export_mesh=0, fea2denseAct='relu', fea_pe=0, featureC=128, flex_thres=0.0, fmo='AIF', focus=3, focus_lambda=0, f
orce_noconv=False, grouping='depthQ', idx_view=0, importance=False, kernel_adaptation=False, kernel_coef=1.0, kernel_sigma=1.0, kernel_type='rand_GD', ksize=7, lindisp=False, lof=400, loss_acc=0, lr_basis=0.001, lr_center=0.0, lr_
crf=0.05, lr_decay_iters=-1, lr_decay_target_ratio=0.1, lr_init=0.02, lr_kernel=0.05, lr_kernel_decay_end=55000, lr_kernel_decay_start=45000, lr_kernel_decay_target_ratio=0.1, lr_upsample_reset=1, model_name='TensorVMSplit', nSamp
les_coarse=64, nSamples_fine=64, n_iters=25000, n_lamb_sh=[64, 14, 14], n_lamb_sigma=[24, 6, 6], ndc_ray=1, pad_mode='full', patch_batch=64, patch_size=8, patch_start_iter=0, perturb=1.0, pick=-1, pos_pe=6, progress_refresh_rate=1
0, q_lambda=0.0, q_range=0, reg_lambda=0.0, render_only=0, render_path=0, render_test=1, render_train=0, rm_weight_mask_thre=0.0001, sample_mode='per_scene_patch', sample_perturb=False, shadingMode='MLP_Fea', step_ratio=0.5, tag='
64*4_strong', tone_mapping=-1, top_off=100, tv_decay_end=25000, tv_decay_start=0, tv_decay_target_ratio=0.1, update_AlphaMask_list=[2000], upsamp_list=[2000, 3000, 4000, 5500], view_pe=0, vis_every=5000, white_bkgd=False, with_dep
th=False)
C:\ProgramData\Anaconda3\envs\NF1\lib\site-packages\torch\functional.py:507: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at C:\cb\pytorch_1000000000
000\work\aten\src\ATen\native\TensorShape.cpp:3550.)
return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined]
torch.Size([8400000, 3]) torch.Size([8400000, 6]) train
Traceback (most recent call last):
File "train.py", line 419, in
reconstruction(args)
File "train.py", line 92, in reconstruction
train_dataset = dataset(args.datadir, split='train', downsample=args.downsample_train, is_stack=False, lof=args.lof, focus=args.focus, datatype=datatype, grouping=args.grouping, aabb=aabb, fmo=args.fmo, tag=args.tag, valid_lof
=args.lof-args.top_off, patch_size=args.patch_size, pad=args.ksize//2, patch_batch=args.patch_batch)
File "E:\DTH2025\SharpNeRF-main\dataLoader\llff.py", line 168, in init
self.read_focus(grouping, fmo, tag=tag, lof=lof)
File "E:\DTH2025\SharpNeRF-main\dataLoader\llff.py", line 226, in read_focus
focus_map = torch.from_numpy(np.load(self.focus_path)) # (N, H, W) or (N, H, W, 3)
File "C:\ProgramData\Anaconda3\envs\NF1\lib\site-packages\numpy\lib\npyio.py", line 405, in load
fid = stack.enter_context(open(os_fspath(file), "rb"))
FileNotFoundError: [Errno 2] No such file or directory: './data/real_defocus_blur/defocustools\focus_map_AIF_3.npy'
Hello, I encountered the following problem while using the pre calculated file you provided for training, and I was unable to calculate the focus map when using the pre trained weights (dmenetpre trained. npz) myself. May I ask how to solve it
python train.py --config configs/deblur_vm96.txt --datadir=./data/real_defocus_blur/defocustools --expname=test
Namespace(L1_weight_inital=0.0, L1_weight_rest=0, N_vis=-1, N_voxel_final_coarse=110592000, N_voxel_final_fine=110592000, N_voxel_init_coarse=614125, N_voxel_init_fine=614125, Ortho_weight=0.0, TV_weight_app=1.0, TV_weight_density
=1.0, accumulate_decay=0.998, add_timestamp=0, alpha_mask_thre=0.0001, basedir='./log', batch_size=4096, c2f=False, ckpt=None, config='configs/deblur_vm96.txt', data_dim_color=27, datadir='./data/real_defocus_blur/defocustools', d
ataset_name='llff', density_shift=-10, distance_scale=25, downsample_test=1.0, downsample_train=1.0, expname='test', export_mesh=0, fea2denseAct='relu', fea_pe=0, featureC=128, flex_thres=0.0, fmo='AIF', focus=3, focus_lambda=0, f
orce_noconv=False, grouping='depthQ', idx_view=0, importance=False, kernel_adaptation=False, kernel_coef=1.0, kernel_sigma=1.0, kernel_type='rand_GD', ksize=7, lindisp=False, lof=400, loss_acc=0, lr_basis=0.001, lr_center=0.0, lr_
crf=0.05, lr_decay_iters=-1, lr_decay_target_ratio=0.1, lr_init=0.02, lr_kernel=0.05, lr_kernel_decay_end=55000, lr_kernel_decay_start=45000, lr_kernel_decay_target_ratio=0.1, lr_upsample_reset=1, model_name='TensorVMSplit', nSamp
les_coarse=64, nSamples_fine=64, n_iters=25000, n_lamb_sh=[64, 14, 14], n_lamb_sigma=[24, 6, 6], ndc_ray=1, pad_mode='full', patch_batch=64, patch_size=8, patch_start_iter=0, perturb=1.0, pick=-1, pos_pe=6, progress_refresh_rate=1
0, q_lambda=0.0, q_range=0, reg_lambda=0.0, render_only=0, render_path=0, render_test=1, render_train=0, rm_weight_mask_thre=0.0001, sample_mode='per_scene_patch', sample_perturb=False, shadingMode='MLP_Fea', step_ratio=0.5, tag='
64*4_strong', tone_mapping=-1, top_off=100, tv_decay_end=25000, tv_decay_start=0, tv_decay_target_ratio=0.1, update_AlphaMask_list=[2000], upsamp_list=[2000, 3000, 4000, 5500], view_pe=0, vis_every=5000, white_bkgd=False, with_dep
th=False)
C:\ProgramData\Anaconda3\envs\NF1\lib\site-packages\torch\functional.py:507: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at C:\cb\pytorch_1000000000
000\work\aten\src\ATen\native\TensorShape.cpp:3550.)
return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined]
torch.Size([8400000, 3]) torch.Size([8400000, 6]) train
Traceback (most recent call last):
File "train.py", line 419, in
reconstruction(args)
File "train.py", line 92, in reconstruction
train_dataset = dataset(args.datadir, split='train', downsample=args.downsample_train, is_stack=False, lof=args.lof, focus=args.focus, datatype=datatype, grouping=args.grouping, aabb=aabb, fmo=args.fmo, tag=args.tag, valid_lof
=args.lof-args.top_off, patch_size=args.patch_size, pad=args.ksize//2, patch_batch=args.patch_batch)
File "E:\DTH2025\SharpNeRF-main\dataLoader\llff.py", line 168, in init
self.read_focus(grouping, fmo, tag=tag, lof=lof)
File "E:\DTH2025\SharpNeRF-main\dataLoader\llff.py", line 226, in read_focus
focus_map = torch.from_numpy(np.load(self.focus_path)) # (N, H, W) or (N, H, W, 3)
File "C:\ProgramData\Anaconda3\envs\NF1\lib\site-packages\numpy\lib\npyio.py", line 405, in load
fid = stack.enter_context(open(os_fspath(file), "rb"))
FileNotFoundError: [Errno 2] No such file or directory: './data/real_defocus_blur/defocustools\focus_map_AIF_3.npy'
Hello, I encountered the following problem while using the pre calculated file you provided for training, and I was unable to calculate the focus map when using the pre trained weights (dmenetpre trained. npz) myself. May I ask how to solve it