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README.md +22 -65
app.py +8 -65
space.py +10 -66
src/README.md +22 -65
src/backend/gradio_model4dgs/model4dgs.py +2 -0
src/backend/gradio_model4dgs/templates/component/index.js +0 -0
src/demo/app.py +8 -64
src/demo/space.py +10 -66
src/frontend/Index.svelte +2 -0
src/frontend/shared/Model4DGS.svelte +3 -1
src/pyproject.toml +1 -1

README.md CHANGED Viewed

@@ -26,73 +26,17 @@ pip install gradio_model4dgs
 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)
@@ -125,6 +69,19 @@ str | Callable | None
 <td align="left">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.</td>
 </tr>
 <tr>
 <td align="left"><code>height</code></td>
 <td align="left" style="width: 25%;">

 import gradio as gr
 from gradio_model4dgs import Model4DGS
 import os
+image_dir = os.path.join(os.path.dirname(__file__), "assets")
+if os.path.exists(image_dir) and os.path.isdir(image_dir) and os.listdir(image_dir):
+    examples = [os.path.join(image_dir, file) for file in os.listdir(image_dir)]
+else:
+    examples = [os.path.join(os.path.dirname(__file__), example) for example in Model4DGS().example_inputs()]
+with gr.Blocks() as demo:
+    with gr.Row():
+        Model4DGS(value=examples, label="4D Model", fps=8)
 if __name__ == "__main__":
     demo.launch(share=True)
 <td align="left">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.</td>
 </tr>
+<tr>
+<td align="left"><code>fps</code></td>
+<td align="left" style="width: 25%;">
+```python
+float
+```
+</td>
+<td align="left"><code>8</code></td>
+<td align="left">None</td>
+</tr>
 <tr>
 <td align="left"><code>height</code></td>
 <td align="left" style="width: 25%;">

app.py CHANGED Viewed

@@ -1,74 +1,17 @@
 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 = '''DreamGaussian4D: Generative 4D Gaussian Splatting'''
-    _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_rgba.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,
-                    cache_examples=False,
-                    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)

 import gradio as gr
 from gradio_model4dgs import Model4DGS
 import os
+image_dir = os.path.join(os.path.dirname(__file__), "assets")
+if os.path.exists(image_dir) and os.path.isdir(image_dir) and os.listdir(image_dir):
+    examples = [os.path.join(image_dir, file) for file in os.listdir(image_dir)]
+else:
+    examples = [os.path.join(os.path.dirname(__file__), example) for example in Model4DGS().example_inputs()]
+with gr.Blocks() as demo:
+    with gr.Row():
+        Model4DGS(value=examples, label="4D Model", fps=8)
 if __name__ == "__main__":
     demo.launch(share=True)

space.py CHANGED Viewed

@@ -3,7 +3,7 @@ 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")
@@ -41,73 +41,17 @@ pip install gradio_model4dgs
 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,iVBORw0KGgoAAAANSUhEUgAAADcAAABMCAYAAADJPi9EAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAuIwAALiMBeKU/dgAAABl0RVh0U29mdHdhcmUAd3d3Lmlua3NjYXBlLm9yZ5vuPBoAAAa2SURBVHja3Zt7bBRFGMAXUCDGF4rY7m7bAwuhlggKStFgLBgFEkCIIRJEEoOBYHwRFYKilUgEReVNJEGCJJpehHI3M9vZvd3bUP1DjNhEIRQQsQgSHiJgQZ5dv7krWEvvdmZ7d7vHJN+ft/f99pv5XvOtJMFCqvoCUpTdIEeRLC+L9Ox5i3Q9LACaCeK0kXoSChVcD3C/tQPHpAEsquQ73IkUcEz2kcLCknyGW5MGjkljRFVL8xJOKyi4CwCOuQAeAkfTP1+tNxLkogvgEbDgffkJqKqvuMA5ifOpqg/5qWecRstNg7xoUTI1Fovdxg8oy2s5AP8CGeYHmGngeZaOL4I4LXLcpHg4149/GDz4xqgsb+UAbMKKUpkrqHA43MUyyJpWUK0EHeG2YKRXr7tB+QMcgGewLD+ebTDbtrtbBt7UPlhS4rV4IvcDI7J8P1OeA/AcAI7LHljN7aB8XTowJmZt9EFRD/o0SDMH4HlwMhMyDWZZSAHFf3YDs3RS49WDLuaAY3IJq+qzmQKLxXAZKN7oDoYbdV3v5elPqiSpMyiOuAEVZVqHXb1OhloUH+MA+ztO0cAO/RkrfyBE7OAEbAZvO8vzVtTRWFD6DAfY5biBM3PWiaL0a4lvXICwnV8WjmE6ntYmhqX2jjp5LbMZjCw/wbYeN6CizOa2GMVzQOlmHjB4Ceuyk6LJ8huccEmR5Xddg7OOV/NAtchW+E3XbOag60QA4Qwuarca0bRuEJyr+cFQwzcY98huxhAKdQelt4kAQpj4qJ3gvFXAYn+aJumXk1yPlpQUgtIHhbYoFMUstNRRWgjnpl4A7IKlayNymqFHFaWCpV9CFry3LGxR1CgA5kB5M8OX2goApwpaz6mdOMGxtAgXWJySxb4WuQD4qTDgU+N5AAnzpr7ChSWpCyisiQJqY0Y7FtmSKpbV23b45kC0KHBxcQ9QeI8w4KgnHRPVtIU7rOtbioLVg5Hl/qDwSVFAMqLSMSObroCdZYlzIJtMRFVHCaRo/wFWPgaAXzdbBpkc2A4aKzCNd97+URQuESYGDDhIVfWOQIKZJu4D2+oXlgDTV1865gUQZDts756BArMNMoR1oa46BYqbyPixZz1ZUFV3sgwoGBajuBKATl3btIn8QYYMuezRgrsiRUWyr2BxA40EkPMpA/Hm6gbUu7fjEXA3azP6AsbKD9bxdUuhjM9W7fII52BF+daRpE4+WA3P501+jbfmHvQKyFqMuXf7Ot4mkN2fr50y+bRH61X7AXdUpHSxaPQ4GVbR5AGw3g+434XgQGKfr72I+vQRhfsu92dOx7WicInzt3CBg1RVpMm0NveWo2SqFzgmdNZMbriILD+S+zoueWf2vSdAipzacWN5nMl6XxNlUHa/J8DoJodUDE0HR8Ll5V0lPxcrLEHZPV4AzS83OLis7FowVa3RSku7BSNxJqQAlN3hBTC2apmDSkpaw22wJemGQFUG7J4MlP3JC6A+f96V7vRyX9It3nzT/GrjIU8edM7rMSnIi10f476lzbE1K7yEiEuWro0OJBguLCwDuFOJc1Na6sRWL/cCeMIwUN9ggSVbe3v/5/EgzTKWLvEAiBrYRUkgwNI2ZaFQNT75UDxEUEx97zYnzpmiLEmbaYCbNxYtFAb0/Z4AztgUrhyxuNgxPnhfHFDHz/vTgFWUQZxTRkkJhQ6YNdVUEPAfO6ZV5BRss6LcCVb7VaAma9giy0XJZBt9IQh42NY0NSdgbLIPlLUF6rEdrdt0CUCK1wsCbkcI3ZSLc7ZSwGLbmJXbPsNxnE5xilYKAobZ77LpGZ8TAIun+/iCKQoF71IxQDI3K2CCd+ARNvXg9sykBcnHAoCZG4u66hlDoQLe6QV4CRtFSxZQ+D0BwNO2jgdkzoGoah1nj3FVlSR19taTSYxI8QLut23U8dsgzqHulJNCQpcqBnpTALCuQ6NSYLHpmR5i42gZzuIdcrMMvMJbQlxe3jXxyZnLACl7ARm/FjPIDOY8ODtpM71sxwfcZpvBeUzKWmfNINM5AS+wO0Khh7dMqKccu4+qatarZjYAwDlgetzStHtEt+XedsBOQtU9XMrRgjg4KTnc5nr+dmqadit/4C4uLm8DuA9koJTj1TL7fI5nDL+qqoo/FLGAzL7dYT17PzvAcQONYSUQRxW/QMrHZVIyik0ZuQA2mzp+Ji8BW4YM3Mbzm9inaHkJCGfrUZZjujiYailfFwA8DHIy3acwUj4v9vUVa+SmgNsl5fuyDTKovW9/IAmfLV0Pi2UncA515kjYdrwC9i9rpuHiq3JwtAAAAABJRU5ErkJggg=="></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)

 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.'}, 'fps': {'type': 'float', 'default': '8', 'description': None}, '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")
 import gradio as gr
 from gradio_model4dgs import Model4DGS
 import os
+image_dir = os.path.join(os.path.dirname(__file__), "assets")
+if os.path.exists(image_dir) and os.path.isdir(image_dir) and os.listdir(image_dir):
+    examples = [os.path.join(image_dir, file) for file in os.listdir(image_dir)]
+else:
+    examples = [os.path.join(os.path.dirname(__file__), example) for example in Model4DGS().example_inputs()]
+with gr.Blocks() as demo:
+    with gr.Row():
+        Model4DGS(value=examples, label="4D Model", fps=8)
 if __name__ == "__main__":
     demo.launch(share=True)

src/README.md CHANGED Viewed

@@ -26,73 +26,17 @@ pip install gradio_model4dgs
 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)
@@ -125,6 +69,19 @@ str | Callable | None
 <td align="left">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.</td>
 </tr>
 <tr>
 <td align="left"><code>height</code></td>
 <td align="left" style="width: 25%;">

 import gradio as gr
 from gradio_model4dgs import Model4DGS
 import os
+image_dir = os.path.join(os.path.dirname(__file__), "assets")
+if os.path.exists(image_dir) and os.path.isdir(image_dir) and os.listdir(image_dir):
+    examples = [os.path.join(image_dir, file) for file in os.listdir(image_dir)]
+else:
+    examples = [os.path.join(os.path.dirname(__file__), example) for example in Model4DGS().example_inputs()]
+with gr.Blocks() as demo:
+    with gr.Row():
+        Model4DGS(value=examples, label="4D Model", fps=8)
 if __name__ == "__main__":
     demo.launch(share=True)
 <td align="left">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.</td>
 </tr>
+<tr>
+<td align="left"><code>fps</code></td>
+<td align="left" style="width: 25%;">
+```python
+float
+```
+</td>
+<td align="left"><code>8</code></td>
+<td align="left">None</td>
+</tr>
 <tr>
 <td align="left"><code>height</code></td>
 <td align="left" style="width: 25%;">

src/backend/gradio_model4dgs/model4dgs.py CHANGED Viewed

@@ -32,6 +32,7 @@ class Model4DGS(Component):
         self,
         value: str | Callable | None = None,
         *,
         height: int | None = None,
         label: str | None = None,
         show_label: bool | None = None,
@@ -51,6 +52,7 @@ class Model4DGS(Component):
             height: height of the model4DGS component, in pixels.
         """
         self.height = height
         super().__init__(
             label=label,
             every=every,

         self,
         value: str | Callable | None = None,
         *,
+        fps: float = 8,
         height: int | None = None,
         label: str | None = None,
         show_label: bool | None = None,
             height: height of the model4DGS component, in pixels.
         """
         self.height = height
+        self.fps=fps
         super().__init__(
             label=label,
             every=every,

src/backend/gradio_model4dgs/templates/component/index.js CHANGED Viewed

The diff for this file is too large to render. See raw diff

src/demo/app.py CHANGED Viewed

@@ -1,73 +1,17 @@
 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)

 import gradio as gr
 from gradio_model4dgs import Model4DGS
 import os
+image_dir = os.path.join(os.path.dirname(__file__), "assets")
+if os.path.exists(image_dir) and os.path.isdir(image_dir) and os.listdir(image_dir):
+    examples = [os.path.join(image_dir, file) for file in os.listdir(image_dir)]
+else:
+    examples = [os.path.join(os.path.dirname(__file__), example) for example in Model4DGS().example_inputs()]
+with gr.Blocks() as demo:
+    with gr.Row():
+        Model4DGS(value=examples, label="4D Model", fps=8)
 if __name__ == "__main__":
     demo.launch(share=True)

src/demo/space.py CHANGED Viewed

@@ -3,7 +3,7 @@ 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")
@@ -41,73 +41,17 @@ pip install gradio_model4dgs
 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)

 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.'}, 'fps': {'type': 'float', 'default': '8', 'description': None}, '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")
 import gradio as gr
 from gradio_model4dgs import Model4DGS
 import os
+image_dir = os.path.join(os.path.dirname(__file__), "assets")
+if os.path.exists(image_dir) and os.path.isdir(image_dir) and os.listdir(image_dir):
+    examples = [os.path.join(image_dir, file) for file in os.listdir(image_dir)]
+else:
+    examples = [os.path.join(os.path.dirname(__file__), example) for example in Model4DGS().example_inputs()]
+with gr.Blocks() as demo:
+    with gr.Row():
+        Model4DGS(value=examples, label="4D Model", fps=8)
 if __name__ == "__main__":
     demo.launch(share=True)

src/frontend/Index.svelte CHANGED Viewed

@@ -26,6 +26,7 @@
     export let min_width: number | undefined = undefined;
     export let gradio: Gradio;
     export let height: number | undefined = undefined;
     let dragging = false;
 </script>
@@ -53,6 +54,7 @@
             {show_label}
             {root}
             {proxy_url}
         />
     {:else}
         <BlockLabel {show_label} Icon={File} label={label || "Splat"} />

     export let min_width: number | undefined = undefined;
     export let gradio: Gradio;
     export let height: number | undefined = undefined;
+    export let fps=8;
     let dragging = false;
 </script>
             {show_label}
             {root}
             {proxy_url}
+            {fps}
         />
     {:else}
         <BlockLabel {show_label} Icon={File} label={label || "Splat"} />

src/frontend/shared/Model4DGS.svelte CHANGED Viewed

@@ -13,6 +13,8 @@
     export let label = "";
     export let show_label: boolean;
     export let i18n: I18nFormatter;
     let currFrameIndex = 0;
     let NUM_FRAMES = 1;
@@ -55,7 +57,7 @@
                         requestAnimationFrame(update);
                         const timeDelta = performance.now() - startTime;
-                        if (timeDelta > 150) {
                             const prevSplatScene = viewer.getSplatScene(currFrameIndex);
                             prevSplatScene.scale.copy(invisible_scale);

     export let label = "";
     export let show_label: boolean;
     export let i18n: I18nFormatter;
+    export let fps=8;
     let currFrameIndex = 0;
     let NUM_FRAMES = 1;
                         requestAnimationFrame(update);
                         const timeDelta = performance.now() - startTime;
+                        if (timeDelta > 1000/fps) {
                             const prevSplatScene = viewer.getSplatScene(currFrameIndex);
                             prevSplatScene.scale.copy(invisible_scale);

src/pyproject.toml CHANGED Viewed

@@ -8,7 +8,7 @@ build-backend = "hatchling.build"
 [project]
 name = "gradio_model4dgs"
-version = "0.0.4"
 description = "Python library for easily interacting with trained machine learning models"
 readme = "README.md"
 license = "MIT"

 [project]
 name = "gradio_model4dgs"
+version = "0.0.5"
 description = "Python library for easily interacting with trained machine learning models"
 readme = "README.md"
 license = "MIT"