Upload folder using huggingface_hub

.gitattributes

@@ -43,3 +43,4 @@ gradio_cache/3/textured_mesh.glb filter=lfs diff=lfs merge=lfs -text
 gradio_cache/4/textured_mesh.glb filter=lfs diff=lfs merge=lfs -text
 gradio_cache/5/textured_mesh.glb filter=lfs diff=lfs merge=lfs -text
 *.whl filter=lfs diff=lfs merge=lfs -text
+gradio_cache/1/textured_mesh.glb filter=lfs diff=lfs merge=lfs -text

.ipynb_checkpoints/README-checkpoint.md

@@ -0,0 +1,201 @@
+---
+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

@@ -0,0 +1,392 @@
+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

@@ -0,0 +1,416 @@
+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

@@ -0,0 +1,35 @@
+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

assets/modelviewer-template.html

@@ -3,7 +3,8 @@
 
 <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 src="https://ajax.googleapis.com/ajax/libs/model-viewer/3.1.1/model-viewer.min.js" type="module"></script> -->
+    <script src="https://cdn.jsdelivr.net/npm/@google/[email protected]/dist/model-viewer.min.js" type="module"></script>
 
     <script>
         document.addEventListener('DOMContentLoaded', () => {
@@ -46,4 +47,4 @@
 </div>
 </body>
 
-</html>
+</html>

assets/modelviewer-textured-template.html

@@ -3,7 +3,8 @@
 
 <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 src="https://ajax.googleapis.com/ajax/libs/model-viewer/3.1.1/model-viewer.min.js" type="module"></script> -->
+    <script src="https://cdn.jsdelivr.net/npm/@google/[email protected]/dist/model-viewer.min.js" type="module"></script>
 
     <style>
         body {
@@ -29,4 +30,4 @@
 </div>
 </body>
 
-</html>
+</html>

gradio_cache/0/textured_mesh.glb

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

gradio_cache/0/textured_mesh.html

@@ -0,0 +1,40 @@
+<!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

@@ -0,0 +1,57 @@
+<!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

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

gradio_cache/1/textured_mesh.html

@@ -0,0 +1,40 @@
+<!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

@@ -0,0 +1,57 @@
+<!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

@@ -0,0 +1,57 @@
+<!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

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

gradio_cache/3/textured_mesh.html

@@ -0,0 +1,40 @@
+<!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

@@ -0,0 +1,57 @@
+<!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

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

gradio_cache/4/textured_mesh.html

@@ -0,0 +1,40 @@
+<!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

@@ -0,0 +1,57 @@
+<!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>

hg_app.py

@@ -431,6 +431,6 @@ if __name__ == '__main__':
     app.mount("/static", StaticFiles(directory=static_dir), name="static")
 
     demo = build_app()
-    demo.queue(max_size=1)
+    demo.queue(max_size=10)
     app = gr.mount_gradio_app(app, demo, path="/")
     uvicorn.run(app, host=IP, port=PORT)

hy3dgen/.ipynb_checkpoints/text2image-checkpoint.py

@@ -0,0 +1,92 @@
+# 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