', obj_html))
-
- output_html_path = output_html_path.replace(SAVE_DIR + '/', '')
- iframe_tag = f''
- print(f'Find html {output_html_path}, {os.path.exists(output_html_path)}')
-
- return f"""
-
- {iframe_tag}
-
- """
-
-
-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()
-
- if image is None:
- start_time = time.time()
- try:
- image = t2i_worker(caption)
- except Exception as e:
- raise gr.Error(f"Text to 3D is disable. Please enable it by `python gradio_app.py --enable_t23d`.")
- 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),
- 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),
- model_viewer_html,
- )
-
-
-def build_app():
- title_html = """
-
-
- Hunyuan3D-2: Scaling Diffusion Models for High Resolution Textured 3D Assets Generation
-
-
- Tencent Hunyuan3D Team
-
-
- """
-
- with gr.Blocks(theme=gr.themes.Base(), title='Hunyuan-3D-2.0') as demo:
- 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', visible=HAS_T2I) 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', visible=HAS_TEXTUREGEN)
-
- 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:
- 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')
-
- 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', visible=HAS_T2I) as tab_gt:
- with gr.Row():
- gr.Examples(examples=example_ts, inputs=[caption],
- label="Text Prompts", examples_per_page=18)
-
- if not HAS_TEXTUREGEN:
- gr.HTML(""")
-
- Warning:
- Texture synthesis is disable due to missing requirements,
- please install requirements following README.md to activate it.
-
- """)
- if not args.enable_t23d:
- gr.HTML("""
-
- Warning:
- Text to 3D is disable. To activate it, please run `python gradio_app.py --enable_t23d`.
-
- """)
-
- tab_gi.select(fn=lambda: gr.update(selected='tab_img_prompt'), outputs=tabs_prompt)
- if HAS_T2I:
- 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]
- ).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]
- ).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')
- parser.add_argument('--enable_t23d', action='store_true')
- 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 = """
-
- """
-
- INPUT_MESH_HTML = """
-
-
- """
- example_is = get_example_img_list()
- example_ts = get_example_txt_list()
-
- try:
- from hy3dgen.texgen import Hunyuan3DPaintPipeline
-
- texgen_worker = Hunyuan3DPaintPipeline.from_pretrained('tencent/Hunyuan3D-2')
- HAS_TEXTUREGEN = True
- except Exception as e:
- print(e)
- print("Failed to load texture generator.")
- print('Please try to install requirements by following README.md')
- HAS_TEXTUREGEN = False
-
- HAS_T2I = False
- if args.enable_t23d:
- from hy3dgen.text2image import HunyuanDiTPipeline
-
- t2i_worker = HunyuanDiTPipeline('Tencent-Hunyuan/HunyuanDiT-v1.1-Diffusers-Distilled')
- HAS_T2I = True
-
- from hy3dgen.shapegen import FaceReducer, FloaterRemover, DegenerateFaceRemover, \
- Hunyuan3DDiTFlowMatchingPipeline
- from hy3dgen.rembg import BackgroundRemover
-
- rmbg_worker = BackgroundRemover()
- i23d_worker = Hunyuan3DDiTFlowMatchingPipeline.from_pretrained('tencent/Hunyuan3D-2')
- floater_remove_worker = FloaterRemover()
- degenerate_face_remove_worker = DegenerateFaceRemover()
- face_reduce_worker = FaceReducer()
-
- # https://discuss.huggingface.co/t/how-to-serve-an-html-file/33921/2
- # create a FastAPI app
- app = FastAPI()
- # create a static directory to store the static files
- static_dir = Path('./gradio_cache')
- static_dir.mkdir(parents=True, exist_ok=True)
- app.mount("/static", StaticFiles(directory=static_dir), name="static")
-
- demo = build_app()
- app = gr.mount_gradio_app(app, demo, path="/")
- uvicorn.run(app, host="0.0.0.0", port=args.port)
diff --git a/.ipynb_checkpoints/hg_app-checkpoint.py b/.ipynb_checkpoints/hg_app-checkpoint.py
deleted file mode 100644
index 41d691e119a36d0d4460f9fa287e36e667bc3a5e..0000000000000000000000000000000000000000
--- a/.ipynb_checkpoints/hg_app-checkpoint.py
+++ /dev/null
@@ -1,416 +0,0 @@
-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 .")
-
-import os
-import shutil
-import time
-from glob import glob
-from pathlib import Path
-
-import gradio as gr
-import torch
-import uvicorn
-from fastapi import FastAPI
-from fastapi.staticfiles import StaticFiles
-
-
-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"""
-
-
-
-
- """
-
- with open(output_html_path, 'w') as f:
- f.write(template_html.replace('', obj_html))
-
- output_html_path = output_html_path.replace(SAVE_DIR + '/', '')
- iframe_tag = f''
- print(f'Find html {output_html_path}, {os.path.exists(output_html_path)}')
-
- return f"""
-
- {iframe_tag}
-
- """
-
-@spaces.GPU(duration=40)
-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()
-
- if image is None:
- start_time = time.time()
- try:
- image = t2i_worker(caption)
- except Exception as e:
- raise gr.Error(f"Text to 3D is disable. Please enable it by `python gradio_app.py --enable_t23d`.")
- 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
-
-@spaces.GPU(duration=60)
-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),
- model_viewer_html,
- model_viewer_html_textured,
- )
-
-@spaces.GPU(duration=40)
-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),
- model_viewer_html,
- )
-
-
-def build_app():
- title_html = """
-
-
- Hunyuan3D-2: Scaling Diffusion Models for High Resolution Textured 3D Assets Generation
-
-
- Tencent Hunyuan3D Team
-
-
- """
-
- with gr.Blocks(theme=gr.themes.Base(), title='Hunyuan-3D-2.0') as demo:
- 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', visible=HAS_T2I) 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', visible=HAS_TEXTUREGEN)
-
- 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:
- 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')
-
- 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', visible=HAS_T2I) as tab_gt:
- with gr.Row():
- gr.Examples(examples=example_ts, inputs=[caption],
- label="Text Prompts", examples_per_page=18)
-
- if not HAS_TEXTUREGEN:
- gr.HTML(""")
-
- Warning:
- Texture synthesis is disable due to missing requirements,
- please install requirements following README.md to activate it.
-
- """)
- if not args.enable_t23d:
- gr.HTML("""
-
- Warning:
- Text to 3D is disable. To activate it, please run `python gradio_app.py --enable_t23d`.
-
- """)
-
- tab_gi.select(fn=lambda: gr.update(selected='tab_img_prompt'), outputs=tabs_prompt)
- if HAS_T2I:
- 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]
- ).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]
- ).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')
- parser.add_argument('--enable_t23d', default=True)
- 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 = """
-
- """
-
- INPUT_MESH_HTML = """
-
-
- """
- example_is = get_example_img_list()
- example_ts = get_example_txt_list()
-
- try:
- from hy3dgen.texgen import Hunyuan3DPaintPipeline
-
- texgen_worker = Hunyuan3DPaintPipeline.from_pretrained('tencent/Hunyuan3D-2')
- HAS_TEXTUREGEN = True
- except Exception as e:
- print(e)
- print("Failed to load texture generator.")
- print('Please try to install requirements by following README.md')
- HAS_TEXTUREGEN = False
-
- HAS_T2I = False
- if args.enable_t23d:
- from hy3dgen.text2image import HunyuanDiTPipeline
-
- t2i_worker = HunyuanDiTPipeline('Tencent-Hunyuan/HunyuanDiT-v1.1-Diffusers-Distilled')
- HAS_T2I = True
-
- from hy3dgen.shapegen import FaceReducer, FloaterRemover, DegenerateFaceRemover, \
- Hunyuan3DDiTFlowMatchingPipeline
- from hy3dgen.rembg import BackgroundRemover
-
- rmbg_worker = BackgroundRemover()
- i23d_worker = Hunyuan3DDiTFlowMatchingPipeline.from_pretrained('tencent/Hunyuan3D-2')
- floater_remove_worker = FloaterRemover()
- degenerate_face_remove_worker = DegenerateFaceRemover()
- face_reduce_worker = FaceReducer()
-
- # https://discuss.huggingface.co/t/how-to-serve-an-html-file/33921/2
- # create a FastAPI app
- app = FastAPI()
- # create a static directory to store the static files
- static_dir = Path('./gradio_cache')
- static_dir.mkdir(parents=True, exist_ok=True)
- app.mount("/static", StaticFiles(directory=static_dir), name="static")
-
- demo = build_app()
- app = gr.mount_gradio_app(app, demo, path="/")
- uvicorn.run(app, host="0.0.0.0", port=7860)
diff --git a/.ipynb_checkpoints/requirements-checkpoint.txt b/.ipynb_checkpoints/requirements-checkpoint.txt
deleted file mode 100644
index 434962eece0c4691e11152c73e063c8a130cdd99..0000000000000000000000000000000000000000
--- a/.ipynb_checkpoints/requirements-checkpoint.txt
+++ /dev/null
@@ -1,35 +0,0 @@
-gradio_litmodel3d
-ninja
-pybind11
-trimesh
-diffusers
-tqdm
-einops
-opencv-python
-numpy
-torch
-transformers
-torchvision
-torchaudio
-ConfigArgParse
-xatlas
-scikit-learn
-scikit-image
-tritonclient
-gevent
-geventhttpclient
-facexlib
-accelerate
-ipdb
-omegaconf
-pymeshlab
-pytorch_lightning
-taming-transformers-rom1504
-kornia
-rembg
-onnxruntime
-pygltflib
-sentencepiece
-gradio
-uvicorn
-fastapi
\ No newline at end of file
diff --git a/README.md b/README.md
index 3c5bafebfe4503dab0bedd7505f6b2691add84c9..6a7d28e5bc1eead243670220e6d55990f74e47ce 100644
--- a/README.md
+++ b/README.md
@@ -8,6 +8,8 @@ sdk_version: 4.44.1
app_file: hg_app.py
pinned: false
short_description: Text-to-3D and Image-to-3D Generation
+models:
+- tencent/Hunyuan3D-2
---
diff --git a/assets/example_images/009.png b/assets/example_images/009.png
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diff --git a/gradio_cache/0/input.png b/gradio_cache/0/input.png
deleted file mode 100644
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diff --git a/gradio_cache/0/rembg.png b/gradio_cache/0/rembg.png
deleted file mode 100644
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diff --git a/gradio_cache/0/textured_mesh.glb b/gradio_cache/0/textured_mesh.glb
deleted file mode 100644
index f4350074bc8af06fe8bebd631b3374cb987ebcf2..0000000000000000000000000000000000000000
--- a/gradio_cache/0/textured_mesh.glb
+++ /dev/null
@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:82c8286bce9c760b166e9f8a57b3c701b913f9e6592f2c4bc08d66ae89c7ea34
-size 2464072
diff --git a/gradio_cache/0/textured_mesh.html b/gradio_cache/0/textured_mesh.html
deleted file mode 100644
index 8d8a5238be36e935f3658c84a97f00656a117cd8..0000000000000000000000000000000000000000
--- a/gradio_cache/0/textured_mesh.html
+++ /dev/null
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-
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diff --git a/gradio_cache/0/white_mesh.glb b/gradio_cache/0/white_mesh.glb
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--- a/gradio_cache/0/white_mesh.html
+++ /dev/null
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diff --git a/gradio_cache/1/input.png b/gradio_cache/1/input.png
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diff --git a/gradio_cache/1/rembg.png b/gradio_cache/1/rembg.png
deleted file mode 100644
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diff --git a/gradio_cache/1/textured_mesh.glb b/gradio_cache/1/textured_mesh.glb
deleted file mode 100644
index 0c19c14e97fdb4d51cc37036e022d8f2a433455c..0000000000000000000000000000000000000000
--- a/gradio_cache/1/textured_mesh.glb
+++ /dev/null
@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:00f04ece070c997b2b25bc9ad7674e737b8f42f533d68b732ed6ae459709fef2
-size 2464060
diff --git a/gradio_cache/1/textured_mesh.html b/gradio_cache/1/textured_mesh.html
deleted file mode 100644
index 8d8a5238be36e935f3658c84a97f00656a117cd8..0000000000000000000000000000000000000000
--- a/gradio_cache/1/textured_mesh.html
+++ /dev/null
@@ -1,40 +0,0 @@
-
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\ No newline at end of file
diff --git a/gradio_cache/1/white_mesh.glb b/gradio_cache/1/white_mesh.glb
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deleted file mode 100644
index f10c4e718eca4aba9dae6dab2452a2a038e6a354..0000000000000000000000000000000000000000
--- a/gradio_cache/1/white_mesh.html
+++ /dev/null
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-
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\ No newline at end of file
diff --git a/gradio_cache/2/input.png b/gradio_cache/2/input.png
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deleted file mode 100644
index f10c4e718eca4aba9dae6dab2452a2a038e6a354..0000000000000000000000000000000000000000
--- a/gradio_cache/2/white_mesh.html
+++ /dev/null
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-
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\ No newline at end of file
diff --git a/gradio_cache/3/input.png b/gradio_cache/3/input.png
deleted file mode 100644
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deleted file mode 100644
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deleted file mode 100644
index 613df20542b42a1486c0843ab26e69138cfe8096..0000000000000000000000000000000000000000
--- a/gradio_cache/3/textured_mesh.glb
+++ /dev/null
@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:c93b387fb95e04b19f37be60d7b334702406f0e672df73fd5803cbd29d41af8b
-size 2183696
diff --git a/gradio_cache/3/textured_mesh.html b/gradio_cache/3/textured_mesh.html
deleted file mode 100644
index 8d8a5238be36e935f3658c84a97f00656a117cd8..0000000000000000000000000000000000000000
--- a/gradio_cache/3/textured_mesh.html
+++ /dev/null
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\ No newline at end of file
diff --git a/gradio_cache/3/white_mesh.glb b/gradio_cache/3/white_mesh.glb
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index f10c4e718eca4aba9dae6dab2452a2a038e6a354..0000000000000000000000000000000000000000
--- a/gradio_cache/3/white_mesh.html
+++ /dev/null
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\ No newline at end of file
diff --git a/gradio_cache/4/input.png b/gradio_cache/4/input.png
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deleted file mode 100644
index b046101ce7c437440c247c62cd99c833a317859f..0000000000000000000000000000000000000000
--- a/gradio_cache/4/textured_mesh.glb
+++ /dev/null
@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:9a3572334508a5661c1ff75f4ad228c6d1b40b5e46b7eded9fc00759d738ec13
-size 2472736
diff --git a/gradio_cache/4/textured_mesh.html b/gradio_cache/4/textured_mesh.html
deleted file mode 100644
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--- a/gradio_cache/4/textured_mesh.html
+++ /dev/null
@@ -1,40 +0,0 @@
-
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\ No newline at end of file
diff --git a/gradio_cache/4/white_mesh.glb b/gradio_cache/4/white_mesh.glb
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deleted file mode 100644
index f10c4e718eca4aba9dae6dab2452a2a038e6a354..0000000000000000000000000000000000000000
--- a/gradio_cache/4/white_mesh.html
+++ /dev/null
@@ -1,57 +0,0 @@
-
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\ No newline at end of file
diff --git a/hy3dgen/.ipynb_checkpoints/text2image-checkpoint.py b/hy3dgen/.ipynb_checkpoints/text2image-checkpoint.py
deleted file mode 100644
index ec2c1cde6b416aa787fc8d0ce1575118a58564b4..0000000000000000000000000000000000000000
--- a/hy3dgen/.ipynb_checkpoints/text2image-checkpoint.py
+++ /dev/null
@@ -1,92 +0,0 @@
-# Open Source Model Licensed under the Apache License Version 2.0
-# and Other Licenses of the Third-Party Components therein:
-# The below Model in this distribution may have been modified by THL A29 Limited
-# ("Tencent Modifications"). All Tencent Modifications are Copyright (C) 2024 THL A29 Limited.
-
-# Copyright (C) 2024 THL A29 Limited, a Tencent company. All rights reserved.
-# The below software and/or models in this distribution may have been
-# modified by THL A29 Limited ("Tencent Modifications").
-# All Tencent Modifications are Copyright (C) THL A29 Limited.
-
-# Hunyuan 3D is licensed under the TENCENT HUNYUAN NON-COMMERCIAL LICENSE AGREEMENT
-# except for the third-party components listed below.
-# Hunyuan 3D does not impose any additional limitations beyond what is outlined
-# in the repsective licenses of these third-party components.
-# Users must comply with all terms and conditions of original licenses of these third-party
-# components and must ensure that the usage of the third party components adheres to
-# all relevant laws and regulations.
-
-# For avoidance of doubts, Hunyuan 3D means the large language models and
-# their software and algorithms, including trained model weights, parameters (including
-# optimizer states), machine-learning model code, inference-enabling code, training-enabling code,
-# fine-tuning enabling code and other elements of the foregoing made publicly available
-# by Tencent in accordance with TENCENT HUNYUAN COMMUNITY LICENSE AGREEMENT.
-
-
-import os
-import random
-
-import numpy as np
-import torch
-from diffusers import AutoPipelineForText2Image
-
-
-def seed_everything(seed):
- random.seed(seed)
- np.random.seed(seed)
- torch.manual_seed(seed)
- os.environ["PL_GLOBAL_SEED"] = str(seed)
-
-
-class HunyuanDiTPipeline:
- def __init__(
- self,
- model_path="Tencent-Hunyuan/HunyuanDiT-v1.1-Diffusers-Distilled",
- device='cuda'
- ):
- self.device = device
- self.pipe = AutoPipelineForText2Image.from_pretrained(
- model_path,
- torch_dtype=torch.float16,
- enable_pag=True,
- pag_applied_layers=["blocks.(16|17|18|19)"]
- ).to(device)
- self.pos_txt = ",白色背景,3D风格,最佳质量"
- self.neg_txt = "文本,特写,裁剪,出框,最差质量,低质量,JPEG伪影,PGLY,重复,病态," \
- "残缺,多余的手指,变异的手,画得不好的手,画得不好的脸,变异,畸形,模糊,脱水,糟糕的解剖学," \
- "糟糕的比例,多余的肢体,克隆的脸,毁容,恶心的比例,畸形的肢体,缺失的手臂,缺失的腿," \
- "额外的手臂,额外的腿,融合的手指,手指太多,长脖子"
-
- def compile(self):
- # accelarate hunyuan-dit transformer,first inference will cost long time
- torch.set_float32_matmul_precision('high')
- self.pipe.transformer = torch.compile(self.pipe.transformer, fullgraph=True)
- # self.pipe.vae.decode = torch.compile(self.pipe.vae.decode, fullgraph=True)
- generator = torch.Generator(device=self.pipe.device) # infer once for hot-start
- out_img = self.pipe(
- prompt='美少女战士',
- negative_prompt='模糊',
- num_inference_steps=25,
- pag_scale=1.3,
- width=1024,
- height=1024,
- generator=generator,
- return_dict=False
- )[0][0]
-
- @torch.no_grad()
- def __call__(self, prompt, seed=0):
- seed_everything(seed)
- generator = torch.Generator(device=self.pipe.device)
- generator = generator.manual_seed(int(seed))
- out_img = self.pipe(
- prompt=self.pos_txt+prompt,
- negative_prompt=self.neg_txt,
- num_inference_steps=25,
- pag_scale=1.3,
- width=1024,
- height=1024,
- generator=generator,
- return_dict=False
- )[0][0]
- return out_img
diff --git a/hy3dgen/__pycache__/__init__.cpython-311.pyc b/hy3dgen/__pycache__/__init__.cpython-311.pyc
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