fix requirements.txt dependency

Author: NIRVANALAN

.gitmodules

@@ -1,3 +1,6 @@
 [submodule "third_party/diff-surfel-rasterization"]
 	path = third_party/diff-surfel-rasterization
-	url = git@github.com:hbb1/diff-surfel-rasterization.git
+	url = git@github.com:hbb1/diff-surfel-rasterization.git
+[submodule "third_party/simple-knn"]
+	path = third_party/simple-knn
+	url = https://gitlab.inria.fr/bkerbl/simple-knn.git

README.md

@@ -138,12 +138,23 @@ bash shell_scripts/final_release/inference/gradio_sample_obajverse_i23d_dit.sh
 
 # Inference
 
-## setup the environment (the same env as [LN3Diff, ECCV 2024](https://github.com/NIRVANALAN/LN3Diff?tab=readme-ov-file))
+## setup the PyTorch environment (the same env as [LN3Diff, ECCV 2024](https://github.com/NIRVANALAN/LN3Diff?tab=readme-ov-file))
 
 ```bash
+# download
+git clone https://github.com/hbb1/2d-gaussian-splatting.git --recursive
+
+# setup the pytorch+xformers+pytorch3d environment
 conda create -n ga python=3.10
 conda activate ga
-pip intall -r requrements.txt # will install the surfel Gaussians environments and pytorch3d automatically.
+pip install -r requirements.txt 
+pip install "git+https://github.com/facebookresearch/pytorch3d.git@stable"
+```
+
+Then, install the 2DGS dependencies:
+```bash
+pip install third_party/diff-surfel-rasterization
+pip install third_party/simple-knn
 ```
 
 ## Gradio demo (Image-to-3D)

datasets/g_buffer_objaverse.py

@@ -4733,10 +4733,10 @@ def __init__(
         if True: # instant-mesh picked images
         # if False:
             all_instances = os.listdir(self.file_path) 
-            # all_fname = [
-            #     t for t in all_instances
-            #     if t.split('.')[1] in ['png', 'jpg']
-            # ]
+            all_fname = [
+                t for t in all_instances
+                if t.split('.')[1] in ['png', 'jpg']
+            ]
 
             # all_fname = [name for name in all_fname if '-input' in name ]
 

nsr/cvD/nvsD_canoD.py

@@ -23,7 +23,7 @@
 from torch.optim import AdamW
 
 from ..train_util import TrainLoopBasic, TrainLoop3DRec
-import vision_aided_loss
+# import vision_aided_loss
 from dnnlib.util import calculate_adaptive_weight
 
 def flip_yaw(pose_matrix):

nsr/script_util.py

@@ -19,7 +19,7 @@
 from ldm.modules.diffusionmodules.mv_unet import MVUNet, LGM_MVEncoder
 from torch.profiler import profile, record_function, ProfilerActivity
 
-from nsr.gs import GaussianRenderer
+# from nsr.gs import GaussianRenderer
 from nsr.gs_surfel import GaussianRenderer2DGS
 # from nsr.srt.encoder import ImprovedSRTEncoderVAE, ImprovedSRTEncoderVAE_L5_vitl, ImprovedSRTEncoderVAE_mlp_ratio4, ImprovedSRTEncoderVAE_L6, ImprovedSRTEncoderVAE_mlp_ratio4_f8, ImprovedSRTEncoderVAE_mlp_ratio4_heavyPatchify, ImprovedSRTEncoderVAE_mlp_ratio4_f8_L6, ImprovedSRTEncoderVAE_mlp_ratio4_L6, HybridEncoder, ImprovedSRTEncoderVAE_mlp_ratio4_decomposed, HybridEncoderPCDStructuredLatent
 from nsr.srt.encoder import *
@@ -1481,8 +1481,10 @@ def create_3DAE_model(
             triplane_decoder = GaussianRenderer2DGS(
                 image_size, out_chans, rendering_kwargs=rendering_kwargs)
         else:
-            triplane_decoder = GaussianRenderer(
-                image_size, out_chans, rendering_kwargs=rendering_kwargs)
+            raise NotImplementedError()
+
+        #     triplane_decoder = GaussianRenderer(
+        #         image_size, out_chans, rendering_kwargs=rendering_kwargs)
 
         if load_pretrain_encoder:
 

nsr/train_util.py

@@ -9,7 +9,7 @@
 from pdb import set_trace as st
 
 import traceback
-from nsr.gs import GaussianRenderer
+# from nsr.gs import GaussianRenderer
 from nsr.gs_surfel import GaussianRenderer2DGS
 import blobfile as bf
 import imageio
@@ -880,9 +880,9 @@ def _init_optim_groups(self, kwargs):
 
             # gs rendering no MLP
             if not (
-            isinstance(
-                    self.mp_trainer_rec.model.decoder.triplane_decoder,
-                    GaussianRenderer) or 
+            # isinstance(
+            #         self.mp_trainer_rec.model.decoder.triplane_decoder,
+            #         GaussianRenderer) or 
             isinstance(
                     self.mp_trainer_rec.model.decoder.triplane_decoder,
                     GaussianRenderer2DGS)):

nsr/train_util_cvD.py

@@ -9,7 +9,6 @@
 import numpy as np
 import torch as th
 import torch.distributed as dist
-import torchvision
 from PIL import Image
 from torch.nn.parallel.distributed import DistributedDataParallel as DDP
 from tqdm import tqdm
@@ -23,7 +22,7 @@
 from torch.optim import AdamW
 
 from .train_util import TrainLoopBasic, TrainLoop3DRec
-import vision_aided_loss
+# import vision_aided_loss
 from dnnlib.util import calculate_adaptive_weight
 
 

requirements.txt

@@ -1,6 +1,6 @@
-torch
+torch==2.1.0
+torchvision==0.16.0
 xformers==0.0.26.post1
-torchvision
 absl-py
 tensorboard
 lpips
@@ -44,7 +44,4 @@ onnxscript
 tritonclient
 gradio==4.43.0
 rembg
-onnxruntime
-git+https://github.com/facebookresearch/pytorch3d.git@stable
-git+https://github.com/hbb1/diff-surfel-rasterization.git
-git+https://gitlab.inria.fr/bkerbl/simple-knn.git
+onnxruntime

vit/vit_triplane.py

@@ -58,7 +58,7 @@
 
 from utils.general_utils import matrix_to_quaternion, quaternion_raw_multiply, build_rotation
 
-from nsr.gs import GaussianRenderer
+# from nsr.gs import GaussianRenderer
 
 from utils.dust3r.heads import create_dpt_head