fix some

.ipynb_checkpoints/README-checkpoint.md

@@ -1,201 +0,0 @@
----
-title: Hunyuan3D-2.0
-emoji: 🌍
-colorFrom: purple
-colorTo: red
-sdk: gradio
-sdk_version: 4.44.1
-app_file: hg_app.py
-pinned: false
-short_description: Text-to-3D and Image-to-3D Generation
----
-
-[中文阅读](README_zh_cn.md)
-
-<p align="center">
-  <img src="./assets/images/teaser.jpg">
-
-
-</p>
-
-<div align="center">
-  <a href=https://3d.hunyuan.tencent.com target="_blank"><img src=https://img.shields.io/badge/Hunyuan3D-black.svg?logo=homepage height=22px></a>
-  <a href=https://huggingface.co/spaces/tencent/Hunyuan3D-2  target="_blank"><img src=https://img.shields.io/badge/%F0%9F%A4%97%20Demo-276cb4.svg height=22px></a>
-  <a href=https://huggingface.co/tencent/Hunyuan3D-2 target="_blank"><img src=https://img.shields.io/badge/%F0%9F%A4%97%20Models-d96902.svg height=22px></a>
-  <a href=https://3d-models.hunyuan.tencent.com/ target="_blank"><img src= https://img.shields.io/badge/Page-bb8a2e.svg?logo=github height=22px></a>
-<a href=https://discord.gg/GuaWYwzKbX target="_blank"><img src= https://img.shields.io/badge/Page-white.svg?logo=discord height=22px></a>
-</div>
-
-
-[//]: # (  <a href=# target="_blank"><img src=https://img.shields.io/badge/Report-b5212f.svg?logo=arxiv height=22px></a>)
-
-[//]: # (  <a href=# target="_blank"><img src= https://img.shields.io/badge/Colab-8f2628.svg?logo=googlecolab height=22px></a>)
-
-[//]: # (  <a href="#"><img alt="PyPI - Downloads" src="https://img.shields.io/pypi/v/mulankit?logo=pypi"  height=22px></a>)
-
-<br>
-<p align="center">
-“ Living out everyone’s imagination on creating and manipulating 3D assets.”
-</p>
-
-## 🔥 News
-
-- Jan 21, 2025: 💬 Release [Hunyuan3D 2.0](https://huggingface.co/spaces/tencent/Hunyuan3D-2). Please give it a try!
-
-## **Abstract**
-
-We present Hunyuan3D 2.0, an advanced large-scale 3D synthesis system for generating high-resolution textured 3D assets.
-This system includes two foundation components: a large-scale shape generation model - Hunyuan3D-DiT, and a large-scale
-texture synthesis model - Hunyuan3D-Paint.
-The shape generative model, built on a scalable flow-based diffusion transformer, aims to create geometry that properly
-aligns with a given condition image, laying a solid foundation for downstream applications.
-The texture synthesis model, benefiting from strong geometric and diffusion priors, produces high-resolution and vibrant
-texture maps for either generated or hand-crafted meshes.
-Furthermore, we build Hunyuan3D-Studio - a versatile, user-friendly production platform that simplifies the re-creation
-process of 3D assets. It allows both professional and amateur users to manipulate or even animate their meshes
-efficiently.
-We systematically evaluate our models, showing that Hunyuan3D 2.0 outperforms previous state-of-the-art models,
-including the open-source models and closed-source models in geometry details, condition alignment, texture quality, and
-e.t.c.
-
-
-
-<p align="center">
-  <img src="assets/images/system.jpg">
-</p>
-
-## ☯️ **Hunyuan3D 2.0**
-
-### Architecture
-
-Hunyuan3D 2.0 features a two-stage generation pipeline, starting with the creation of a bare mesh, followed by the
-synthesis of a texture map for that mesh. This strategy is effective for decoupling the difficulties of shape and
-texture generation and also provides flexibility for texturing either generated or handcrafted meshes.
-
-<p align="left">
-  <img src="assets/images/arch.jpg">
-</p>
-
-### Performance
-
-We have evaluated Hunyuan3D 2.0 with other open-source as well as close-source 3d-generation methods.
-The numerical results indicate that Hunyuan3D 2.0 surpasses all baselines in the quality of generated textured 3D assets
-and the condition following ability.
-
-| Model                   | CMMD(⬇)   | FID_CLIP(⬇) | FID(⬇)      | CLIP-score(⬆) |
-|-------------------------|-----------|-------------|-------------|---------------|
-| Top Open-source Model1  | 3.591     | 54.639      | 289.287     | 0.787         |
-| Top Close-source Model1 | 3.600     | 55.866      | 305.922     | 0.779         |
-| Top Close-source Model2 | 3.368     | 49.744      | 294.628     | 0.806         |
-| Top Close-source Model3 | 3.218     | 51.574      | 295.691     | 0.799         |
-| Hunyuan3D 2.0           | **3.193** | **49.165**  | **282.429** | **0.809**     |
-
-Generation results of Hunyuan3D 2.0:
-<p align="left">
-  <img src="assets/images/e2e-1.gif"  height=300>
-  <img src="assets/images/e2e-2.gif"  height=300>
-</p>
-
-### Pretrained Models
-
-| Model                | Date       | Huggingface                                            |
-|----------------------|------------|--------------------------------------------------------| 
-| Hunyuan3D-DiT-v2-0   | 2025-01-21 | [Download](https://huggingface.co/tencent/Hunyuan3D-2) |
-| Hunyuan3D-Paint-v2-0 | 2025-01-21 | [Download](https://huggingface.co/tencent/Hunyuan3D-2) |
-
-## 🤗 Get Started with Hunyuan3D 2.0
-
-You may follow the next steps to use Hunyuan3D 2.0 via code or the Gradio App.
-
-### Install Requirements
-
-Please install Pytorch via the [official](https://pytorch.org/) site. Then install the other requirements via
-
-```bash
-pip install -r requirements.txt
-# for texture
-cd hy3dgen/texgen/custom_rasterizer
-python3 setup.py install
-cd hy3dgen/texgen/differentiable_renderer
-bash compile_mesh_painter.sh
-```
-
-### API Usage
-
-We designed a diffusers-like API to use our shape generation model - Hunyuan3D-DiT and texture synthesis model -
-Hunyuan3D-Paint.
-
-You could assess **Hunyuan3D-DiT** via:
-
-```python
-from hy3dgen.shapegen import Hunyuan3DDiTFlowMatchingPipeline
-
-pipeline = Hunyuan3DDiTFlowMatchingPipeline.from_pretrained('tencent/Hunyuan3D-2')
-mesh = pipeline(image='assets/demo.png')[0]
-```
-
-The output mesh is a [trimesh object](https://trimesh.org/trimesh.html), which you could save to glb/obj (or other
-format) file.
-
-For **Hunyuan3D-Paint**, do the following:
-
-```python
-from hy3dgen.texgen import Hunyuan3DPaintPipeline
-from hy3dgen.shapegen import Hunyuan3DDiTFlowMatchingPipeline
-
-# let's generate a mesh first
-pipeline = Hunyuan3DDiTFlowMatchingPipeline.from_pretrained('tencent/Hunyuan3D-2')
-mesh = pipeline(image='assets/demo.png')[0]
-
-pipeline = Hunyuan3DPaintPipeline.from_pretrained('tencent/Hunyuan3D-2')
-mesh = pipeline(mesh, image='assets/demo.png')
-```
-
-Please visit [minimal_demo.py](minimal_demo.py) for more advanced usage, such as **text to 3D** and **texture generation
-for handcrafted mesh**.
-
-### Gradio App
-
-You could also host a [Gradio](https://www.gradio.app/) App in your own computer via:
-
-```bash
-pip3 install gradio==3.39.0
-python3 gradio_app.py
-```
-
-Don't forget to visit [Hunyuan3D](https://3d.hunyuan.tencent.com) for quick use, if you don't want to host yourself.
-
-## 📑 Open-Source Plan
-
-- [x] Inference Code
-- [x] Model Checkpoints
-- [ ] ComfyUI
-- [ ] TensorRT Version
-
-## 🔗 BibTeX
-
-If you found this repository helpful, please cite our report:
-
-```bibtex
-@misc{hunyuan3d22025tencent,
-    title={Hunyuan3D 2.0: Scaling Diffusion Models for High Resolution Textured 3D Assets Generation},
-    author={Tencent Hunyuan3D Team},
-    year={2025},
-}
-```
-
-## Acknowledgements
-
-We would like to thank the contributors to
-the [DINOv2](https://github.com/facebookresearch/dinov2), [Stable Diffusion](https://github.com/Stability-AI/stablediffusion), [FLUX](https://github.com/black-forest-labs/flux), [diffusers](https://github.com/huggingface/diffusers)
-and [HuggingFace](https://huggingface.co) repositories, for their open research and exploration.
-
-## Star History
-
-<a href="https://star-history.com/#Tencent/Hunyuan3D-2&Date">
- <picture>
-   <source media="(prefers-color-scheme: dark)" srcset="https://api.star-history.com/svg?repos=Tencent/Hunyuan3D-2&type=Date&theme=dark" />
-   <source media="(prefers-color-scheme: light)" srcset="https://api.star-history.com/svg?repos=Tencent/Hunyuan3D-2&type=Date" />
-   <img alt="Star History Chart" src="https://api.star-history.com/svg?repos=Tencent/Hunyuan3D-2&type=Date" />
- </picture>
-</a>

.ipynb_checkpoints/gradio_app-checkpoint.py

@@ -1,392 +0,0 @@
-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"""
-            <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))
-
-    output_html_path = output_html_path.replace(SAVE_DIR + '/', '')
-    iframe_tag = f'<iframe src="/static/{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()
-
-    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 = """
-    <div style="font-size: 2em; font-weight: bold; text-align: center; margin-bottom: 5px">
-
-    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-2">Github Page</a> &ensp; 
-      <a href="http://3d-models.hunyuan.tencent.com">Homepage</a> &ensp;
-      <a href="#">Technical Report</a> &ensp;
-      <a href="https://huggingface.co/Tencent/Hunyuan3D-2"> Models</a> &ensp;
-    </div>
-    """
-
-    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(""")
-            <div style="margin-top: 20px;">
-                <b>Warning: </b>
-                Texture synthesis is disable due to missing requirements,
-                 please install requirements following README.md to activate it.
-            </div>
-            """)
-        if not args.enable_t23d:
-            gr.HTML("""
-            <div style="margin-top: 20px;">
-                <b>Warning: </b>
-                Text to 3D is disable. To activate it, please run `python gradio_app.py --enable_t23d`.
-            </div>
-            """)
-
-        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 = """
-    <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()
-
-    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)

.ipynb_checkpoints/hg_app-checkpoint.py

@@ -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"""
-            <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))
-
-    output_html_path = output_html_path.replace(SAVE_DIR + '/', '')
-    iframe_tag = f'<iframe src="/static/{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>
-    """
-
-@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 = """
-    <div style="font-size: 2em; font-weight: bold; text-align: center; margin-bottom: 5px">
-
-    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-2">Github Page</a> &ensp; 
-      <a href="http://3d-models.hunyuan.tencent.com">Homepage</a> &ensp;
-      <a href="#">Technical Report</a> &ensp;
-      <a href="https://huggingface.co/Tencent/Hunyuan3D-2"> Models</a> &ensp;
-    </div>
-    """
-
-    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(""")
-            <div style="margin-top: 20px;">
-                <b>Warning: </b>
-                Texture synthesis is disable due to missing requirements,
-                 please install requirements following README.md to activate it.
-            </div>
-            """)
-        if not args.enable_t23d:
-            gr.HTML("""
-            <div style="margin-top: 20px;">
-                <b>Warning: </b>
-                Text to 3D is disable. To activate it, please run `python gradio_app.py --enable_t23d`.
-            </div>
-            """)
-
-        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 = """
-    <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()
-
-    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)

.ipynb_checkpoints/requirements-checkpoint.txt

@@ -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

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
 ---
 
 

gradio_cache/0/textured_mesh.glb

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:82c8286bce9c760b166e9f8a57b3c701b913f9e6592f2c4bc08d66ae89c7ea34
-size 2464072

gradio_cache/0/textured_mesh.html

@@ -1,40 +0,0 @@
-<!DOCTYPE html>
-<html>
-
-<head>
-    <!-- Import the component -->
-    <script src="https://ajax.googleapis.com/ajax/libs/model-viewer/3.1.1/model-viewer.min.js" type="module"></script>
-
-    <style>
-        body {
-            margin: 0;
-            font-family: Arial, sans-serif;
-        }
-
-        .centered-container {
-            display: flex;
-            justify-content: center;
-            align-items: center;
-            border-radius: 8px;
-            border-color: #e5e7eb;
-            border-style: solid;
-            border-width: 1px;
-        }
-    </style>
-</head>
-
-<body>
-<div class="centered-container">
-    
-            <div class="column is-mobile is-centered">
-                <model-viewer style="height: 586px; width: 700px;" rotation-per-second="10deg" id="modelViewer"
-                    src="./textured_mesh.glb/" 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>
-            
-</div>
-</body>
-
-</html>

gradio_cache/0/white_mesh.html

@@ -1,57 +0,0 @@
-<!DOCTYPE html>
-<html>
-
-<head>
-    <!-- Import the component -->
-    <script src="https://ajax.googleapis.com/ajax/libs/model-viewer/3.1.1/model-viewer.min.js" type="module"></script>
-
-    <script>
-        document.addEventListener('DOMContentLoaded', () => {
-            const modelViewers = document.querySelectorAll('model-viewer');
-
-            modelViewers.forEach(modelViewer => {
-                modelViewer.addEventListener('load', (event) => {
-                    const [material] = modelViewer.model.materials;
-                    let color = [43, 44, 46, 255];
-                    color = color.map(x => x / 255);
-                    material.pbrMetallicRoughness.setMetallicFactor(0.1); // 完全金属
-                    material.pbrMetallicRoughness.setRoughnessFactor(0.7); // 低粗糙度
-                    material.pbrMetallicRoughness.setBaseColorFactor(color);  // CornflowerBlue in RGB
-                });
-            });
-        });
-    </script>
-
-    <style>
-        body {
-            margin: 0;
-            font-family: Arial, sans-serif;
-        }
-
-        .centered-container {
-            display: flex;
-            justify-content: center;
-            align-items: center;
-            border-radius: 8px;
-            border-color: #e5e7eb;
-            border-style: solid;
-            border-width: 1px;
-        }
-    </style>
-</head>
-
-<body>
-<div class="centered-container">
-    
-            <div class="column is-mobile is-centered">
-                <model-viewer style="height: 586px; width: 700px;" rotation-per-second="10deg" id="modelViewer"
-                    src="./white_mesh.glb/" 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>
-            
-</div>
-</body>
-
-</html>

gradio_cache/1/textured_mesh.glb

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:00f04ece070c997b2b25bc9ad7674e737b8f42f533d68b732ed6ae459709fef2
-size 2464060

gradio_cache/1/textured_mesh.html

@@ -1,40 +0,0 @@
-<!DOCTYPE html>
-<html>
-
-<head>
-    <!-- Import the component -->
-    <script src="https://ajax.googleapis.com/ajax/libs/model-viewer/3.1.1/model-viewer.min.js" type="module"></script>
-
-    <style>
-        body {
-            margin: 0;
-            font-family: Arial, sans-serif;
-        }
-
-        .centered-container {
-            display: flex;
-            justify-content: center;
-            align-items: center;
-            border-radius: 8px;
-            border-color: #e5e7eb;
-            border-style: solid;
-            border-width: 1px;
-        }
-    </style>
-</head>
-
-<body>
-<div class="centered-container">
-    
-            <div class="column is-mobile is-centered">
-                <model-viewer style="height: 586px; width: 700px;" rotation-per-second="10deg" id="modelViewer"
-                    src="./textured_mesh.glb/" 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>
-            
-</div>
-</body>
-
-</html>

gradio_cache/1/white_mesh.html

@@ -1,57 +0,0 @@
-<!DOCTYPE html>
-<html>
-
-<head>
-    <!-- Import the component -->
-    <script src="https://ajax.googleapis.com/ajax/libs/model-viewer/3.1.1/model-viewer.min.js" type="module"></script>
-
-    <script>
-        document.addEventListener('DOMContentLoaded', () => {
-            const modelViewers = document.querySelectorAll('model-viewer');
-
-            modelViewers.forEach(modelViewer => {
-                modelViewer.addEventListener('load', (event) => {
-                    const [material] = modelViewer.model.materials;
-                    let color = [43, 44, 46, 255];
-                    color = color.map(x => x / 255);
-                    material.pbrMetallicRoughness.setMetallicFactor(0.1); // 完全金属
-                    material.pbrMetallicRoughness.setRoughnessFactor(0.7); // 低粗糙度
-                    material.pbrMetallicRoughness.setBaseColorFactor(color);  // CornflowerBlue in RGB
-                });
-            });
-        });
-    </script>
-
-    <style>
-        body {
-            margin: 0;
-            font-family: Arial, sans-serif;
-        }
-
-        .centered-container {
-            display: flex;
-            justify-content: center;
-            align-items: center;
-            border-radius: 8px;
-            border-color: #e5e7eb;
-            border-style: solid;
-            border-width: 1px;
-        }
-    </style>
-</head>
-
-<body>
-<div class="centered-container">
-    
-            <div class="column is-mobile is-centered">
-                <model-viewer style="height: 586px; width: 700px;" rotation-per-second="10deg" id="modelViewer"
-                    src="./white_mesh.glb/" 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>
-            
-</div>
-</body>
-
-</html>

gradio_cache/2/white_mesh.html

@@ -1,57 +0,0 @@
-<!DOCTYPE html>
-<html>
-
-<head>
-    <!-- Import the component -->
-    <script src="https://ajax.googleapis.com/ajax/libs/model-viewer/3.1.1/model-viewer.min.js" type="module"></script>
-
-    <script>
-        document.addEventListener('DOMContentLoaded', () => {
-            const modelViewers = document.querySelectorAll('model-viewer');
-
-            modelViewers.forEach(modelViewer => {
-                modelViewer.addEventListener('load', (event) => {
-                    const [material] = modelViewer.model.materials;
-                    let color = [43, 44, 46, 255];
-                    color = color.map(x => x / 255);
-                    material.pbrMetallicRoughness.setMetallicFactor(0.1); // 完全金属
-                    material.pbrMetallicRoughness.setRoughnessFactor(0.7); // 低粗糙度
-                    material.pbrMetallicRoughness.setBaseColorFactor(color);  // CornflowerBlue in RGB
-                });
-            });
-        });
-    </script>
-
-    <style>
-        body {
-            margin: 0;
-            font-family: Arial, sans-serif;
-        }
-
-        .centered-container {
-            display: flex;
-            justify-content: center;
-            align-items: center;
-            border-radius: 8px;
-            border-color: #e5e7eb;
-            border-style: solid;
-            border-width: 1px;
-        }
-    </style>
-</head>
-
-<body>
-<div class="centered-container">
-    
-            <div class="column is-mobile is-centered">
-                <model-viewer style="height: 586px; width: 700px;" rotation-per-second="10deg" id="modelViewer"
-                    src="./white_mesh.glb/" 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>
-            
-</div>
-</body>
-
-</html>

gradio_cache/3/textured_mesh.glb

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:c93b387fb95e04b19f37be60d7b334702406f0e672df73fd5803cbd29d41af8b
-size 2183696

gradio_cache/3/textured_mesh.html

@@ -1,40 +0,0 @@
-<!DOCTYPE html>
-<html>
-
-<head>
-    <!-- Import the component -->
-    <script src="https://ajax.googleapis.com/ajax/libs/model-viewer/3.1.1/model-viewer.min.js" type="module"></script>
-
-    <style>
-        body {
-            margin: 0;
-            font-family: Arial, sans-serif;
-        }
-
-        .centered-container {
-            display: flex;
-            justify-content: center;
-            align-items: center;
-            border-radius: 8px;
-            border-color: #e5e7eb;
-            border-style: solid;
-            border-width: 1px;
-        }
-    </style>
-</head>
-
-<body>
-<div class="centered-container">
-    
-            <div class="column is-mobile is-centered">
-                <model-viewer style="height: 586px; width: 700px;" rotation-per-second="10deg" id="modelViewer"
-                    src="./textured_mesh.glb/" 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>
-            
-</div>
-</body>
-
-</html>

gradio_cache/3/white_mesh.html

@@ -1,57 +0,0 @@
-<!DOCTYPE html>
-<html>
-
-<head>
-    <!-- Import the component -->
-    <script src="https://ajax.googleapis.com/ajax/libs/model-viewer/3.1.1/model-viewer.min.js" type="module"></script>
-
-    <script>
-        document.addEventListener('DOMContentLoaded', () => {
-            const modelViewers = document.querySelectorAll('model-viewer');
-
-            modelViewers.forEach(modelViewer => {
-                modelViewer.addEventListener('load', (event) => {
-                    const [material] = modelViewer.model.materials;
-                    let color = [43, 44, 46, 255];
-                    color = color.map(x => x / 255);
-                    material.pbrMetallicRoughness.setMetallicFactor(0.1); // 完全金属
-                    material.pbrMetallicRoughness.setRoughnessFactor(0.7); // 低粗糙度
-                    material.pbrMetallicRoughness.setBaseColorFactor(color);  // CornflowerBlue in RGB
-                });
-            });
-        });
-    </script>
-
-    <style>
-        body {
-            margin: 0;
-            font-family: Arial, sans-serif;
-        }
-
-        .centered-container {
-            display: flex;
-            justify-content: center;
-            align-items: center;
-            border-radius: 8px;
-            border-color: #e5e7eb;
-            border-style: solid;
-            border-width: 1px;
-        }
-    </style>
-</head>
-
-<body>
-<div class="centered-container">
-    
-            <div class="column is-mobile is-centered">
-                <model-viewer style="height: 586px; width: 700px;" rotation-per-second="10deg" id="modelViewer"
-                    src="./white_mesh.glb/" 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>
-            
-</div>
-</body>
-
-</html>

gradio_cache/4/textured_mesh.glb

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:9a3572334508a5661c1ff75f4ad228c6d1b40b5e46b7eded9fc00759d738ec13
-size 2472736

gradio_cache/4/textured_mesh.html

@@ -1,40 +0,0 @@
-<!DOCTYPE html>
-<html>
-
-<head>
-    <!-- Import the component -->
-    <script src="https://ajax.googleapis.com/ajax/libs/model-viewer/3.1.1/model-viewer.min.js" type="module"></script>
-
-    <style>
-        body {
-            margin: 0;
-            font-family: Arial, sans-serif;
-        }
-
-        .centered-container {
-            display: flex;
-            justify-content: center;
-            align-items: center;
-            border-radius: 8px;
-            border-color: #e5e7eb;
-            border-style: solid;
-            border-width: 1px;
-        }
-    </style>
-</head>
-
-<body>
-<div class="centered-container">
-    
-            <div class="column is-mobile is-centered">
-                <model-viewer style="height: 586px; width: 700px;" rotation-per-second="10deg" id="modelViewer"
-                    src="./textured_mesh.glb/" 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>
-            
-</div>
-</body>
-
-</html>

gradio_cache/4/white_mesh.html

@@ -1,57 +0,0 @@
-<!DOCTYPE html>
-<html>
-
-<head>
-    <!-- Import the component -->
-    <script src="https://ajax.googleapis.com/ajax/libs/model-viewer/3.1.1/model-viewer.min.js" type="module"></script>
-
-    <script>
-        document.addEventListener('DOMContentLoaded', () => {
-            const modelViewers = document.querySelectorAll('model-viewer');
-
-            modelViewers.forEach(modelViewer => {
-                modelViewer.addEventListener('load', (event) => {
-                    const [material] = modelViewer.model.materials;
-                    let color = [43, 44, 46, 255];
-                    color = color.map(x => x / 255);
-                    material.pbrMetallicRoughness.setMetallicFactor(0.1); // 完全金属
-                    material.pbrMetallicRoughness.setRoughnessFactor(0.7); // 低粗糙度
-                    material.pbrMetallicRoughness.setBaseColorFactor(color);  // CornflowerBlue in RGB
-                });
-            });
-        });
-    </script>
-
-    <style>
-        body {
-            margin: 0;
-            font-family: Arial, sans-serif;
-        }
-
-        .centered-container {
-            display: flex;
-            justify-content: center;
-            align-items: center;
-            border-radius: 8px;
-            border-color: #e5e7eb;
-            border-style: solid;
-            border-width: 1px;
-        }
-    </style>
-</head>
-
-<body>
-<div class="centered-container">
-    
-            <div class="column is-mobile is-centered">
-                <model-viewer style="height: 586px; width: 700px;" rotation-per-second="10deg" id="modelViewer"
-                    src="./white_mesh.glb/" 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>
-            
-</div>
-</body>
-
-</html>

hy3dgen/.ipynb_checkpoints/text2image-checkpoint.py

@@ -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