Spaces:
Runtime error
Runtime error
| import gradio as gr | |
| from app import demo as app | |
| import os | |
| _docs = {'Model4DGS': {'description': 'Component allows users to upload or view 4D Gaussian Splatting files (.splat).', 'members': {'__init__': {'value': {'type': 'str | Callable | None', 'default': 'None', 'description': 'path to (.splat) file to show in model4DGS viewer. If callable, the function will be called whenever the app loads to set the initial value of the component.'}, 'height': {'type': 'int | None', 'default': 'None', 'description': 'height of the model4DGS component, in pixels.'}, 'label': {'type': 'str | None', 'default': 'None', 'description': None}, 'show_label': {'type': 'bool | None', 'default': 'None', 'description': None}, 'every': {'type': 'float | None', 'default': 'None', 'description': None}, 'container': {'type': 'bool', 'default': 'True', 'description': None}, 'scale': {'type': 'int | None', 'default': 'None', 'description': None}, 'min_width': {'type': 'int', 'default': '160', 'description': None}, 'interactive': {'type': 'bool | None', 'default': 'None', 'description': None}, 'visible': {'type': 'bool', 'default': 'True', 'description': None}, 'elem_id': {'type': 'str | None', 'default': 'None', 'description': None}, 'elem_classes': {'type': 'list[str] | str | None', 'default': 'None', 'description': None}, 'render': {'type': 'bool', 'default': 'True', 'description': None}}, 'postprocess': {'value': {'type': 'List[str] | str | None', 'description': "The output data received by the component from the user's function in the backend."}}, 'preprocess': {'return': {'type': 'List[str] | None', 'description': "The preprocessed input data sent to the user's function in the backend."}, 'value': None}}, 'events': {'change': {'type': None, 'default': None, 'description': 'Triggered when the value of the Model4DGS changes either because of user input (e.g. a user types in a textbox) OR because of a function update (e.g. an image receives a value from the output of an event trigger). See `.input()` for a listener that is only triggered by user input.'}, 'upload': {'type': None, 'default': None, 'description': 'This listener is triggered when the user uploads a file into the Model4DGS.'}, 'edit': {'type': None, 'default': None, 'description': 'This listener is triggered when the user edits the Model4DGS (e.g. image) using the built-in editor.'}, 'clear': {'type': None, 'default': None, 'description': 'This listener is triggered when the user clears the Model4DGS using the X button for the component.'}}}, '__meta__': {'additional_interfaces': {}, 'user_fn_refs': {'Model4DGS': []}}} | |
| abs_path = os.path.join(os.path.dirname(__file__), "css.css") | |
| with gr.Blocks( | |
| css=abs_path, | |
| theme=gr.themes.Default( | |
| font_mono=[ | |
| gr.themes.GoogleFont("Inconsolata"), | |
| "monospace", | |
| ], | |
| ), | |
| ) as demo: | |
| gr.Markdown( | |
| """ | |
| # `gradio_model4dgs` | |
| <div style="display: flex; gap: 7px;"> | |
| <a href="https://pypi.org/project/gradio_model4dgs/" target="_blank"><img alt="PyPI - Version" src="https://img.shields.io/pypi/v/gradio_model4dgs"></a> | |
| </div> | |
| Python library for easily interacting with trained machine learning models | |
| """, elem_classes=["md-custom"], header_links=True) | |
| app.render() | |
| gr.Markdown( | |
| """ | |
| ## Installation | |
| ```bash | |
| pip install gradio_model4dgs | |
| ``` | |
| ## Usage | |
| ```python | |
| import gradio as gr | |
| from gradio_model4dgs import Model4DGS | |
| import os | |
| from PIL import Image | |
| import hashlib | |
| def check_img_input(control_image): | |
| if control_image is None: | |
| raise gr.Error("Please select or upload an input image") | |
| if __name__ == "__main__": | |
| _TITLE = '''DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation''' | |
| _DESCRIPTION = ''' | |
| <div> | |
| <a style="display:inline-block" href="https://jiawei-ren.github.io/projects/dreamgaussian4d/"><img src='https://img.shields.io/badge/public_website-8A2BE2'></a> | |
| <a style="display:inline-block; margin-left: .5em" href="https://arxiv.org/abs/2312.17142"><img src="https://img.shields.io/badge/2309.16653-f9f7f7?logo=data:image/png;base64,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"></a> | |
| <a style="display:inline-block; margin-left: .5em" href='https://github.com/jiawei-ren/dreamgaussian4d'><img src='https://img.shields.io/github/stars/jiawei-ren/dreamgaussian4d?style=social'/></a> | |
| </div> | |
| We introduce DreamGaussian4D, an efficient 4D generation framework that builds on 4D Gaussian Splatting representation. | |
| ''' | |
| # load images in 'assets' folder as examples | |
| image_dir = os.path.join(os.path.dirname(__file__), "assets") | |
| examples_img = None | |
| if os.path.exists(image_dir) and os.path.isdir(image_dir) and os.listdir(image_dir): | |
| examples_4d = [os.path.join(image_dir, file) for file in os.listdir(image_dir) if file.endswith('.ply')] | |
| examples_img = [os.path.join(image_dir, file) for file in os.listdir(image_dir) if file.endswith('.png')] | |
| else: | |
| examples_4d = [os.path.join(os.path.dirname(__file__), example) for example in Model4DGS().example_inputs()] | |
| def optimize(image_block: Image.Image): | |
| # temporarily only show tiger | |
| return f'{os.path.join(os.path.dirname(__file__), "logs")}/tiger.glb', examples_4d | |
| # Compose demo layout & data flow | |
| with gr.Blocks(title=_TITLE, theme=gr.themes.Soft()) as demo: | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| gr.Markdown('# ' + _TITLE) | |
| gr.Markdown(_DESCRIPTION) | |
| with gr.Row(variant='panel'): | |
| left_column = gr.Column(scale=5) | |
| with left_column: | |
| image_block = gr.Image(type='pil', image_mode='RGBA', height=290, label='Input image') | |
| preprocess_chk = gr.Checkbox(True, | |
| label='Preprocess image automatically (remove background and recenter object)') | |
| with gr.Column(scale=5): | |
| obj3d = gr.Model3D(clear_color=[0.0, 0.0, 0.0, 0.0], label="3D Model (Final)") | |
| obj4d = Model4DGS(label="4D Model") | |
| with left_column: | |
| gr.Examples( | |
| examples=examples_img, # NOTE: elements must match inputs list! | |
| inputs=image_block, | |
| outputs=obj3d, | |
| fn=optimize, | |
| label='Examples (click one of the images below to start)', | |
| examples_per_page=40 | |
| ) | |
| img_run_btn = gr.Button("Generate 4D") | |
| # if there is an input image, continue with inference | |
| # else display an error message | |
| img_run_btn.click(check_img_input, inputs=[image_block], queue=False).success( | |
| optimize, inputs=[image_block], outputs=[obj3d, obj4d]) | |
| if __name__ == "__main__": | |
| demo.launch(share=True) | |
| ``` | |
| """, elem_classes=["md-custom"], header_links=True) | |
| gr.Markdown(""" | |
| ## `Model4DGS` | |
| ### Initialization | |
| """, elem_classes=["md-custom"], header_links=True) | |
| gr.ParamViewer(value=_docs["Model4DGS"]["members"]["__init__"], linkify=[]) | |
| gr.Markdown("### Events") | |
| gr.ParamViewer(value=_docs["Model4DGS"]["events"], linkify=['Event']) | |
| gr.Markdown(""" | |
| ### User function | |
| The impact on the users predict function varies depending on whether the component is used as an input or output for an event (or both). | |
| - When used as an Input, the component only impacts the input signature of the user function. | |
| - When used as an output, the component only impacts the return signature of the user function. | |
| The code snippet below is accurate in cases where the component is used as both an input and an output. | |
| - **As input:** Is passed, the preprocessed input data sent to the user's function in the backend. | |
| - **As output:** Should return, the output data received by the component from the user's function in the backend. | |
| ```python | |
| def predict( | |
| value: List[str] | None | |
| ) -> List[str] | str | None: | |
| return value | |
| ``` | |
| """, elem_classes=["md-custom", "Model4DGS-user-fn"], header_links=True) | |
| demo.load(None, js=r"""function() { | |
| const refs = {}; | |
| const user_fn_refs = { | |
| Model4DGS: [], }; | |
| requestAnimationFrame(() => { | |
| Object.entries(user_fn_refs).forEach(([key, refs]) => { | |
| if (refs.length > 0) { | |
| const el = document.querySelector(`.${key}-user-fn`); | |
| if (!el) return; | |
| refs.forEach(ref => { | |
| el.innerHTML = el.innerHTML.replace( | |
| new RegExp("\\b"+ref+"\\b", "g"), | |
| `<a href="#h-${ref.toLowerCase()}">${ref}</a>` | |
| ); | |
| }) | |
| } | |
| }) | |
| Object.entries(refs).forEach(([key, refs]) => { | |
| if (refs.length > 0) { | |
| const el = document.querySelector(`.${key}`); | |
| if (!el) return; | |
| refs.forEach(ref => { | |
| el.innerHTML = el.innerHTML.replace( | |
| new RegExp("\\b"+ref+"\\b", "g"), | |
| `<a href="#h-${ref.toLowerCase()}">${ref}</a>` | |
| ); | |
| }) | |
| } | |
| }) | |
| }) | |
| } | |
| """) | |
| demo.launch() | |