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tags title short_description colorFrom colorTo sdk pinned app_file
gradio-custom-component
SimpleImage
multimodal data
visualization
machine learning
robotics
gradio_rerun
Rerun viewer with Gradio
blue
yellow
gradio
false
space.py

gradio_rerun

Static Badge Static Badge

Rerun viewer with Gradio

Installation

pip install gradio_rerun

Usage

import gradio as gr
from gradio_rerun import Rerun


example = Rerun().example_value()


def predict(url: str, file_path: str | list[str] | None):
    if url:
        return url
    return file_path


with gr.Blocks(css=".gradio-container { max-width: unset!important; }") as demo:
    with gr.Row():
        with gr.Column():
            with gr.Group():
                file_path = gr.File(file_count="multiple", type="filepath")
                url = gr.Text(
                    info="Or use a URL",
                    label="URL",
                )
        with gr.Column():
            pass
    btn = gr.Button("Run", scale=0)
    with gr.Row():
        rerun_viewer = Rerun(height=900)

    inputs = [file_path, url]
    outputs = [rerun_viewer]

    gr.on([btn.click, file_path.upload], fn=predict, inputs=inputs, outputs=outputs)

    gr.Examples(
        examples=[
            [
                None,
                "https://app.rerun.io/version/0.15.1/examples/detect_and_track_objects.rrd",
            ],
            [
                ["./examples/rgbd.rrd"],
                None,
            ],
            [
                ["./examples/rrt-star.rrd"],
                None,
            ],
            [
                ["./examples/structure_from_motion.rrd"],
                None,
            ],
            [
                ["./examples/structure_from_motion.rrd", "./examples/rrt-star.rrd"],
                None,
            ],
        ],
        fn=predict,
        inputs=inputs,
        outputs=outputs,
        run_on_click=True,
    )

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

Rerun

Initialization

name type default description
value
list[str] | None
None A path or URL for the default value that Rerun component is going to take. 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.
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 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.
height
int | str
640 height of component in pixels. If a string is provided, will be interpreted as a CSS value. If None, will be set to 640px.
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.
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.

Events

name description
clear This listener is triggered when the user clears the Rerun using the X button for the component.
change Triggered when the value of the Rerun 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 Rerun.

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, a str containing the path to the image.
  • As input: Should return, expects a str or pathlib.Path object containing the path to the image.
def predict(
    value: str | None
) -> list[gradio.data_classes.FileData]
   | gradio.data_classes.FileData
   | str
   | list[str]:
    return value