以下code 有沒有錯,或者,待優化之處?
#存储库克隆到你的 Google Colab Notebook
!git clone https://t.cn/A6NRWmuS
#进入 shap-e目录并安装依赖包：
%cd shap-e
!pip install -e .
#导入所有必需的库
import torch
from shap_e.diffusion.sample import sample_latents
from shap_e.diffusion.gaussian_diffusion import diffusion_from_config
from shap_e.models.download import load_model, load_config
from shap_e.util.notebooks import create_pan_cameras, decode_latent_images, gif_widget
#将设备设置为 cuda（如果可用），否则设置为 cpu。
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
#加载模型和权重。
xm = load_model('transmitter', device=device)
model = load_model('text300M', device=device)
diffusion = diffusion_from_config(load_config('diffusion'))
#在这里我们将生成 3D 模型。
batch_size = 1 # this is the size of the models, higher values take longer to generate.
guidance_scale = 15.0 # this is the scale of the guidance, higher values make the model look more like the prompt.
prompt = "A mystical sword with a slender, gleaming blade is adorned with intricate designs. It emits a soft glow illuminating the dark, starry cosmos that serves as its backdrop." # this is the prompt, you can change this to anything you want.
latents = sample_latents(
batch_size=batch_size,
model=model,
diffusion=diffusion,
guidance_scale=guidance_scale,
model_kwargs=dict(texts=[prompt] * batch_size),
progress=True,
clip_denoised=True,
use_fp16=True,
use_karras=True,
karras_steps=64,
sigma_min=1E-3,
sigma_max=160,
s_churn=0,
)
#渲染 3D 模型，使用 render_mode = 'nerf' 神经辐射场 (NeRF) 来渲染 3D 模型。 你可以将其更改为 render_mode = 'stf' 以使用风格传递函数 (STF) 渲染模式渲染 3D 模型。
render_mode = 'nerf' # you can change this to 'stf'
size = 64 # this is the size of the renders, higher values take longer to render.
cameras = create_pan_cameras(size, device)
for i, latent in enumerate(latents):
images = decode_latent_images(xm, latent, cameras, rendering_mode=render_mode)
display(gif_widget(images))
#将 3D 模型保存为 .ply 和 .obj 文件。注意： .obj，稍后我们将使用它在 Blender Studio 中进行自定义。
# Example of saving the latents as meshes.
from shap_e.util.notebooks import decode_latent_mesh
for i, latent in enumerate(latents):
t = decode_latent_mesh(xm, latent).tri_mesh()
with open(f'example_mesh_{i}.ply', 'wb') as f: # this is three-dimensional geometric data of model.
t.write_ply(f)
with open(f'example_mesh_{i}.obj', 'w') as f: # we will use this file to customize in Blender Studio later.
t.write_obj(f)
# Clone the repo.
!git clone https://t.cn/A6jX18IT
%cd /content/camp_zipnerf
# Make a conda environment.
!conda create --name camp_zipnerf python=3.11
!conda activate camp_zipnerf
# Prepare pip.
!conda install pip
!pip install --upgrade pip
# Install requirements.
!pip install -r requirements.txt
# Manually install rmbrualla's `pycolmap` (don't use pip's! It's different).
!git clone https://t.cn/A6jX18IH ./internal/pycolmap
# Confirm that all the unit tests pass.
!./scripts/run_all_unit_tests.sh
%cd /content
!git clone -b dev https://t.cn/A6jX0dU6
!git clone -b dev https://t.cn/A6jX0dUJ
%cd /content/threefiner
!pip install .
%cd /content/3DTopia
!apt -y install -qq aria2
!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://t.cn/A6jX0dUS -d /content/3DTopia/checkpoints -o 3dtopia_diffusion_state_dict.ckpt
!pip install -q pymcubes trimesh pytorch_lightning omegaconf einops wandb git+https://t.cn/A6qBislP kornia open-clip-torch
!pip install -q https://t.cn/A6jX0dUK
!pip install -q https://t.cn/A6jX0dUi
!pip install -q threefiner
# stage 2 - step 1
!threefiner sd --mesh results/default/stage1/example_mesh_0.ply --prompt "A mystical sword with a slender, gleaming blade is adorned with intricate designs. It emits a soft glow illuminating the dark, starry cosmos that serves as its backdrop." --text_dir --front_dir='-y' --outdir results/default/stage2/ --save A_mystical_sword_1_0_sd.glb --force_cuda_rast
# stage 2 - step 2
!threefiner if2 --mesh results/default/stage2/A_mystical_sword_1_0_sd.glb --prompt "A mystical sword with a slender, gleaming blade is adorned with intricate designs. It emits a soft glow illuminating the dark, starry cosmos that serves as its backdrop." --outdir results/default/stage2/ --save A_mystical_sword_1_0_if2.glb --force_cuda_rast
#存储库克隆到你的 Google Colab Notebook
!git clone https://t.cn/A6NRWmuS
#进入 shap-e目录并安装依赖包：
%cd shap-e
!pip install -e .
#导入所有必需的库
import torch
from shap_e.diffusion.sample import sample_latents
from shap_e.diffusion.gaussian_diffusion import diffusion_from_config
from shap_e.models.download import load_model, load_config
from shap_e.util.notebooks import create_pan_cameras, decode_latent_images, gif_widget
#将设备设置为 cuda（如果可用），否则设置为 cpu。
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
#加载模型和权重。
xm = load_model('transmitter', device=device)
model = load_model('text300M', device=device)
diffusion = diffusion_from_config(load_config('diffusion'))
#在这里我们将生成 3D 模型。
batch_size = 1 # this is the size of the models, higher values take longer to generate.
guidance_scale = 15.0 # this is the scale of the guidance, higher values make the model look more like the prompt.
prompt = "A mystical sword with a slender, gleaming blade is adorned with intricate designs. It emits a soft glow illuminating the dark, starry cosmos that serves as its backdrop." # this is the prompt, you can change this to anything you want.
latents = sample_latents(
batch_size=batch_size,
model=model,
diffusion=diffusion,
guidance_scale=guidance_scale,
model_kwargs=dict(texts=[prompt] * batch_size),
progress=True,
clip_denoised=True,
use_fp16=True,
use_karras=True,
karras_steps=64,
sigma_min=1E-3,
sigma_max=160,
s_churn=0,
)
#渲染 3D 模型，使用 render_mode = 'nerf' 神经辐射场 (NeRF) 来渲染 3D 模型。 你可以将其更改为 render_mode = 'stf' 以使用风格传递函数 (STF) 渲染模式渲染 3D 模型。
render_mode = 'nerf' # you can change this to 'stf'
size = 64 # this is the size of the renders, higher values take longer to render.
cameras = create_pan_cameras(size, device)
for i, latent in enumerate(latents):
images = decode_latent_images(xm, latent, cameras, rendering_mode=render_mode)
display(gif_widget(images))
#将 3D 模型保存为 .ply 和 .obj 文件。注意： .obj，稍后我们将使用它在 Blender Studio 中进行自定义。
# Example of saving the latents as meshes.
from shap_e.util.notebooks import decode_latent_mesh
for i, latent in enumerate(latents):
t = decode_latent_mesh(xm, latent).tri_mesh()
with open(f'example_mesh_{i}.ply', 'wb') as f: # this is three-dimensional geometric data of model.
t.write_ply(f)
with open(f'example_mesh_{i}.obj', 'w') as f: # we will use this file to customize in Blender Studio later.
t.write_obj(f)
# Clone the repo.
!git clone https://t.cn/A6jX18IT
%cd /content/camp_zipnerf
# Make a conda environment.
!conda create --name camp_zipnerf python=3.11
!conda activate camp_zipnerf
# Prepare pip.
!conda install pip
!pip install --upgrade pip
# Install requirements.
!pip install -r requirements.txt
# Manually install rmbrualla's `pycolmap` (don't use pip's! It's different).
!git clone https://t.cn/A6jX18IH ./internal/pycolmap
# Confirm that all the unit tests pass.
!./scripts/run_all_unit_tests.sh
%cd /content
!git clone -b dev https://t.cn/A6jX0dU6
!git clone -b dev https://t.cn/A6jX0dUJ
%cd /content/threefiner
!pip install .
%cd /content/3DTopia
!apt -y install -qq aria2
!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://t.cn/A6jX0dUS -d /content/3DTopia/checkpoints -o 3dtopia_diffusion_state_dict.ckpt
!pip install -q pymcubes trimesh pytorch_lightning omegaconf einops wandb git+https://t.cn/A6qBislP kornia open-clip-torch
!pip install -q https://t.cn/A6jX0dUK
!pip install -q https://t.cn/A6jX0dUi
!pip install -q threefiner
# stage 2 - step 1
!threefiner sd --mesh results/default/stage1/example_mesh_0.ply --prompt "A mystical sword with a slender, gleaming blade is adorned with intricate designs. It emits a soft glow illuminating the dark, starry cosmos that serves as its backdrop." --text_dir --front_dir='-y' --outdir results/default/stage2/ --save A_mystical_sword_1_0_sd.glb --force_cuda_rast
# stage 2 - step 2
!threefiner if2 --mesh results/default/stage2/A_mystical_sword_1_0_sd.glb --prompt "A mystical sword with a slender, gleaming blade is adorned with intricate designs. It emits a soft glow illuminating the dark, starry cosmos that serves as its backdrop." --outdir results/default/stage2/ --save A_mystical_sword_1_0_if2.glb --force_cuda_rast
ttps://github.com/3DTopia/3DTopia
ttps://github.com/camenduru/3DTopia-jupyter
stage 1 - step 1(T4跑不动,别用T4 run)
这个a_dragon_0_0.ply就是 24-1-16 16:33
text to 3D_shap-e.
https://t.cn/A6jX0dUM
---------------------
%cd /content
!git clone -b dev https://t.cn/A6jX0dU6
!git clone -b dev https://t.cn/A6jX0dUJ
%cd /content/threefiner
!pip install .
%cd /content/3DTopia
!apt -y install -qq aria2
!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://t.cn/A6jX0dUS -d /content/3DTopia/checkpoints -o 3dtopia_diffusion_state_dict.ckpt
!pip install -q pymcubes trimesh pytorch_lightning omegaconf einops wandb git+https://t.cn/A6qBislP kornia open-clip-torch
!pip install -q https://t.cn/A6jX0dUK
!pip install -q https://t.cn/A6jX0dUi
!pip install -q threefiner
# stage 2 - step 1
!threefiner sd --mesh results/default/stage1/a_dragon_0_0.ply --prompt "a dragon" --text_dir --front_dir='-y' --outdir results/default/stage2/ --save a_dragon_1_0_sd.glb --force_cuda_rast
ttps://github.com/camenduru/3DTopia-jupyter
stage 1 - step 1(T4跑不动,别用T4 run)
这个a_dragon_0_0.ply就是 24-1-16 16:33
text to 3D_shap-e.
https://t.cn/A6jX0dUM
---------------------
%cd /content
!git clone -b dev https://t.cn/A6jX0dU6
!git clone -b dev https://t.cn/A6jX0dUJ
%cd /content/threefiner
!pip install .
%cd /content/3DTopia
!apt -y install -qq aria2
!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://t.cn/A6jX0dUS -d /content/3DTopia/checkpoints -o 3dtopia_diffusion_state_dict.ckpt
!pip install -q pymcubes trimesh pytorch_lightning omegaconf einops wandb git+https://t.cn/A6qBislP kornia open-clip-torch
!pip install -q https://t.cn/A6jX0dUK
!pip install -q https://t.cn/A6jX0dUi
!pip install -q threefiner
# stage 2 - step 1
!threefiner sd --mesh results/default/stage1/a_dragon_0_0.ply --prompt "a dragon" --text_dir --front_dir='-y' --outdir results/default/stage2/ --save a_dragon_1_0_sd.glb --force_cuda_rast
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