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Parent(s):
31fcf48
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app.py
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@@ -1,9 +1,10 @@
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import gradio as gr
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import spaces
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-
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import os
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from typing import *
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import imageio
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import uuid
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from PIL import Image
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@@ -37,11 +38,13 @@ def image_to_3d(image: Image.Image) -> Tuple[dict, str]:
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str: The path to the video of the 3D model.
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"""
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outputs = pipeline(image, formats=["gaussian", "mesh"], preprocess_image=False)
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video = render_utils.render_video(outputs['gaussian'][0])['color']
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model_id = uuid.uuid4()
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video_path = f"/tmp/Trellis-demo/{model_id}.mp4"
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os.makedirs(os.path.dirname(video_path), exist_ok=True)
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imageio.mimsave(video_path, video, fps=
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model = {'gaussian': outputs['gaussian'][0], 'mesh': outputs['mesh'][0], 'model_id': model_id}
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return model, video_path
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@@ -74,18 +77,25 @@ def deactivate_button() -> gr.Button:
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with gr.Blocks() as demo:
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with gr.Row():
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with gr.Column():
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image_prompt = gr.Image(label="Image Prompt", image_mode="RGBA", type="pil", height=300)
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generate_btn = gr.Button("Generate"
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mesh_simplify = gr.Slider(0.9, 0.98, label="Simplify", value=0.95, step=0.01)
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texture_size = gr.Slider(512, 2048, label="Texture Size", value=1024, step=512)
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extract_glb_btn = gr.Button("Extract GLB", interactive=False)
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with gr.Column():
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video_output = gr.Video(label="Generated 3D Asset", autoplay=True, loop=True, height=300)
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model_output =
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download_glb = gr.DownloadButton(label="Download GLB", interactive=False)
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# Example images at the bottom of the page
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@@ -96,8 +106,8 @@ with gr.Blocks() as demo:
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for image in os.listdir("assets/example_image")
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],
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inputs=[image_prompt],
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fn=lambda image:
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outputs=[image_prompt
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run_on_click=True,
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examples_per_page=64,
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)
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@@ -109,14 +119,6 @@ with gr.Blocks() as demo:
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preprocess_image,
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inputs=[image_prompt],
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outputs=[image_prompt],
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).then(
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activate_button,
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outputs=[generate_btn],
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)
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image_prompt.clear(
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deactivate_button,
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outputs=[generate_btn],
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)
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generate_btn.click(
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import gradio as gr
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import spaces
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from gradio_litmodel3d import LitModel3D
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import os
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from typing import *
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import numpy as np
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import imageio
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import uuid
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from PIL import Image
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str: The path to the video of the 3D model.
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"""
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outputs = pipeline(image, formats=["gaussian", "mesh"], preprocess_image=False)
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video = render_utils.render_video(outputs['gaussian'][0], num_frames=120)['color']
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video_geo = render_utils.render_video(outputs['mesh'][0], num_frames=120)['normal']
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video = [np.concatenate([video[i], video_geo[i]], axis=1) for i in range(len(video))]
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model_id = uuid.uuid4()
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video_path = f"/tmp/Trellis-demo/{model_id}.mp4"
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os.makedirs(os.path.dirname(video_path), exist_ok=True)
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imageio.mimsave(video_path, video, fps=15)
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model = {'gaussian': outputs['gaussian'][0], 'mesh': outputs['mesh'][0], 'model_id': model_id}
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return model, video_path
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with gr.Blocks() as demo:
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gr.Markdown("""
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## Image to 3D Asset with [TRELLIS](https://trellis3d.github.io/)
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* Upload an image and click "Generate" to create a 3D asset. If the image has alpha channel, it be used as the mask. Otherwise, we use `rembg` to remove the background.
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* If you find the generated 3D asset satisfactory, click "Extract GLB" to extract the GLB file and download it.
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""")
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with gr.Row():
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with gr.Column():
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image_prompt = gr.Image(label="Image Prompt", image_mode="RGBA", type="pil", height=300)
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generate_btn = gr.Button("Generate")
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gr.Markdown("GLB Extraction Parameters:")
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mesh_simplify = gr.Slider(0.9, 0.98, label="Simplify", value=0.95, step=0.01)
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texture_size = gr.Slider(512, 2048, label="Texture Size", value=1024, step=512)
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extract_glb_btn = gr.Button("Extract GLB", interactive=False)
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with gr.Column():
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video_output = gr.Video(label="Generated 3D Asset", autoplay=True, loop=True, height=300)
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model_output = LitModel3D(label="Extracted GLB", exposure=20.0, height=300)
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download_glb = gr.DownloadButton(label="Download GLB", interactive=False)
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# Example images at the bottom of the page
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for image in os.listdir("assets/example_image")
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],
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inputs=[image_prompt],
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fn=lambda image: preprocess_image(image),
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outputs=[image_prompt],
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run_on_click=True,
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examples_per_page=64,
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)
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preprocess_image,
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inputs=[image_prompt],
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outputs=[image_prompt],
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)
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generate_btn.click(
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requirements.txt
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@@ -22,6 +22,7 @@ xformers==0.0.27.post2
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kaolin==0.17.0
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spconv-cu120==2.3.6
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transformers==4.46.3
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https://github.com/Dao-AILab/flash-attention/releases/download/v2.7.0.post2/flash_attn-2.7.0.post2+cu12torch2.4cxx11abiFALSE-cp310-cp310-linux_x86_64.whl
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https://huggingface.co/spaces/JeffreyXiang/TRELLIS/resolve/main/wheels/diff_gaussian_rasterization-0.0.0-cp310-cp310-linux_x86_64.whl?download=true
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https://huggingface.co/spaces/JeffreyXiang/TRELLIS/resolve/main/wheels/nvdiffrast-0.3.3-py3-none-any.whl?download=true
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kaolin==0.17.0
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spconv-cu120==2.3.6
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transformers==4.46.3
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gradio_litmodel3d==0.0.1
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https://github.com/Dao-AILab/flash-attention/releases/download/v2.7.0.post2/flash_attn-2.7.0.post2+cu12torch2.4cxx11abiFALSE-cp310-cp310-linux_x86_64.whl
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https://huggingface.co/spaces/JeffreyXiang/TRELLIS/resolve/main/wheels/diff_gaussian_rasterization-0.0.0-cp310-cp310-linux_x86_64.whl?download=true
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https://huggingface.co/spaces/JeffreyXiang/TRELLIS/resolve/main/wheels/nvdiffrast-0.3.3-py3-none-any.whl?download=true
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wheels/diff_gaussian_rasterization-0.0.0-cp310-cp310-linux_x86_64.whl
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Binary files a/wheels/diff_gaussian_rasterization-0.0.0-cp310-cp310-linux_x86_64.whl and b/wheels/diff_gaussian_rasterization-0.0.0-cp310-cp310-linux_x86_64.whl differ
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