# `gradio_model4dgs`

Python library for easily interacting with trained machine learning models ## Installation ```bash pip install gradio_model4dgs ``` ## Usage ```python 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") if __name__ == "__main__": demo.launch(share=True) ``` ## `Model4DGS` ### Initialization

name	type	default	description
`value`	```python str \| Callable \| None ```	`None`	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`	```python int \| None ```	`None`	height of the model4DGS component, in pixels.
`label`	```python str \| None ```	`None`	None
`show_label`	```python bool \| None ```	`None`	None
`every`	```python float \| None ```	`None`	None
`container`	```python bool ```	`True`	None
`scale`	```python int \| None ```	`None`	None
`min_width`	```python int ```	`160`	None
`interactive`	```python bool \| None ```	`None`	None
`visible`	```python bool ```	`True`	None
`elem_id`	```python str \| None ```	`None`	None
`elem_classes`	```python list[str] \| str \| None ```	`None`	None
`render`	```python bool ```	`True`	None

### Events | name | description | |:-----|:------------| | `change` | 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` | This listener is triggered when the user uploads a file into the Model4DGS. | | `edit` | This listener is triggered when the user edits the Model4DGS (e.g. image) using the built-in editor. | | `clear` | This listener is triggered when the user clears the Model4DGS using the X button for the component. | ### 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 output:** Is passed, the preprocessed input data sent to the user's function in the backend. - **As input:** 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 ```