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import gradio as gr |
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import os |
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from util.instantmesh import generate_mvs, make3d, preprocess, check_input_image |
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from util.text_img import generate_txttoimg, check_prompt, generate_imgtoimg, update_image |
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_CITE_ = r""" |
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```bibtex |
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@article{xu2024instantmesh, |
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title={InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Models}, |
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author={Xu, Jiale and Cheng, Weihao and Gao, Yiming and Wang, Xintao and Gao, Shenghua and Shan, Ying}, |
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journal={arXiv preprint arXiv:2404.07191}, |
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year={2024} |
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} |
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``` |
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""" |
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theme = gr.themes.Soft( |
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primary_hue="orange", |
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secondary_hue="gray", |
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neutral_hue="slate", |
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font=['Montserrat', gr.themes.GoogleFont('ui-sans-serif'), 'system-ui', 'sans-serif'], |
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) |
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with gr.Blocks(theme=theme) as GenDemo: |
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gen_image_var = gr.State() |
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with gr.Tab("Text to Image Generator"): |
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with gr.Row(variant="panel"): |
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with gr.Column(): |
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prompt = gr.Textbox(label="Enter a discription of a shoe") |
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select = gr.Dropdown(label="Select a controlnet model", choices=["Depth","Normal"]) |
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controlNet_image = gr.Image(label="Enter an image of a shoe, that you want to use as a reference", type='pil') |
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gr.Examples( |
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examples=[ |
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os.path.join("examples", img_name) for img_name in sorted(os.listdir("examples")) |
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], |
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inputs=[controlNet_image], |
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label="Examples", |
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cache_examples=False, |
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) |
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with gr.Column(): |
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button_txt = gr.Button("Generate Image", elem_id="generateIm", variant="primary") |
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gen_image = gr.Image(label="Generated Image", image_mode="RGBA", type='pil', show_download_button=True, show_label=False) |
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button_txt.click(check_prompt, inputs=[prompt]).success(generate_txttoimg, inputs=[prompt, controlNet_image, select], outputs=[gen_image]).success(update_image, inputs=[gen_image], outputs=[gen_image_var]) |
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with gr.Tab("Image to 3D Model Generator"): |
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with gr.Row(variant="panel"): |
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with gr.Column(): |
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with gr.Row(): |
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processed_image = gr.Image( |
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label="Processed Image", |
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image_mode="RGBA", |
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type="pil", |
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interactive=False |
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) |
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with gr.Row(): |
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with gr.Group(): |
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do_remove_background = gr.Checkbox( |
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label="Remove Background", value=True |
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) |
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sample_seed = gr.Number(value=42, label="Seed Value", precision=0) |
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sample_steps = gr.Slider( |
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label="Sample Steps", |
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minimum=30, |
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maximum=75, |
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value=75, |
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step=5 |
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) |
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with gr.Row(): |
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submit = gr.Button("Generate", elem_id="generate", variant="primary") |
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with gr.Column(): |
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with gr.Row(): |
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with gr.Column(): |
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mv_show_images = gr.Image( |
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label="Generated Multi-views", |
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type="pil", |
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width=379, |
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interactive=False |
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) |
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with gr.Row(): |
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with gr.Tab("obj"): |
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output_model_obj = gr.Model3D( |
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label="Output Model (OBJ Format)", |
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interactive=False, |
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) |
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with gr.Tab("glb"): |
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output_model_glb = gr.Model3D( |
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label="Output Model (GLB Format)", |
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interactive=False, |
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) |
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with gr.Row(): |
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gr.Markdown('''Try a different <b>seed value</b> if the result is unsatisfying (Default: 42).''') |
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gr.Markdown(_CITE_) |
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mv_images = gr.State() |
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submit.click(fn=check_input_image, inputs=[gen_image_var]).success( |
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fn=preprocess, |
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inputs=[gen_image_var, do_remove_background], |
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outputs=[processed_image], |
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).success( |
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fn=generate_mvs, |
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inputs=[processed_image, sample_steps, sample_seed], |
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outputs=[mv_images, mv_show_images] |
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).success( |
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fn=make3d, |
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inputs=[mv_images], |
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outputs=[output_model_obj, output_model_glb] |
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) |
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GenDemo.launch() |
