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gallery with download button

Project description


tags: [gradio-custom-component, Gallery] title: gradio_downloadgallery short_description: gallery with download button colorFrom: blue colorTo: yellow sdk: gradio pinned: false app_file: space.py

gradio_downloadgallery

PyPI - Version

gallery with download button

Installation

pip install gradio_downloadgallery

Usage

import gradio as gr
from gradio_downloadgallery import DownloadGallery

example = DownloadGallery().example_value()
payload = DownloadGallery().example_payload()

with gr.Blocks() as demo:
    with gr.Row():
        # DownloadGallery(label="Blank"),  # blank component
        gallery = DownloadGallery(value=example, interactive=False)  #

    def on_toggle_favorite(value, evt: gr.EventData):
        favorite = evt._data["favorite"]
        if favorite:
            # add here logic to save the image to favorites
            print(f"Add {evt._data['image']['orig_name']} to favorites")
        else:
            # add here logic to remove the image from favorites
            print(f"Remove {evt._data['image']['orig_name']} from favorites")

    gallery.toggle_favorite(on_toggle_favorite, gallery, None)


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

DownloadGallery

Initialization

name type default description
value
Sequence[
        np.ndarray | PIL.Image.Image | str | 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.
format
str
"webp" Format to save images before they are returned to the frontend, such as 'jpeg' or 'png'. This parameter only applies to images that are returned from the prediction function as numpy arrays or PIL Images. The format should be supported by the PIL library.
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
Timer | float | None
None Continously calls `value` to recalculate it if `value` is a function (has no effect otherwise). Can provide a Timer whose tick resets `value`, or a float that provides the regular interval for the reset Timer.
inputs
Component | Sequence[Component] | set[Component] | None
None Components that are used as inputs to calculate `value` if `value` is a function (has no effect otherwise). `value` is recalculated any time the inputs change.
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.
key
int | str | None
None if assigned, will be used to assume identity across a re-render. Components that have the same key across a re-render will have their value preserved.
columns
int | list[int] | Tuple[int, ...] | 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 | list[int] | 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 | str | 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, downloadGallery 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 downloadGallery to preview mode unless allow_preview is set to False.
object_fit
Literal[
        "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
Literal["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.
show_fullscreen_button
bool
True If True, will show a fullscreen icon in the corner of the component that allows user to view the gallery in fullscreen mode. 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.

Events

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

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, passes the list of images as a list of (image, caption) tuples, or a list of (image, None) tuples if no captions are provided (which is usually the case). The image can be a str file path, a numpy array, or a PIL.Image object depending on type.
  • As input: Should return, expects the function to return a list of images, or list of (image, str caption) tuples. Each image can be a str file path, a numpy array, or a PIL.Image object.
def predict(
    value: list[tuple[str, str | None, bool | None]]
   | list[tuple[PIL.Image.Image, str | None, bool | None]]
   | list[tuple[numpy.ndarray, str | None, bool | None]]
   | None
) -> list[
       numpy.ndarray
       | PIL.Image.Image
       | pathlib.Path
       | str
       | tuple[
           numpy.ndarray
           | PIL.Image.Image
           | pathlib.Path
           | str,
           str,
       ]
       | tuple[
           numpy.ndarray
           | PIL.Image.Image
           | pathlib.Path
           | str,
           str,
           bool,
       ]
   ]
   | None:
    return value

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