HongFangzhou commited on
Commit
699ffc9
1 Parent(s): 8ee45cc

should work now

Browse files
Files changed (2) hide show
  1. app.py +10 -3
  2. requirements.txt +6 -6
app.py CHANGED
@@ -2,9 +2,7 @@ import os
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  import sys
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  import cv2
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  import time
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- import tyro
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  import json
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- import kiui
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  import tqdm
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  import torch
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  import mcubes
@@ -22,6 +20,13 @@ from huggingface_hub import hf_hub_download
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  sys.path.append("3DTopia")
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  from ldm.models.diffusion.ddim import DDIMSampler
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  from ldm.models.diffusion.plms import PLMSSampler
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  from ldm.models.diffusion.dpm_solver import DPMSolverSampler
@@ -110,6 +115,7 @@ opt.save = GRADIO_SAVE_PATH_MESH
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  opt.prompt = ''
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  opt.text_dir = True
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  opt.front_dir = '+z'
 
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  device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
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  gui = GUI(opt)
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  ###################################### INIT STAGE 2 #########################################
@@ -135,7 +141,7 @@ def add_text(rgb, caption):
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  def marching_cube(b, text, global_info):
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  # prepare volumn for marching cube
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- res = 128
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  assert 'decode_res' in global_info
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  decode_res = global_info['decode_res']
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  c_list = torch.linspace(-1.2, 1.2, steps=res)
@@ -358,6 +364,7 @@ def process_stage2(input_model, input_text, input_dir, iters, output_model, outp
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  markdown=f'''
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  # 3DTopia
 
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  A two-stage text-to-3D generation model. The first stage uses diffusion model to quickly generate candidates. The second stage refines the assets chosen from the first stage.
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  ### Usage:
 
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  import sys
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  import cv2
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  import time
 
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  import json
 
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  import tqdm
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  import torch
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  import mcubes
 
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  sys.path.append("3DTopia")
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+ os.system("pip install git+https://github.com/NVlabs/tiny-cuda-nn/#subdirectory=bindings/torch")
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+ os.system("pip install git+https://github.com/NVlabs/nvdiffrast")
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+ os.system("pip install git+https://github.com/3DTopia/threefiner")
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+
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+ import tyro
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+ import kiui
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+
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  from ldm.models.diffusion.ddim import DDIMSampler
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  from ldm.models.diffusion.plms import PLMSSampler
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  from ldm.models.diffusion.dpm_solver import DPMSolverSampler
 
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  opt.prompt = ''
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  opt.text_dir = True
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  opt.front_dir = '+z'
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+ opt.force_cuda_rast = True
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  device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
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  gui = GUI(opt)
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  ###################################### INIT STAGE 2 #########################################
 
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  def marching_cube(b, text, global_info):
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  # prepare volumn for marching cube
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+ res = 64
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  assert 'decode_res' in global_info
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  decode_res = global_info['decode_res']
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  c_list = torch.linspace(-1.2, 1.2, steps=res)
 
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  markdown=f'''
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  # 3DTopia
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+ ![](https://visitor-badge.laobi.icu/badge?page_id=3DTopia.3DTopia.gradio)
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  A two-stage text-to-3D generation model. The first stage uses diffusion model to quickly generate candidates. The second stage refines the assets chosen from the first stage.
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  ### Usage:
requirements.txt CHANGED
@@ -1,6 +1,7 @@
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- torch
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- torchvision
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- torchaudio
 
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  pytorch-lightning
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  numpy
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  tqdm
@@ -55,6 +56,5 @@ vit-pytorch
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  wandb
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  wcwidth
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  zipp
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- git+https://github.com/NVlabs/tiny-cuda-nn/#subdirectory=bindings/torch
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- git+https://github.com/NVlabs/nvdiffrast
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- git+https://github.com/3DTopia/threefiner
 
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+ torch==1.13.1+cu117
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+ torchvision==0.14.1+cu117
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+ torchaudio==0.13.1
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+ --extra-index-url https://download.pytorch.org/whl/cu117
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  pytorch-lightning
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  numpy
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  tqdm
 
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  wandb
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  wcwidth
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  zipp
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+ kiui
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+ accelerate