Spaces:
Running
on
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Running
on
Zero
# pip install gradio==4.44.1 | |
if False: | |
import os | |
import spaces | |
import subprocess | |
def install_cuda_toolkit(): | |
# CUDA_TOOLKIT_URL = "https://developer.download.nvidia.com/compute/cuda/11.8.0/local_installers/cuda_11.8.0_520.61.05_linux.run" | |
CUDA_TOOLKIT_URL = "https://developer.download.nvidia.com/compute/cuda/12.2.0/local_installers/cuda_12.2.0_535.54.03_linux.run" | |
CUDA_TOOLKIT_FILE = "/tmp/%s" % os.path.basename(CUDA_TOOLKIT_URL) | |
subprocess.call(["wget", "-q", CUDA_TOOLKIT_URL, "-O", CUDA_TOOLKIT_FILE]) | |
subprocess.call(["chmod", "+x", CUDA_TOOLKIT_FILE]) | |
subprocess.call([CUDA_TOOLKIT_FILE, "--silent", "--toolkit"]) | |
os.environ["CUDA_HOME"] = "/usr/local/cuda" | |
os.environ["PATH"] = "%s/bin:%s" % (os.environ["CUDA_HOME"], os.environ["PATH"]) | |
os.environ["LD_LIBRARY_PATH"] = "%s/lib:%s" % ( | |
os.environ["CUDA_HOME"], | |
"" if "LD_LIBRARY_PATH" not in os.environ else os.environ["LD_LIBRARY_PATH"], | |
) | |
# Fix: arch_list[-1] += '+PTX'; IndexError: list index out of range | |
os.environ["TORCH_CUDA_ARCH_LIST"] = "8.0;8.6" | |
install_cuda_toolkit() | |
os.system("cd /home/user/app/hy3dgen/texgen/differentiable_renderer/ && bash compile_mesh_painter.sh") | |
os.system("cd /home/user/app/hy3dgen/texgen/custom_rasterizer && pip install .") | |
# os.system("cd /home/user/app/hy3dgen/texgen/custom_rasterizer && CUDA_HOME=/usr/local/cuda FORCE_CUDA=1 TORCH_CUDA_ARCH_LIST='8.0;8.6;8.9;9.0' python setup.py install") | |
else: | |
class spaces: | |
class GPU: | |
def __init__(self, duration=60): | |
self.duration = duration | |
def __call__(self, func): | |
return func | |
import os | |
import shutil | |
import time | |
from glob import glob | |
import gradio as gr | |
import torch | |
from gradio_litmodel3d import LitModel3D | |
def get_example_img_list(): | |
print('Loading example img list ...') | |
return sorted(glob('./assets/example_images/*.png')) | |
def get_example_txt_list(): | |
print('Loading example txt list ...') | |
txt_list = list() | |
for line in open('./assets/example_prompts.txt'): | |
txt_list.append(line.strip()) | |
return txt_list | |
def gen_save_folder(max_size=60): | |
os.makedirs(SAVE_DIR, exist_ok=True) | |
exists = set(int(_) for _ in os.listdir(SAVE_DIR) if not _.startswith(".")) | |
cur_id = min(set(range(max_size)) - exists) if len(exists) < max_size else -1 | |
if os.path.exists(f"{SAVE_DIR}/{(cur_id + 1) % max_size}"): | |
shutil.rmtree(f"{SAVE_DIR}/{(cur_id + 1) % max_size}") | |
print(f"remove {SAVE_DIR}/{(cur_id + 1) % max_size} success !!!") | |
save_folder = f"{SAVE_DIR}/{max(0, cur_id)}" | |
os.makedirs(save_folder, exist_ok=True) | |
print(f"mkdir {save_folder} suceess !!!") | |
return save_folder | |
def export_mesh(mesh, save_folder, textured=False): | |
if textured: | |
path = os.path.join(save_folder, f'textured_mesh.glb') | |
else: | |
path = os.path.join(save_folder, f'white_mesh.glb') | |
mesh.export(path, include_normals=textured) | |
return path | |
def build_model_viewer_html(save_folder, height=660, width=790, textured=False): | |
if textured: | |
related_path = f"./textured_mesh.glb" | |
template_name = './assets/modelviewer-textured-template.html' | |
output_html_path = os.path.join(save_folder, f'textured_mesh.html') | |
else: | |
related_path = f"./white_mesh.glb" | |
template_name = './assets/modelviewer-template.html' | |
output_html_path = os.path.join(save_folder, f'white_mesh.html') | |
with open(os.path.join(CURRENT_DIR, template_name), 'r') as f: | |
template_html = f.read() | |
obj_html = f""" | |
<div class="column is-mobile is-centered"> | |
<model-viewer style="height: {height - 10}px; width: {width}px;" rotation-per-second="10deg" id="modelViewer" | |
src="{related_path}/" disable-tap | |
environment-image="neutral" auto-rotate camera-target="0m 0m 0m" orientation="0deg 0deg 170deg" shadow-intensity=".9" | |
ar auto-rotate camera-controls> | |
</model-viewer> | |
</div> | |
""" | |
with open(output_html_path, 'w') as f: | |
f.write(template_html.replace('<model-viewer>', obj_html)) | |
iframe_tag = f'<iframe src="file/{output_html_path}" height="{height}" width="100%" frameborder="0"></iframe>' | |
print(f'Find html {output_html_path}, {os.path.exists(output_html_path)}') | |
return f""" | |
<div style='height: {height}; width: 100%;'> | |
{iframe_tag} | |
</div> | |
""" | |
def _gen_shape( | |
caption, | |
image, | |
steps=50, | |
guidance_scale=7.5, | |
seed=1234, | |
octree_resolution=256, | |
check_box_rembg=False, | |
): | |
if caption: print('prompt is', caption) | |
save_folder = gen_save_folder() | |
stats = {} | |
time_meta = {} | |
start_time_0 = time.time() | |
image_path = '' | |
if image is None: | |
start_time = time.time() | |
image = t2i_worker(caption) | |
time_meta['text2image'] = time.time() - start_time | |
image.save(os.path.join(save_folder, 'input.png')) | |
print(image.mode) | |
if check_box_rembg or image.mode == "RGB": | |
start_time = time.time() | |
image = rmbg_worker(image.convert('RGB')) | |
time_meta['rembg'] = time.time() - start_time | |
image.save(os.path.join(save_folder, 'rembg.png')) | |
# image to white model | |
start_time = time.time() | |
generator = torch.Generator() | |
generator = generator.manual_seed(int(seed)) | |
mesh = i23d_worker( | |
image=image, | |
num_inference_steps=steps, | |
guidance_scale=guidance_scale, | |
generator=generator, | |
octree_resolution=octree_resolution | |
)[0] | |
mesh = FloaterRemover()(mesh) | |
mesh = DegenerateFaceRemover()(mesh) | |
mesh = FaceReducer()(mesh) | |
stats['number_of_faces'] = mesh.faces.shape[0] | |
stats['number_of_vertices'] = mesh.vertices.shape[0] | |
time_meta['image_to_textured_3d'] = {'total': time.time() - start_time} | |
time_meta['total'] = time.time() - start_time_0 | |
stats['time'] = time_meta | |
return mesh, save_folder | |
def generation_all( | |
caption, | |
image, | |
steps=50, | |
guidance_scale=7.5, | |
seed=1234, | |
octree_resolution=256, | |
check_box_rembg=False | |
): | |
mesh, save_folder = _gen_shape( | |
caption, | |
image, | |
steps=steps, | |
guidance_scale=guidance_scale, | |
seed=seed, | |
octree_resolution=octree_resolution, | |
check_box_rembg=check_box_rembg | |
) | |
path = export_mesh(mesh, save_folder, textured=False) | |
model_viewer_html = build_model_viewer_html(save_folder, height=596, width=700) | |
textured_mesh = texgen_worker(mesh, image) | |
path_textured = export_mesh(textured_mesh, save_folder, textured=True) | |
model_viewer_html_textured = build_model_viewer_html(save_folder, height=596, width=700, textured=True) | |
return ( | |
gr.update(value=path, visible=True), | |
gr.update(value=path_textured, visible=True), | |
gr.update(value=path, visible=True), | |
gr.update(value=path_textured, visible=True), | |
# model_viewer_html, | |
# model_viewer_html_textured, | |
) | |
def shape_generation( | |
caption, | |
image, | |
steps=50, | |
guidance_scale=7.5, | |
seed=1234, | |
octree_resolution=256, | |
check_box_rembg=False, | |
): | |
mesh, save_folder = _gen_shape( | |
caption, | |
image, | |
steps=steps, | |
guidance_scale=guidance_scale, | |
seed=seed, | |
octree_resolution=octree_resolution, | |
check_box_rembg=check_box_rembg | |
) | |
path = export_mesh(mesh, save_folder, textured=False) | |
model_viewer_html = build_model_viewer_html(save_folder, height=596, width=700) | |
return ( | |
gr.update(value=path, visible=True), | |
gr.update(value=path, visible=True), | |
# model_viewer_html, | |
) | |
def build_app(): | |
title_html = """ | |
<div style="font-size: 2em; font-weight: bold; text-align: center; margin-bottom: 20px"> | |
Hunyuan3D-2: Scaling Diffusion Models for High Resolution Textured 3D Assets Generation | |
</div> | |
<div align="center"> | |
Tencent Hunyuan3D Team | |
</div> | |
<div align="center"> | |
<a href="https://github.com/tencent/Hunyuan3D-1">Github Page</a>   | |
<a href="http://3d-models.hunyuan.tencent.com">Homepage</a>   | |
<a href="https://arxiv.org/pdf/2411.02293">Technical Report</a>   | |
<a href="https://huggingface.co./Tencent/Hunyuan3D-2"> Models</a>   | |
</div> | |
""" | |
css = """ | |
.json-output { | |
height: 578px; | |
} | |
.json-output .json-holder { | |
height: 538px; | |
overflow-y: scroll; | |
} | |
""" | |
with gr.Blocks(theme=gr.themes.Base(), css=css, title='Hunyuan-3D-2.0') as demo: | |
# if not gr.__version__.startswith('4'): gr.HTML(title_html) | |
gr.HTML(title_html) | |
with gr.Row(): | |
with gr.Column(scale=2): | |
with gr.Tabs() as tabs_prompt: | |
with gr.Tab('Image Prompt', id='tab_img_prompt') as tab_ip: | |
image = gr.Image(label='Image', type='pil', image_mode='RGBA', height=290) | |
with gr.Row(): | |
check_box_rembg = gr.Checkbox(value=True, label='Remove Background') | |
with gr.Tab('Text Prompt', id='tab_txt_prompt') as tab_tp: | |
caption = gr.Textbox(label='Text Prompt', | |
placeholder='HunyuanDiT will be used to generate image.', | |
info='Example: A 3D model of a cute cat, white background') | |
with gr.Accordion('Advanced Options', open=False): | |
num_steps = gr.Slider(maximum=50, minimum=20, value=30, step=1, label='Inference Steps') | |
octree_resolution = gr.Dropdown([256, 384, 512], value=256, label='Octree Resolution') | |
cfg_scale = gr.Number(value=5.5, label='Guidance Scale') | |
seed = gr.Slider(maximum=1e7, minimum=0, value=1234, label='Seed') | |
with gr.Group(): | |
btn = gr.Button(value='Generate Shape Only', variant='primary') | |
btn_all = gr.Button(value='Generate Shape and Texture', variant='primary') | |
with gr.Group(): | |
file_out = gr.File(label="File", visible=False) | |
file_out2 = gr.File(label="File", visible=False) | |
with gr.Column(scale=5): | |
with gr.Tabs(): | |
with gr.Tab('Generated Mesh') as mesh1: | |
mesh_output1 = LitModel3D( | |
label="3D Model1", | |
exposure=10.0, | |
height=600, | |
visible=True, | |
clear_color=[0.0, 0.0, 0.0, 0.0], | |
tonemapping="aces", | |
contrast=1.0, | |
scale=1.0, | |
) | |
# html_output1 = gr.HTML(HTML_OUTPUT_PLACEHOLDER, label='Output') | |
with gr.Tab('Generated Textured Mesh') as mesh2: | |
# html_output2 = gr.HTML(HTML_OUTPUT_PLACEHOLDER, label='Output') | |
mesh_output2 = LitModel3D( | |
label="3D Model2", | |
exposure=10.0, | |
height=600, | |
visible=True, | |
clear_color=[0.0, 0.0, 0.0, 0.0], | |
tonemapping="aces", | |
contrast=1.0, | |
scale=1.0, | |
) | |
with gr.Column(scale=2): | |
with gr.Tabs() as gallery: | |
with gr.Tab('Image to 3D Gallery', id='tab_img_gallery') as tab_gi: | |
with gr.Row(): | |
gr.Examples(examples=example_is, inputs=[image], | |
label="Image Prompts", examples_per_page=18) | |
with gr.Tab('Text to 3D Gallery', id='tab_txt_gallery') as tab_gt: | |
with gr.Row(): | |
gr.Examples(examples=example_ts, inputs=[caption], | |
label="Text Prompts", examples_per_page=18) | |
tab_gi.select(fn=lambda: gr.update(selected='tab_img_prompt'), outputs=tabs_prompt) | |
tab_gt.select(fn=lambda: gr.update(selected='tab_txt_prompt'), outputs=tabs_prompt) | |
btn.click( | |
shape_generation, | |
inputs=[ | |
caption, | |
image, | |
num_steps, | |
cfg_scale, | |
seed, | |
octree_resolution, | |
check_box_rembg, | |
], | |
# outputs=[file_out, html_output1] | |
outputs=[file_out, mesh_output1] | |
).then( | |
lambda: gr.update(visible=True), | |
outputs=[file_out], | |
) | |
btn_all.click( | |
generation_all, | |
inputs=[ | |
caption, | |
image, | |
num_steps, | |
cfg_scale, | |
seed, | |
octree_resolution, | |
check_box_rembg, | |
], | |
# outputs=[file_out, file_out2, html_output1, html_output2] | |
outputs=[file_out, file_out2, mesh_output1, mesh_output2] | |
).then( | |
lambda: (gr.update(visible=True), gr.update(visible=True)), | |
outputs=[file_out, file_out2], | |
) | |
return demo | |
if __name__ == '__main__': | |
import argparse | |
parser = argparse.ArgumentParser() | |
parser.add_argument('--port', type=int, default=8080) | |
parser.add_argument('--cache-path', type=str, default='./gradio_cache') | |
args = parser.parse_args() | |
SAVE_DIR = args.cache_path | |
os.makedirs(SAVE_DIR, exist_ok=True) | |
CURRENT_DIR = os.path.dirname(os.path.abspath(__file__)) | |
HTML_OUTPUT_PLACEHOLDER = """ | |
<div style='height: 596px; width: 100%; border-radius: 8px; border-color: #e5e7eb; order-style: solid; border-width: 1px;'></div> | |
""" | |
INPUT_MESH_HTML = """ | |
<div style='height: 490px; width: 100%; border-radius: 8px; | |
border-color: #e5e7eb; order-style: solid; border-width: 1px;'> | |
</div> | |
""" | |
example_is = get_example_img_list() | |
example_ts = get_example_txt_list() | |
from hy3dgen.text2image import HunyuanDiTPipeline | |
from hy3dgen.shapegen import FaceReducer, FloaterRemover, DegenerateFaceRemover, \ | |
Hunyuan3DDiTFlowMatchingPipeline | |
from hy3dgen.texgen import Hunyuan3DPaintPipeline | |
from hy3dgen.rembg import BackgroundRemover | |
rmbg_worker = BackgroundRemover() | |
t2i_worker = HunyuanDiTPipeline() | |
i23d_worker = Hunyuan3DDiTFlowMatchingPipeline.from_pretrained('tencent/Hunyuan3D-2') | |
texgen_worker = Hunyuan3DPaintPipeline.from_pretrained('tencent/Hunyuan3D-2') | |
floater_remove_worker = FloaterRemover() | |
degenerate_face_remove_worker = DegenerateFaceRemover() | |
face_reduce_worker = FaceReducer() | |
demo = build_app() | |
demo.queue().launch() | |