test.md

gradio_imageslider

None

Python library for easily interacting with trained machine learning models

Installation

pip install gradio_imageslider

Usage

import gradio as gr
from gradio_imageslider import ImageSlider


def fn(im):
    return im


with gr.Blocks() as demo:
    img1 = ImageSlider()

if __name__ == "__main__":
    demo.launch()

ImageSlider

Initialization

name	type	default	description
value	tuple[str, str] | tuple[PIL.Image.Image, PIL.Image.Image] | tuple[numpy.ndarray, numpy.ndarray] | None	None	A PIL Image, numpy array, path or URL for the default value that Image component is going to take. If callable, the function will be called whenever the app loads to set the initial value of the component.
height	int | None	None	Height of the displayed image in pixels.
width	int | None	None	Width of the displayed image in pixels.
type	"numpy" | "pil" | "filepath"	"numpy"	The format the image is converted to before being passed into the prediction function. "numpy" converts the image to a numpy array with shape (height, width, 3) and values from 0 to 255, "pil" converts the image to a PIL image object, "filepath" passes a str path to a temporary file containing the image.
label	str | None	None	component name in interface.
every	float | None	None	If `value` is a callable, run the function 'every' number of seconds while the client connection is open. Has no effect otherwise. Queue must be enabled. The event can be accessed (e.g. to cancel it) via this component's .load_event attribute.
show_label	bool | None	None	if True, will display label.
show_download_button	bool	True	If True, will display button to download image.
container	bool	True	If True, will place the component in a container - providing some extra padding around the border.
scale	int | None	None	relative width compared to adjacent Components in a Row. For example, if Component A has scale=2, and Component B has scale=1, A will be twice as wide as B. Should be an integer.
min_width	int	160	minimum pixel width, will wrap if not sufficient screen space to satisfy this value. If a certain scale value results in this Component being narrower than min_width, the min_width parameter will be respected first.
interactive	bool | None	None	if True, will allow users to upload and edit an image; if False, can only be used to display images. If not provided, this is inferred based on whether the component is used as an input or output.
visible	bool	True	If False, component will be hidden.
elem_id	str | None	None	An optional string that is assigned as the id of this component in the HTML DOM. Can be used for targeting CSS styles.
elem_classes	list[str] | str | None	None	An optional list of strings that are assigned as the classes of this component in the HTML DOM. Can be used for targeting CSS styles.
show_share_button	bool | None	None	If True, will show a share icon in the corner of the component that allows user to share outputs to Hugging Face Spaces Discussions. If False, icon does not appear. If set to None (default behavior), then the icon appears if this Gradio app is launched on Spaces, but not otherwise.
position	int	0.5	The position of the slider, between 0 and 1.

Events

name	description
change	Triggered when the value of the ImageSlider 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 ImageSlider.

User function

• As output: Is passed, tuple of images in the requested format..
• As input: Should return, image as a numpy array, PIL Image, string/Path filepath, or string URL.

def predict(
    value: tuple[str, str]
    | tuple[PIL.Image.Image, PIL.Image.Image]
    | tuple[numpy.ndarray, numpy.ndarray]
    | None
) -> tuple[str, str]
    | tuple[PIL.Image.Image, PIL.Image.Image]
    | tuple[numpy.ndarray, numpy.ndarray]
    | None:
    return value