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ComfyUI-Hunyuan3DWrapper/nodes.py
kijai a8f03c7b0a Add Hy3DRenderSingleView -node
2025-01-26 17:02:29 +02:00

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import os
import torch
import torchvision.transforms as transforms
from PIL import Image
from pathlib import Path
import numpy as np
import trimesh
from .hy3dgen.shapegen import Hunyuan3DDiTFlowMatchingPipeline, FaceReducer, FloaterRemover, DegenerateFaceRemover
import folder_paths
import comfy.model_management as mm
from comfy.utils import load_torch_file, ProgressBar
script_directory = os.path.dirname(os.path.abspath(__file__))
from .utils import log, print_memory
class ComfyProgressCallback:
def __init__(self, total_steps):
self.pbar = ProgressBar(total_steps)
def __call__(self, pipe, i, t, callback_kwargs):
self.pbar.update(1)
return {
"latents": callback_kwargs["latents"],
"prompt_embeds": callback_kwargs["prompt_embeds"],
"negative_prompt_embeds": callback_kwargs["negative_prompt_embeds"]
}
class Hy3DTorchCompileSettings:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"backend": (["inductor","cudagraphs"], {"default": "inductor"}),
"fullgraph": ("BOOLEAN", {"default": False, "tooltip": "Enable full graph mode"}),
"mode": (["default", "max-autotune", "max-autotune-no-cudagraphs", "reduce-overhead"], {"default": "default"}),
"dynamic": ("BOOLEAN", {"default": False, "tooltip": "Enable dynamic mode"}),
"dynamo_cache_size_limit": ("INT", {"default": 64, "min": 0, "max": 1024, "step": 1, "tooltip": "torch._dynamo.config.cache_size_limit"}),
"compile_transformer": ("BOOLEAN", {"default": True, "tooltip": "Compile single blocks"}),
"compile_vae": ("BOOLEAN", {"default": True, "tooltip": "Compile double blocks"}),
},
}
RETURN_TYPES = ("HY3DCOMPILEARGS",)
RETURN_NAMES = ("torch_compile_args",)
FUNCTION = "loadmodel"
CATEGORY = "HunyuanVideoWrapper"
DESCRIPTION = "torch.compile settings, when connected to the model loader, torch.compile of the selected layers is attempted. Requires Triton and torch 2.5.0 is recommended"
def loadmodel(self, backend, fullgraph, mode, dynamic, dynamo_cache_size_limit, compile_transformer, compile_vae):
compile_args = {
"backend": backend,
"fullgraph": fullgraph,
"mode": mode,
"dynamic": dynamic,
"dynamo_cache_size_limit": dynamo_cache_size_limit,
"compile_transformer": compile_transformer,
"compile_vae": compile_vae,
}
return (compile_args, )
#region Model loading
class Hy3DModelLoader:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"model": (folder_paths.get_filename_list("diffusion_models"), {"tooltip": "These models are loaded from the 'ComfyUI/models/diffusion_models' -folder",}),
},
"optional": {
"compile_args": ("HY3DCOMPILEARGS", {"tooltip": "torch.compile settings, when connected to the model loader, torch.compile of the selected models is attempted. Requires Triton and torch 2.5.0 is recommended"}),
"attention_mode": (["sdpa", "sageattn"], {"default": "sdpa"}),
}
}
RETURN_TYPES = ("HY3DMODEL", "HY3DVAE")
RETURN_NAMES = ("pipeline", "vae")
FUNCTION = "loadmodel"
CATEGORY = "Hunyuan3DWrapper"
def loadmodel(self, model, compile_args=None, attention_mode="sdpa"):
device = mm.get_torch_device()
offload_device=mm.unet_offload_device()
config_path = os.path.join(script_directory, "configs", "dit_config.yaml")
model_path = folder_paths.get_full_path("diffusion_models", model)
pipe, vae = Hunyuan3DDiTFlowMatchingPipeline.from_single_file(
ckpt_path=model_path,
config_path=config_path,
use_safetensors=True,
device=device,
offload_device=offload_device,
compile_args=compile_args,
attention_mode=attention_mode)
return (pipe, vae,)
class DownloadAndLoadHy3DDelightModel:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"model": (["hunyuan3d-delight-v2-0"],),
},
}
RETURN_TYPES = ("DELIGHTMODEL",)
RETURN_NAMES = ("delight_pipe", )
FUNCTION = "loadmodel"
CATEGORY = "Hunyuan3DWrapper"
def loadmodel(self, model):
device = mm.get_torch_device()
offload_device = mm.unet_offload_device()
download_path = os.path.join(folder_paths.models_dir,"diffusers")
model_path = os.path.join(download_path, model)
if not os.path.exists(model_path):
log.info(f"Downloading model to: {model_path}")
from huggingface_hub import snapshot_download
snapshot_download(
repo_id="tencent/Hunyuan3D-2",
allow_patterns=["*hunyuan3d-delight-v2-0*"],
local_dir=download_path,
local_dir_use_symlinks=False,
)
from diffusers import StableDiffusionInstructPix2PixPipeline, EulerAncestralDiscreteScheduler
delight_pipe = StableDiffusionInstructPix2PixPipeline.from_pretrained(
model_path,
torch_dtype=torch.float16,
safety_checker=None,
)
delight_pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(delight_pipe.scheduler.config)
delight_pipe = delight_pipe.to(device, torch.float16)
delight_pipe.enable_model_cpu_offload()
return (delight_pipe,)
class Hy3DDelightImage:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"delight_pipe": ("DELIGHTMODEL",),
"image": ("IMAGE", ),
"steps": ("INT", {"default": 50, "min": 1}),
"width": ("INT", {"default": 512, "min": 64, "max": 4096, "step": 16}),
"height": ("INT", {"default": 512, "min": 64, "max": 4096, "step": 16}),
"cfg_image": ("FLOAT", {"default": 1.5, "min": 0.0, "max": 100.0, "step": 0.01}),
"cfg_text": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 100.0, "step": 0.01}),
"seed": ("INT", {"default": 42, "min": 0, "max": 0xffffffffffffffff}),
}
}
RETURN_TYPES = ("IMAGE",)
RETURN_NAMES = ("image",)
FUNCTION = "process"
CATEGORY = "Hunyuan3DWrapper"
def process(self, delight_pipe, image, width, height, cfg_image, cfg_text, steps, seed):
device = mm.get_torch_device()
offload_device = mm.unet_offload_device()
image = image.permute(0, 3, 1, 2).to(device)
image = delight_pipe(
prompt="",
image=image,
generator=torch.manual_seed(seed),
height=height,
width=width,
num_inference_steps=steps,
image_guidance_scale=cfg_image,
guidance_scale=cfg_text,
output_type="pt",
).images[0]
out_tensor = image.unsqueeze(0).permute(0, 2, 3, 1).cpu().float()
return (out_tensor, )
class DownloadAndLoadHy3DPaintModel:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"model": (["hunyuan3d-paint-v2-0"],),
},
}
RETURN_TYPES = ("HY3DPAINTMODEL",)
RETURN_NAMES = ("multiview_pipe", )
FUNCTION = "loadmodel"
CATEGORY = "Hunyuan3DWrapper"
def loadmodel(self, model):
device = mm.get_torch_device()
offload_device = mm.unet_offload_device()
download_path = os.path.join(folder_paths.models_dir,"diffusers")
model_path = os.path.join(download_path, model)
if not os.path.exists(model_path):
log.info(f"Downloading model to: {model_path}")
from huggingface_hub import snapshot_download
snapshot_download(
repo_id="tencent/Hunyuan3D-2",
allow_patterns=[f"*{model}*"],
local_dir=download_path,
local_dir_use_symlinks=False,
)
from diffusers import DiffusionPipeline, EulerAncestralDiscreteScheduler
custom_pipeline_path = os.path.join(script_directory, 'hy3dgen', 'texgen', 'hunyuanpaint')
pipeline = DiffusionPipeline.from_pretrained(
model_path,
custom_pipeline=custom_pipeline_path,
torch_dtype=torch.float16)
pipeline.scheduler = EulerAncestralDiscreteScheduler.from_config(pipeline.scheduler.config, timestep_spacing='trailing')
pipeline.enable_model_cpu_offload()
return (pipeline,)
#region Texture
class Hy3DCameraConfig:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"camera_azimuths": ("STRING", {"default": "0, 90, 180, 270, 0, 180", "multiline": False}),
"camera_elevations": ("STRING", {"default": "0, 0, 0, 0, 90, -90", "multiline": False}),
"view_weights": ("STRING", {"default": "1, 0.1, 0.5, 0.1, 0.05, 0.05", "multiline": False}),
"camera_distance": ("FLOAT", {"default": 1.45, "min": 0.1, "max": 10.0, "step": 0.001}),
"ortho_scale": ("FLOAT", {"default": 1.2, "min": 0.1, "max": 10.0, "step": 0.001}),
},
}
RETURN_TYPES = ("HY3DCAMERA",)
RETURN_NAMES = ("camera_config",)
FUNCTION = "process"
CATEGORY = "Hunyuan3DWrapper"
def process(self, camera_azimuths, camera_elevations, view_weights, camera_distance, ortho_scale):
angles_list = list(map(int, camera_azimuths.replace(" ", "").split(',')))
elevations_list = list(map(int, camera_elevations.replace(" ", "").split(',')))
weights_list = list(map(float, view_weights.replace(" ", "").split(',')))
camera_config = {
"selected_camera_azims": angles_list,
"selected_camera_elevs": elevations_list,
"selected_view_weights": weights_list,
"camera_distance": camera_distance,
"ortho_scale": ortho_scale,
}
return (camera_config,)
class Hy3DMeshUVWrap:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"mesh": ("HY3DMESH",),
},
}
RETURN_TYPES = ("HY3DMESH", )
RETURN_NAMES = ("mesh", )
FUNCTION = "process"
CATEGORY = "Hunyuan3DWrapper"
def process(self, mesh):
from .hy3dgen.texgen.utils.uv_warp_utils import mesh_uv_wrap
mesh = mesh_uv_wrap(mesh)
return (mesh,)
class Hy3DRenderMultiView:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"mesh": ("HY3DMESH",),
"render_size": ("INT", {"default": 1024, "min": 64, "max": 4096, "step": 16}),
"texture_size": ("INT", {"default": 1024, "min": 64, "max": 4096, "step": 16}),
},
"optional": {
"camera_config": ("HY3DCAMERA",),
}
}
RETURN_TYPES = ("IMAGE", "IMAGE", "MESHRENDER")
RETURN_NAMES = ("normal_maps", "position_maps", "renderer")
FUNCTION = "process"
CATEGORY = "Hunyuan3DWrapper"
def process(self, mesh, render_size, texture_size, camera_config=None):
from .hy3dgen.texgen.differentiable_renderer.mesh_render import MeshRender
if camera_config is None:
selected_camera_azims = [0, 90, 180, 270, 0, 180]
selected_camera_elevs = [0, 0, 0, 0, 90, -90]
camera_distance = 1.45
ortho_scale = 1.2
else:
selected_camera_azims = camera_config["selected_camera_azims"]
selected_camera_elevs = camera_config["selected_camera_elevs"]
camera_distance = camera_config["camera_distance"]
ortho_scale = camera_config["ortho_scale"]
self.render = MeshRender(
default_resolution=render_size,
texture_size=texture_size,
camera_distance=camera_distance,
ortho_scale=ortho_scale)
self.render.load_mesh(mesh)
normal_maps = self.render_normal_multiview(
selected_camera_elevs, selected_camera_azims, use_abs_coor=True)
normal_tensors = torch.stack(normal_maps, dim=0)
position_maps = self.render_position_multiview(
selected_camera_elevs, selected_camera_azims)
position_tensors = torch.stack(position_maps, dim=0)
return (normal_tensors, position_tensors, self.render,)
def render_normal_multiview(self, camera_elevs, camera_azims, use_abs_coor=True):
normal_maps = []
for elev, azim in zip(camera_elevs, camera_azims):
normal_map, _ = self.render.render_normal(
elev, azim, use_abs_coor=use_abs_coor, return_type='th')
normal_maps.append(normal_map)
return normal_maps
def render_position_multiview(self, camera_elevs, camera_azims):
position_maps = []
for elev, azim in zip(camera_elevs, camera_azims):
position_map = self.render.render_position(
elev, azim, return_type='th')
position_maps.append(position_map)
return position_maps
class Hy3DRenderSingleView:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"mesh": ("HY3DMESH",),
"render_type": (["normal", "depth"], {"default": "normal"}),
"render_size": ("INT", {"default": 1024, "min": 64, "max": 4096, "step": 16}),
"camera_type": (["orth", "perspective"], {"default": "orth"}),
"camera_distance": ("FLOAT", {"default": 1.45, "min": 0.1, "max": 10.0, "step": 0.001}),
"pan_x": ("FLOAT", {"default": 0.0, "min": -1.0, "max": 1.0, "step": 0.01}),
"pan_y": ("FLOAT", {"default": 0.0, "min": -1.0, "max": 1.0, "step": 0.01}),
"ortho_scale": ("FLOAT", {"default": 1.2, "min": 0.1, "max": 10.0, "step": 0.001}),
"azimuth": ("FLOAT", {"default": 0, "min": -360, "max": 360, "step": 1}),
"elevation": ("FLOAT", {"default": 0, "min": -360, "max": 360, "step": 1}),
"bg_color": ("STRING", {"default": "0, 0, 0", "tooltip": "Color as RGB values in range 0-255, separated by commas."}),
},
}
RETURN_TYPES = ("IMAGE",)
RETURN_NAMES = ("image", )
FUNCTION = "process"
CATEGORY = "Hunyuan3DWrapper"
def process(self, mesh, render_type, camera_type, ortho_scale, camera_distance, pan_x, pan_y, render_size, azimuth, elevation, bg_color):
from .hy3dgen.texgen.differentiable_renderer.mesh_render import MeshRender
bg_color = [int(x.strip())/255.0 for x in bg_color.split(",")]
self.render = MeshRender(
default_resolution=render_size,
texture_size=1024,
camera_distance=camera_distance,
camera_type=camera_type,
ortho_scale=ortho_scale,
filter_mode='linear'
)
self.render.load_mesh(mesh)
if render_type == "normal":
normals, mask = self.render.render_normal(
elevation,
azimuth,
camera_distance=camera_distance,
center=None,
resolution=render_size,
bg_color=[0, 0, 0],
use_abs_coor=False,
pan_x=pan_x,
pan_y=pan_y
)
normals = 2.0 * normals - 1.0 # Map [0,1] to [-1,1]
normals = normals / (torch.norm(normals, dim=-1, keepdim=True) + 1e-6)
# Remap axes for standard normal map convention
image = torch.zeros_like(normals)
image[..., 0] = normals[..., 0] # View right to R
image[..., 1] = normals[..., 1] # View up to G
image[..., 2] = -normals[..., 2] # View forward (negated) to B
image = (image + 1) * 0.5
#mask = mask.cpu().float()
masked_image = image * mask
bg_color = torch.tensor(bg_color, dtype=torch.float32, device=image.device)
bg = bg_color.view(1, 1, 3) * (1.0 - mask)
final_image = masked_image + bg
elif render_type == "depth":
depth = self.render.render_depth(
elevation,
azimuth,
camera_distance=camera_distance,
center=None,
resolution=render_size,
pan_x=pan_x,
pan_y=pan_y
)
final_image = depth.unsqueeze(0).repeat(1, 1, 1, 3).cpu().float()
return (final_image,)
def render_normal_multiview(self, camera_elevs, camera_azims, use_abs_coor=True):
normal_maps = []
for elev, azim in zip(camera_elevs, camera_azims):
normal_map, _ = self.render.render_normal(
elev, azim, use_abs_coor=use_abs_coor, return_type='th')
normal_maps.append(normal_map)
return normal_maps
def render_position_multiview(self, camera_elevs, camera_azims):
position_maps = []
for elev, azim in zip(camera_elevs, camera_azims):
position_map = self.render.render_position(
elev, azim, return_type='th')
position_maps.append(position_map)
return position_maps
class Hy3DRenderMultiViewDepth:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"mesh": ("HY3DMESH",),
"render_size": ("INT", {"default": 1024, "min": 64, "max": 4096, "step": 16}),
"texture_size": ("INT", {"default": 1024, "min": 64, "max": 4096, "step": 16}),
},
"optional": {
"camera_config": ("HY3DCAMERA",),
}
}
RETURN_TYPES = ("IMAGE", )
RETURN_NAMES = ("depth_maps", )
FUNCTION = "process"
CATEGORY = "Hunyuan3DWrapper"
def process(self, mesh, render_size, texture_size, camera_config=None):
from .hy3dgen.texgen.differentiable_renderer.mesh_render import MeshRender
if camera_config is None:
selected_camera_azims = [0, 90, 180, 270, 0, 180]
selected_camera_elevs = [0, 0, 0, 0, 90, -90]
camera_distance = 1.45
ortho_scale = 1.2
else:
selected_camera_azims = camera_config["selected_camera_azims"]
selected_camera_elevs = camera_config["selected_camera_elevs"]
camera_distance = camera_config["camera_distance"]
ortho_scale = camera_config["ortho_scale"]
self.render = MeshRender(
default_resolution=render_size,
texture_size=texture_size,
camera_distance=camera_distance,
ortho_scale=ortho_scale)
self.render.load_mesh(mesh)
depth_maps = self.render_depth_multiview(
selected_camera_elevs, selected_camera_azims)
depth_tensors = torch.stack(depth_maps, dim=0)
depth_tensors = depth_tensors.repeat(1, 1, 1, 3)
return (depth_tensors,)
def render_depth_multiview(self, camera_elevs, camera_azims):
depth_maps = []
for elev, azim in zip(camera_elevs, camera_azims):
depth_map = self.render.render_depth(elev, azim, return_type='th')
depth_maps.append(depth_map)
return depth_maps
class Hy3DSampleMultiView:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"pipeline": ("HY3DPAINTMODEL",),
"ref_image": ("IMAGE", ),
"normal_maps": ("IMAGE", ),
"position_maps": ("IMAGE", ),
"view_size": ("INT", {"default": 512, "min": 64, "max": 4096, "step": 16}),
"steps": ("INT", {"default": 30, "min": 1}),
"seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff}),
},
"optional": {
"camera_config": ("HY3DCAMERA",),
}
}
RETURN_TYPES = ("IMAGE",)
RETURN_NAMES = ("image",)
FUNCTION = "process"
CATEGORY = "Hunyuan3DWrapper"
def process(self, pipeline, ref_image, normal_maps, position_maps, view_size, seed, steps, camera_config=None):
device = mm.get_torch_device()
mm.soft_empty_cache()
torch.manual_seed(seed)
generator=torch.Generator(device=pipeline.device).manual_seed(seed)
input_image = ref_image.permute(0, 3, 1, 2).unsqueeze(0).to(device)
device = mm.get_torch_device()
if camera_config is None:
selected_camera_azims = [0, 90, 180, 270, 0, 180]
selected_camera_elevs = [0, 0, 0, 0, 90, -90]
else:
selected_camera_azims = camera_config["selected_camera_azims"]
selected_camera_elevs = camera_config["selected_camera_elevs"]
camera_info = [(((azim // 30) + 9) % 12) // {-90: 3, -45: 2, -20: 1, 0: 1, 20: 1, 45: 2, 90: 3}[
elev] + {-90: 36, -45: 30, -20: 0, 0: 12, 20: 24, 45: 30, 90: 40}[elev] for azim, elev in
zip(selected_camera_azims, selected_camera_elevs)]
print(camera_info)
normal_maps_np = (normal_maps * 255).to(torch.uint8).cpu().numpy()
normal_maps_pil = [Image.fromarray(normal_map) for normal_map in normal_maps_np]
position_maps_np = (position_maps * 255).to(torch.uint8).cpu().numpy()
position_maps_pil = [Image.fromarray(position_map) for position_map in position_maps_np]
control_images = normal_maps_pil + position_maps_pil
for i in range(len(control_images)):
control_images[i] = control_images[i].resize((view_size, view_size))
if control_images[i].mode == 'L':
control_images[i] = control_images[i].point(lambda x: 255 if x > 1 else 0, mode='1')
num_view = len(control_images) // 2
normal_image = [[control_images[i] for i in range(num_view)]]
position_image = [[control_images[i + num_view] for i in range(num_view)]]
callback = ComfyProgressCallback(total_steps=steps)
multiview_images = pipeline(
input_image,
width=view_size,
height=view_size,
generator=generator,
num_in_batch = num_view,
camera_info_gen = [camera_info],
camera_info_ref = [[0]],
normal_imgs = normal_image,
position_imgs = position_image,
num_inference_steps=steps,
output_type="pt",
callback_on_step_end=callback,
callback_on_step_end_tensor_inputs=["latents", "prompt_embeds", "negative_prompt_embeds"]
).images
out_tensors = multiview_images.permute(0, 2, 3, 1).cpu().float()
return (out_tensors,)
class Hy3DBakeFromMultiview:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"images": ("IMAGE", ),
"renderer": ("MESHRENDER",),
},
"optional": {
"camera_config": ("HY3DCAMERA",),
}
}
RETURN_TYPES = ("IMAGE", "MASK", "MESHRENDER")
RETURN_NAMES = ("texture", "mask", "renderer")
FUNCTION = "process"
CATEGORY = "Hunyuan3DWrapper"
def process(self, images, renderer, camera_config=None):
device = mm.get_torch_device()
self.render = renderer
multiviews = images.permute(0, 3, 1, 2)
multiviews = multiviews.cpu().numpy()
multiviews_pil = [Image.fromarray((image.transpose(1, 2, 0) * 255).astype(np.uint8)) for image in multiviews]
if camera_config is None:
selected_camera_azims = [0, 90, 180, 270, 0, 180]
selected_camera_elevs = [0, 0, 0, 0, 90, -90]
selected_view_weights = [1, 0.1, 0.5, 0.1, 0.05, 0.05]
else:
selected_camera_azims = camera_config["selected_camera_azims"]
selected_camera_elevs = camera_config["selected_camera_elevs"]
selected_view_weights = camera_config["selected_view_weights"]
merge_method = 'fast'
self.bake_exp = 4
texture, mask = self.bake_from_multiview(multiviews_pil,
selected_camera_elevs, selected_camera_azims, selected_view_weights,
method=merge_method)
mask = mask.squeeze(-1).cpu().float()
texture = texture.unsqueeze(0).cpu().float()
return (texture, mask, self.render)
def bake_from_multiview(self, views, camera_elevs,
camera_azims, view_weights, method='graphcut'):
project_textures, project_weighted_cos_maps = [], []
project_boundary_maps = []
pbar = ProgressBar(len(views))
for view, camera_elev, camera_azim, weight in zip(
views, camera_elevs, camera_azims, view_weights):
project_texture, project_cos_map, project_boundary_map = self.render.back_project(
view, camera_elev, camera_azim)
project_cos_map = weight * (project_cos_map ** self.bake_exp)
project_textures.append(project_texture)
project_weighted_cos_maps.append(project_cos_map)
project_boundary_maps.append(project_boundary_map)
pbar.update(1)
if method == 'fast':
texture, ori_trust_map = self.render.fast_bake_texture(
project_textures, project_weighted_cos_maps)
else:
raise f'no method {method}'
return texture, ori_trust_map > 1E-8
class Hy3DMeshVerticeInpaintTexture:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"texture": ("IMAGE", ),
"mask": ("MASK", ),
"renderer": ("MESHRENDER",),
},
}
RETURN_TYPES = ("IMAGE", "MASK", "MESHRENDER" )
RETURN_NAMES = ("texture", "mask", "renderer" )
FUNCTION = "process"
CATEGORY = "Hunyuan3DWrapper"
def process(self, texture, renderer, mask):
from .hy3dgen.texgen.differentiable_renderer.mesh_processor import meshVerticeInpaint
vtx_pos, pos_idx, vtx_uv, uv_idx = renderer.get_mesh()
mask_np = (mask.squeeze(-1).squeeze(0).cpu().numpy() * 255).astype(np.uint8)
texture_np = texture.squeeze(0).cpu().numpy() * 255
texture_np, mask_np = meshVerticeInpaint(
texture_np, mask_np, vtx_pos, vtx_uv, pos_idx, uv_idx)
texture_tensor = torch.from_numpy(texture_np).float() / 255.0
texture_tensor = texture_tensor.unsqueeze(0)
mask_tensor = torch.from_numpy(mask_np).float() / 255.0
mask_tensor = mask_tensor.unsqueeze(0)
return (texture_tensor, mask_tensor, renderer)
class CV2InpaintTexture:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"texture": ("IMAGE", ),
"mask": ("MASK", ),
"inpaint_radius": ("INT", {"default": 3, "min": 1, "max": 10, "step": 1}),
"inpaint_method": (["ns", "telea"], {"default": "ns"}),
},
}
RETURN_TYPES = ("IMAGE", )
RETURN_NAMES = ("texture", )
FUNCTION = "inpaint"
CATEGORY = "Hunyuan3DWrapper"
def inpaint(self, texture, mask, inpaint_radius, inpaint_method):
import cv2
mask = 1 - mask
mask_np = (mask.squeeze(-1).squeeze(0).cpu().numpy() * 255).astype(np.uint8)
texture_np = (texture.squeeze(0).cpu().numpy() * 255).astype(np.uint8)
if inpaint_method == "ns":
inpaint_algo = cv2.INPAINT_NS
elif inpaint_method == "telea":
inpaint_algo = cv2.INPAINT_TELEA
texture_np = cv2.inpaint(
texture_np,
mask_np,
inpaint_radius,
inpaint_algo)
texture_tensor = torch.from_numpy(texture_np).float() / 255.0
texture_tensor = texture_tensor.unsqueeze(0)
return (texture_tensor, )
class Hy3DApplyTexture:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"texture": ("IMAGE", ),
"renderer": ("MESHRENDER",),
},
}
RETURN_TYPES = ("HY3DMESH", )
RETURN_NAMES = ("mesh", )
FUNCTION = "apply"
CATEGORY = "Hunyuan3DWrapper"
def apply(self, texture, renderer):
self.render = renderer
self.render.set_texture(texture.squeeze(0))
textured_mesh = self.render.save_mesh()
return (textured_mesh,)
#region Mesh
class Hy3DLoadMesh:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"glb_path": ("STRING", {"default": "", "tooltip": "The glb path with mesh to load."}),
}
}
RETURN_TYPES = ("HY3DMESH",)
RETURN_NAMES = ("mesh",)
OUTPUT_TOOLTIPS = ("The glb model with mesh to texturize.",)
FUNCTION = "load"
CATEGORY = "Hunyuan3DWrapper"
DESCRIPTION = "Loads a glb model from the given path."
def load(self, glb_path):
mesh = trimesh.load(glb_path, force="mesh")
return (mesh,)
class Hy3DGenerateMesh:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"pipeline": ("HY3DMODEL",),
"image": ("IMAGE", ),
"guidance_scale": ("FLOAT", {"default": 5.5, "min": 0.0, "max": 100.0, "step": 0.01}),
"steps": ("INT", {"default": 30, "min": 1}),
"seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff}),
},
"optional": {
"mask": ("MASK", ),
}
}
RETURN_TYPES = ("HY3DLATENT",)
RETURN_NAMES = ("latents",)
FUNCTION = "process"
CATEGORY = "Hunyuan3DWrapper"
def process(self, pipeline, image, steps, guidance_scale, seed, mask=None):
device = mm.get_torch_device()
offload_device = mm.unet_offload_device()
image = image.permute(0, 3, 1, 2).to(device)
image = image * 2 - 1
if mask is not None:
mask = mask.unsqueeze(0).to(device)
pipeline.to(device)
try:
torch.cuda.reset_peak_memory_stats(device)
except:
pass
latents = pipeline(
image=image,
mask=mask,
num_inference_steps=steps,
guidance_scale=guidance_scale,
generator=torch.manual_seed(seed))
print_memory(device)
try:
torch.cuda.reset_peak_memory_stats(device)
except:
pass
pipeline.to(offload_device)
return (latents, )
class Hy3DVAEDecode:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"vae": ("HY3DVAE",),
"latents": ("HY3DLATENT", ),
"box_v": ("FLOAT", {"default": 1.01, "min": -10.0, "max": 10.0, "step": 0.001}),
"octree_resolution": ("INT", {"default": 384, "min": 64, "max": 4096, "step": 16}),
"num_chunks": ("INT", {"default": 8000, "min": 1, "max": 10000000, "step": 1}),
"mc_level": ("FLOAT", {"default": 0, "min": -1.0, "max": 1.0, "step": 0.0001}),
"mc_algo": (["mc", "dmc"], {"default": "mc"}),
},
}
RETURN_TYPES = ("HY3DMESH",)
RETURN_NAMES = ("mesh",)
FUNCTION = "process"
CATEGORY = "Hunyuan3DWrapper"
def process(self, vae, latents, box_v, octree_resolution, mc_level, num_chunks, mc_algo):
device = mm.get_torch_device()
offload_device = mm.unet_offload_device()
vae.to(device)
latents = 1. / vae.scale_factor * latents
latents = vae(latents)
outputs = vae.latents2mesh(
latents,
bounds=box_v,
mc_level=mc_level,
num_chunks=num_chunks,
octree_resolution=octree_resolution,
mc_algo=mc_algo,
)[0]
vae.to(offload_device)
outputs.mesh_f = outputs.mesh_f[:, ::-1]
mesh_output = trimesh.Trimesh(outputs.mesh_v, outputs.mesh_f)
log.info(f"Decoded mesh with {mesh_output.vertices.shape[0]} vertices and {mesh_output.faces.shape[0]} faces")
return (mesh_output, )
class Hy3DPostprocessMesh:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"mesh": ("HY3DMESH",),
"remove_floaters": ("BOOLEAN", {"default": True}),
"remove_degenerate_faces": ("BOOLEAN", {"default": True}),
"reduce_faces": ("BOOLEAN", {"default": True}),
"max_facenum": ("INT", {"default": 40000, "min": 1, "max": 10000000, "step": 1}),
"smooth_normals": ("BOOLEAN", {"default": False}),
},
}
RETURN_TYPES = ("HY3DMESH",)
RETURN_NAMES = ("mesh",)
FUNCTION = "process"
CATEGORY = "Hunyuan3DWrapper"
def process(self, mesh, remove_floaters, remove_degenerate_faces, reduce_faces, max_facenum, smooth_normals):
new_mesh = mesh.copy()
if remove_floaters:
new_mesh = FloaterRemover()(new_mesh)
log.info(f"Removed floaters, resulting in {new_mesh.vertices.shape[0]} vertices and {new_mesh.faces.shape[0]} faces")
if remove_degenerate_faces:
new_mesh = DegenerateFaceRemover()(new_mesh)
log.info(f"Removed degenerate faces, resulting in {new_mesh.vertices.shape[0]} vertices and {new_mesh.faces.shape[0]} faces")
if reduce_faces:
new_mesh = FaceReducer()(new_mesh, max_facenum=max_facenum)
log.info(f"Reduced faces, resulting in {new_mesh.vertices.shape[0]} vertices and {new_mesh.faces.shape[0]} faces")
if smooth_normals:
new_mesh.vertex_normals = trimesh.smoothing.get_vertices_normals(new_mesh)
return (new_mesh, )
class Hy3DGetMeshPBRTextures:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"mesh": ("HY3DMESH",),
"texture" : (["base_color", "emissive", "metallic_roughness", "normal", "occlusion"], ),
},
}
RETURN_TYPES = ("IMAGE", )
RETURN_NAMES = ("image",)
FUNCTION = "get_textures"
CATEGORY = "Hunyuan3DWrapper"
def get_textures(self, mesh, texture):
TEXTURE_MAPPING = {
'base_color': ('baseColorTexture', "Base color"),
'emissive': ('emissiveTexture', "Emissive"),
'metallic_roughness': ('metallicRoughnessTexture', "Metallic roughness"),
'normal': ('normalTexture', "Normal"),
'occlusion': ('occlusionTexture', "Occlusion"),
}
texture_attr, texture_name = TEXTURE_MAPPING[texture]
texture_data = getattr(mesh.visual.material, texture_attr)
if texture_data is None:
raise ValueError(f"{texture_name} texture not found")
to_tensor = transforms.ToTensor()
return (to_tensor(texture_data).unsqueeze(0).permute(0, 2, 3, 1).cpu().float(),)
class Hy3DSetMeshPBRTextures:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"mesh": ("HY3DMESH",),
"image": ("IMAGE", ),
"texture" : (["base_color", "emissive", "metallic_roughness", "normal", "occlusion"], ),
},
}
RETURN_TYPES = ("HY3DMESH", )
RETURN_NAMES = ("mesh",)
FUNCTION = "set_textures"
CATEGORY = "Hunyuan3DWrapper"
def set_textures(self, mesh, image, texture):
from trimesh.visual.material import SimpleMaterial
if isinstance(mesh.visual.material, SimpleMaterial):
log.info("Found SimpleMaterial, Converting to PBRMaterial")
mesh.visual.material = mesh.visual.material.to_pbr()
TEXTURE_MAPPING = {
'base_color': ('baseColorTexture', "Base color"),
'emissive': ('emissiveTexture', "Emissive"),
'metallic_roughness': ('metallicRoughnessTexture', "Metallic roughness"),
'normal': ('normalTexture', "Normal"),
'occlusion': ('occlusionTexture', "Occlusion"),
}
new_mesh = mesh.copy()
texture_attr, texture_name = TEXTURE_MAPPING[texture]
image_np = (image[0].cpu().numpy() * 255).astype(np.uint8)
if image_np.shape[2] == 4: # RGBA
pil_image = Image.fromarray(image_np, 'RGBA')
else: # RGB
pil_image = Image.fromarray(image_np, 'RGB')
setattr(new_mesh.visual.material, texture_attr, pil_image)
return (new_mesh,)
class Hy3DSetMeshPBRAttributes:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"mesh": ("HY3DMESH",),
"baseColorFactor": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}),
"emissiveFactor": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.01}),
"metallicFactor": ("FLOAT", {"default": 0.5, "min": 0.0, "max": 1.0, "step": 0.01}),
"roughnessFactor": ("FLOAT", {"default": 0.5, "min": 0.0, "max": 1.0, "step": 0.01}),
"doubleSided": ("BOOLEAN", {"default": False}),
},
}
RETURN_TYPES = ("HY3DMESH", )
RETURN_NAMES = ("mesh",)
FUNCTION = "set_textures"
CATEGORY = "Hunyuan3DWrapper"
def set_textures(self, mesh, baseColorFactor, emissiveFactor, metallicFactor, roughnessFactor, doubleSided):
new_mesh = mesh.copy()
new_mesh.visual.material.baseColorFactor = [baseColorFactor, baseColorFactor, baseColorFactor, 1.0]
new_mesh.visual.material.emissiveFactor = [emissiveFactor, emissiveFactor, emissiveFactor]
new_mesh.visual.material.metallicFactor = metallicFactor
new_mesh.visual.material.roughnessFactor = roughnessFactor
new_mesh.visual.material.doubleSided = doubleSided
return (new_mesh,)
class Hy3DExportMesh:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"mesh": ("HY3DMESH",),
"filename_prefix": ("STRING", {"default": "3D/Hy3D"}),
},
}
RETURN_TYPES = ("STRING",)
RETURN_NAMES = ("glb_path",)
FUNCTION = "process"
CATEGORY = "Hunyuan3DWrapper"
def process(self, mesh, filename_prefix):
full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path(filename_prefix, folder_paths.get_output_directory())
output_glb_path = Path(full_output_folder, f'{filename}_{counter:05}_.glb')
output_glb_path.parent.mkdir(exist_ok=True)
mesh.export(output_glb_path)
relative_path = Path(subfolder) / f'{filename}_{counter:05}_.glb'
return (str(relative_path), )
NODE_CLASS_MAPPINGS = {
"Hy3DModelLoader": Hy3DModelLoader,
"Hy3DGenerateMesh": Hy3DGenerateMesh,
"Hy3DExportMesh": Hy3DExportMesh,
"DownloadAndLoadHy3DDelightModel": DownloadAndLoadHy3DDelightModel,
"DownloadAndLoadHy3DPaintModel": DownloadAndLoadHy3DPaintModel,
"Hy3DDelightImage": Hy3DDelightImage,
"Hy3DRenderMultiView": Hy3DRenderMultiView,
"Hy3DBakeFromMultiview": Hy3DBakeFromMultiview,
"Hy3DTorchCompileSettings": Hy3DTorchCompileSettings,
"Hy3DPostprocessMesh": Hy3DPostprocessMesh,
"Hy3DLoadMesh": Hy3DLoadMesh,
"Hy3DCameraConfig": Hy3DCameraConfig,
"Hy3DMeshUVWrap": Hy3DMeshUVWrap,
"Hy3DSampleMultiView": Hy3DSampleMultiView,
"Hy3DMeshVerticeInpaintTexture": Hy3DMeshVerticeInpaintTexture,
"Hy3DApplyTexture": Hy3DApplyTexture,
"CV2InpaintTexture": CV2InpaintTexture,
"Hy3DRenderMultiViewDepth": Hy3DRenderMultiViewDepth,
"Hy3DGetMeshPBRTextures": Hy3DGetMeshPBRTextures,
"Hy3DSetMeshPBRTextures": Hy3DSetMeshPBRTextures,
"Hy3DSetMeshPBRAttributes": Hy3DSetMeshPBRAttributes,
"Hy3DVAEDecode": Hy3DVAEDecode,
"Hy3DRenderSingleView": Hy3DRenderSingleView
}
NODE_DISPLAY_NAME_MAPPINGS = {
"Hy3DModelLoader": "Hy3DModelLoader",
"Hy3DGenerateMesh": "Hy3DGenerateMesh",
"Hy3DExportMesh": "Hy3DExportMesh",
"DownloadAndLoadHy3DDelightModel": "(Down)Load Hy3D DelightModel",
"DownloadAndLoadHy3DPaintModel": "(Down)Load Hy3D PaintModel",
"Hy3DDelightImage": "Hy3DDelightImage",
"Hy3DRenderMultiView": "Hy3D Render MultiView",
"Hy3DBakeFromMultiview": "Hy3D Bake From Multiview",
"Hy3DTorchCompileSettings": "Hy3D Torch Compile Settings",
"Hy3DPostprocessMesh": "Hy3D Postprocess Mesh",
"Hy3DLoadMesh": "Hy3D Load Mesh",
"Hy3DCameraConfig": "Hy3D Camera Config",
"Hy3DMeshUVWrap": "Hy3D Mesh UV Wrap",
"Hy3DSampleMultiView": "Hy3D Sample MultiView",
"Hy3DMeshVerticeInpaintTexture": "Hy3D Mesh Vertice Inpaint Texture",
"Hy3DApplyTexture": "Hy3D Apply Texture",
"CV2InpaintTexture": "CV2 Inpaint Texture",
"Hy3DRenderMultiViewDepth": "Hy3D Render MultiView Depth",
"Hy3DGetMeshPBRTextures": "Hy3D Get Mesh PBR Textures",
"Hy3DSetMeshPBRTextures": "Hy3D Set Mesh PBR Textures",
"Hy3DSetMeshPBRAttributes": "Hy3D Set Mesh PBR Attributes",
"Hy3DVAEDecode": "Hy3D VAE Decode",
"Hy3DRenderSingleView": "Hy3D Render SingleView"
}
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