gradio-likeablegallery 0.0.1

Python library for easily interacting with trained machine learning models

---

tags: [gradio-custom-component, Gallery] title: gradio_likeablegallery short_description: colorFrom: blue colorTo: yellow sdk: gradio pinned: false app_file: space.py

gradio_likeablegallery

Python library for easily interacting with trained machine learning models

Installation

pip install gradio_likeablegallery

Usage

import gradio as gr
from gradio_likeablegallery import LikeableGallery
from PIL import Image

all_images = [Image.new("RGB", (200, 200)) for _ in range(10)]


with gr.Blocks() as demo:
    with gr.Row():
        LikeableGallery(value=all_images, label="Blank", likeable=True,
                        allow_preview=True, preview=True),  # blank component
        LikeableGallery(label="Populated"),  # populated component


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

LikeableGallery

Initialization

name	type	default	description
value	list[ numpy.ndarray | PIL.Image.Image | gradio.data_classes.FileData | pathlib.Path | str | tuple[ numpy.ndarray | PIL.Image.Image | gradio.data_classes.FileData | pathlib.Path | str, str, ] | GalleryImage ] | 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. 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 size compared to adjacent Components. For example if Components A and B are in a Row, and A has scale=2, and B has scale=1, A will be twice as wide as B. Should be an integer. scale applies in Rows, and to top-level Components in Blocks where fill_height=True.
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 | dict | None	2	Represents the number of images that should be shown in one row, for each of the six standard screen sizes (<576px(xs), <768px(sm), <992px(md), <1200px(lg), <1600px(xl), >1600px(xll)). If fewer than 6 are given then the last will be used for all subsequent breakpoints. If a dict is passed in, you can represents the number of images for each size screen with [xs,sm,md,lg,xl,xll] as the key.
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, Gallery 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.
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".
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 Gallery to preview mode unless allow_preview is set to False.
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. If False, icon does not appear.
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.
action_label	str | None	"Click"	The label for the action button. Only displayed if `clickable` is set to True.
has_more	bool	False	If True, will show the "Load More" button.
load_more_button_props	dict | None	None	gradio Button props.
gap	int | tuple[int, int] | None	8	The gap (px) between images. If a tuple is passed, the first value is the gap for width and the second value is the gap for height.If a number is passed, the gap will be the same for width and height.
clickable	bool | None	None	Whether the gallery image display an action button. Set automatically by the .click method but has to be present in the signature for it to show up in the config.
likeable	bool | None	None	Whether the gallery image display a like or dislike button. Set automatically by the .like method but has to be present in the signature for it to show up in the config.

Events

name	description
select	Event listener for when the user selects or deselects the LikeableGallery. Uses event data gradio.SelectData to carry value referring to the label of the LikeableGallery, and selected to refer to state of the LikeableGallery. See EventData documentation on how to use this event data
change	Triggered when the value of the LikeableGallery 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.
like	This listener is triggered when the user likes/dislikes from within the LikeableGallery. This event has EventData of type gradio.LikeData that carries information, accessible through LikeData.index and LikeData.value. See EventData documentation on how to use this event data.
click	Triggered when the image action button is clicked.
load_more

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, list of images, or list of (image, caption) tuples.

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

GalleryImage

class GalleryImage(GradioModel):
    image: Union[FileData, Path, str]
    caption: Optional[str] = None
    liked: Optional[bool] = None
    # custom meta data
    meta: Optional[Any] = None