adjust directory struct

app.py

@@ -19,9 +19,9 @@ from aiortc import RTCPeerConnection, RTCSessionDescription
 from webrtc import HumanPlayer
 
 import argparse
-from nerf_triplane.provider import NeRFDataset_Test
-from nerf_triplane.utils import *
-from nerf_triplane.network import NeRFNetwork
+from ernerf.nerf_triplane.provider import NeRFDataset_Test
+from ernerf.nerf_triplane.utils import *
+from ernerf.nerf_triplane.network import NeRFNetwork
 from nerfreal import NeRFReal
 
 import shutil

ernerf/encoding.py

@@ -13,23 +13,23 @@ def get_encoder(encoding, input_dim=3,
         return lambda x, **kwargs: x, input_dim
     
     elif encoding == 'frequency':
-        from freqencoder import FreqEncoder
+        from .freqencoder import FreqEncoder
         encoder = FreqEncoder(input_dim=input_dim, degree=multires)
 
     elif encoding == 'spherical_harmonics':
-        from shencoder import SHEncoder
+        from .shencoder import SHEncoder
         encoder = SHEncoder(input_dim=input_dim, degree=degree)
 
     elif encoding == 'hashgrid':
-        from gridencoder import GridEncoder
+        from .gridencoder import GridEncoder
         encoder = GridEncoder(input_dim=input_dim, num_levels=num_levels, level_dim=level_dim, base_resolution=base_resolution, log2_hashmap_size=log2_hashmap_size, desired_resolution=desired_resolution, gridtype='hash', align_corners=align_corners)
     
     elif encoding == 'tiledgrid':
-        from gridencoder import GridEncoder
+        from .gridencoder import GridEncoder
         encoder = GridEncoder(input_dim=input_dim, num_levels=num_levels, level_dim=level_dim, base_resolution=base_resolution, log2_hashmap_size=log2_hashmap_size, desired_resolution=desired_resolution, gridtype='tiled', align_corners=align_corners)
     
     elif encoding == 'ash':
-        from ashencoder import AshEncoder
+        from .ashencoder import AshEncoder
         encoder = AshEncoder(input_dim=input_dim, output_dim=16, log2_hashmap_size=log2_hashmap_size, resolution=desired_resolution)
 
     else:

ernerf/main.py

@@ -1,9 +1,9 @@
 import torch
 import argparse
 
-from nerf_triplane.provider import NeRFDataset,NeRFDataset_Test
-from nerf_triplane.utils import *
-from nerf_triplane.network import NeRFNetwork
+from .nerf_triplane.provider import NeRFDataset,NeRFDataset_Test
+from .nerf_triplane.utils import *
+from .nerf_triplane.network import NeRFNetwork
 
 # torch.autograd.set_detect_anomaly(True)
 # Close tf32 features. Fix low numerical accuracy on rtx30xx gpu.

ernerf/nerf_triplane/network.py

@@ -2,7 +2,7 @@ import torch
 import torch.nn as nn
 import torch.nn.functional as F
 
-from encoding import get_encoder
+from ..encoding import get_encoder
 from .renderer import NeRFRenderer
 
 # Audio feature extractor

ernerf/nerf_triplane/renderer.py

@@ -7,7 +7,7 @@ import torch
 import torch.nn as nn
 import torch.nn.functional as F
 
-import raymarching
+from .. import raymarching
 from .utils import custom_meshgrid, get_audio_features, euler_angles_to_matrix, convert_poses
 
 def sample_pdf(bins, weights, n_samples, det=False):

ernerf/workspace/log_ngp.txt

@@ -0,0 +1,14 @@
+[INFO] Trainer: ngp | 2023-09-23_17-52-22 | cuda | fp16 | workspace
+[INFO] #parameters: 1789121
+[INFO] Loading data/pretrained/ngp_kf.pth ...
+[INFO] Trainer: ngp | 2023-09-23_18-58-25 | cuda | fp16 | workspace
+[INFO] #parameters: 1789121
+[INFO] Loading data/pretrained/ngp_kf.pth ...
+[INFO] Trainer: ngp | 2023-09-23_19-01-54 | cuda | fp16 | workspace
+[INFO] #parameters: 1787681
+[INFO] Loading data/pretrained/ngp_kf.pth ...
+[INFO] loaded model.
+[INFO] load at epoch 14, global step 51226
+[WARN] Failed to load optimizer.
+[INFO] loaded scheduler.
+[INFO] loaded scaler.