`gradio_carousel`

Display a gallery of images in a carousel that autoscrolls 🎠

Installation

pip install gradio_carousel

Usage



import os

import gradio as gr
from gradio_carousel import Carousel

image_dir = os.path.join(os.path.dirname(__file__), "alligator_images")

images = [os.path.join(image_dir, file) for file in os.listdir(image_dir) if file.endswith((".jpg", ".jpeg", ".png"))]

with gr.Blocks() as demo:
    with gr.Row():
        Carousel(label="cool gators", value=images)  # carousel component with images


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

`Carousel`

Initialization

name	type	default	description
`value`	`list[ numpy.ndarray \| PIL.Image.Image \| str \| pathlib.Path \| tuple ] \| Callable \| None`	`None`	List of images to display in the gallery by default. If callable, the function will be called whenever the app loads to set the initial value of the component.
`label`	`str \| None`	`None`	The label for this component. Appears above the component and is also used as the header if there are a table of examples for this component. If None and used in a `gr.Interface`, the label will be the name of the parameter this component is assigned to.
`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.
`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.
`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.
`render`	`bool`	`True`	If False, component will not render be rendered in the Blocks context. Should be used if the intention is to assign event listeners now but render the component later.
`columns`	`int \| tuple \| None`	`2`	Represents the number of images that should be shown in one row, for each of the six standard screen sizes (<576px, <768px, <992px, <1200px, <1400px, >1400px). If fewer than 6 are given then the last will be used for all subsequent breakpoints
`rows`	`int \| tuple \| None`	`None`	Represents the number of rows in the image grid, for each of the six standard screen sizes (<576px, <768px, <992px, <1200px, <1400px, >1400px). If fewer than 6 are given then the last will be used for all subsequent breakpoints
`height`	`int \| float \| None`	`None`	The height of the gallery component, specified in pixels if a number is passed, or in CSS units if a string is passed. If more images are displayed than can fit in the height, a scrollbar will appear.
`allow_preview`	`bool`	`True`	If True, images in the gallery will be enlarged when they are clicked. Default is True.
`preview`	`bool \| None`	`None`	If True, Carousel will start in preview mode, which shows all of the images as thumbnails and allows the user to click on them to view them in full size. Only works if allow_preview is True.
`selected_index`	`int \| None`	`None`	The index of the image that should be initially selected. If None, no image will be selected at start. If provided, will set Carousel to preview mode unless allow_preview is set to False.
`object_fit`	`"contain" \| "cover" \| "fill" \| "none" \| "scale-down" \| None`	`None`	CSS object-fit property for the thumbnail images in the gallery. Can be "contain", "cover", "fill", "none", or "scale-down".
`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.
`show_download_button`	`bool \| None`	`True`	If True, will show a download button in the corner of the selected image. If False, the icon does not appear. Default is True.
`interactive`	`bool \| None`	`None`	If True, the gallery will be interactive, allowing the user to upload images. If False, the gallery will be static. Default is True.
`type`	`"numpy" \| "pil" \| "filepath"`	`"filepath"`	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. If the image is SVG, the `type` is ignored and the filepath of the SVG is returned.

Events

name	description
`select`	Event listener for when the user selects or deselects the Carousel. Uses event data gradio.SelectData to carry `value` referring to the label of the Carousel, and `selected` to refer to state of the Carousel. See EventData documentation on how to use this event data
`upload`	This listener is triggered when the user uploads a file into the Carousel.
`change`	Triggered when the value of the Carousel 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.

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: Should return, list of images, or list of (image, caption) tuples.

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