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gradio.Audio(ยทยทยท)
Description
Creates an audio component that can be used to upload/record audio (as an input) or display audio (as an output).
Behavior
As input: passes the uploaded audio as a Tuple(int, numpy.array) corresponding to (sample rate in Hz, audio data as a 16-bit int array whose values range from -32768 to 32767), or as a str filepath, depending on `type`.
As output: expects a Tuple(int, numpy.array) corresponding to (sample rate in Hz, audio data as a float or int numpy array) or as a str or pathlib.Path filepath or URL to an audio file, which gets displayed
Initialization
Parameter | Description |
---|---|
value
str | Path | tuple[int, np.ndarray] | Callable | None default: None |
A path, URL, or [sample_rate, numpy array] tuple (sample rate in Hz, audio data as a float or int numpy array) for the default value that Audio component is going to take. If callable, the function will be called whenever the app loads to set the initial value of the component. |
source
Literal['upload', 'microphone'] default: "upload" |
Source of audio. "upload" creates a box where user can drop an audio file, "microphone" creates a microphone input. |
type
Literal['numpy', 'filepath'] default: "numpy" |
The format the audio file is converted to before being passed into the prediction function. "numpy" converts the audio to a tuple consisting of: (int sample rate, numpy.array for the data), "filepath" passes a str path to a temporary file containing the audio. |
label
str | None default: None |
component name in interface. |
every
float | None default: 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 default: True |
if True, will display label. |
container
bool default: True |
If True, will place the component in a container - providing some extra padding around the border. |
scale
int | None default: 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 default: 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 default: None |
if True, will allow users to upload and edit a audio file; if False, can only be used to play audio. If not provided, this is inferred based on whether the component is used as an input or output. |
visible
bool default: True |
If False, component will be hidden. |
streaming
bool default: False |
If set to True when used in a `live` interface, will automatically stream webcam feed. Only valid is source is 'microphone'. |
elem_id
str | None default: 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 default: 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. |
format
Literal['wav', 'mp3'] default: "wav" |
The file format to save audio files. Either 'wav' or 'mp3'. wav files are lossless but will tend to be larger files. mp3 files tend to be smaller. Default is wav. Applies both when this component is used as an input (when `type` is "format") and when this component is used as an output. |
autoplay
bool default: False |
Whether to automatically play the audio when the component is used as an output. Note: browsers will not autoplay audio files if the user has not interacted with the page yet. |
show_share_button
bool | None default: 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. |
Shortcuts
Class | Interface String Shortcut | Initialization |
---|---|---|
|
"audio" |
Uses default values |
|
"microphone" |
Uses source="microphone" |
Demos
from math import log2, pow
import os
import numpy as np
from scipy.fftpack import fft
import gradio as gr
A4 = 440
C0 = A4 * pow(2, -4.75)
name = ["C", "C#", "D", "D#", "E", "F", "F#", "G", "G#", "A", "A#", "B"]
def get_pitch(freq):
h = round(12 * log2(freq / C0))
n = h % 12
return name[n]
def main_note(audio):
rate, y = audio
if len(y.shape) == 2:
y = y.T[0]
N = len(y)
T = 1.0 / rate
yf = fft(y)
yf2 = 2.0 / N * np.abs(yf[0 : N // 2])
xf = np.linspace(0.0, 1.0 / (2.0 * T), N // 2)
volume_per_pitch = {}
total_volume = np.sum(yf2)
for freq, volume in zip(xf, yf2):
if freq == 0:
continue
pitch = get_pitch(freq)
if pitch not in volume_per_pitch:
volume_per_pitch[pitch] = 0
volume_per_pitch[pitch] += 1.0 * volume / total_volume
volume_per_pitch = {k: float(v) for k, v in volume_per_pitch.items()}
return volume_per_pitch
demo = gr.Interface(
main_note,
gr.Audio(source="microphone"),
gr.Label(num_top_classes=4),
examples=[
[os.path.join(os.path.dirname(__file__),"audio/recording1.wav")],
[os.path.join(os.path.dirname(__file__),"audio/cantina.wav")],
],
interpretation="default",
)
if __name__ == "__main__":
demo.launch()
Methods
gradio.Audio.change(fn, ยทยทยท)
Description
This listener is triggered when the component's value 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. This method can be used when this component is in a Gradio Blocks.
Agruments
Parameter | Description |
---|---|
fn
Callable | None required |
the function to wrap an interface around. Often a machine learning model's prediction function. Each parameter of the function corresponds to one input component, and the function should return a single value or a tuple of values, with each element in the tuple corresponding to one output component. |
inputs
Component | list[Component] | set[Component] | None default: None |
List of gradio.components to use as inputs. If the function takes no inputs, this should be an empty list. |
outputs
Component | list[Component] | None default: None |
List of gradio.components to use as outputs. If the function returns no outputs, this should be an empty list. |
api_name
str | None | Literal[False] default: None |
Defines how the endpoint appears in the API docs. Can be a string, None, or False. If False, the endpoint will not be exposed in the api docs. If set to None, the endpoint will be exposed in the api docs as an unnamed endpoint, although this behavior will be changed in Gradio 4.0. If set to a string, the endpoint will be exposed in the api docs with the given name. |
status_tracker
None default: None |
|
scroll_to_output
bool default: False |
If True, will scroll to output component on completion |
show_progress
Literal['full', 'minimal', 'hidden'] default: "full" |
If True, will show progress animation while pending |
queue
bool | None default: None |
If True, will place the request on the queue, if the queue has been enabled. If False, will not put this event on the queue, even if the queue has been enabled. If None, will use the queue setting of the gradio app. |
batch
bool default: False |
If True, then the function should process a batch of inputs, meaning that it should accept a list of input values for each parameter. The lists should be of equal length (and be up to length `max_batch_size`). The function is then *required* to return a tuple of lists (even if there is only 1 output component), with each list in the tuple corresponding to one output component. |
max_batch_size
int default: 4 |
Maximum number of inputs to batch together if this is called from the queue (only relevant if batch=True) |
preprocess
bool default: True |
If False, will not run preprocessing of component data before running 'fn' (e.g. leaving it as a base64 string if this method is called with the `Image` component). |
postprocess
bool default: True |
If False, will not run postprocessing of component data before returning 'fn' output to the browser. |
cancels
dict[str, Any] | list[dict[str, Any]] | None default: None |
A list of other events to cancel when This listener is triggered. For example, setting cancels=[click_event] will cancel the click_event, where click_event is the return value of another components .click method. Functions that have not yet run (or generators that are iterating) will be cancelled, but functions that are currently running will be allowed to finish. |
every
float | None default: None |
Run this event 'every' number of seconds while the client connection is open. Interpreted in seconds. Queue must be enabled. |
gradio.Audio.clear(fn, ยทยทยท)
Description
This listener is triggered when the user clears the component (e.g. image or audio) using the X button for the component. This method can be used when this component is in a Gradio Blocks.
Agruments
Parameter | Description |
---|---|
fn
Callable | None required |
the function to wrap an interface around. Often a machine learning model's prediction function. Each parameter of the function corresponds to one input component, and the function should return a single value or a tuple of values, with each element in the tuple corresponding to one output component. |
inputs
Component | list[Component] | set[Component] | None default: None |
List of gradio.components to use as inputs. If the function takes no inputs, this should be an empty list. |
outputs
Component | list[Component] | None default: None |
List of gradio.components to use as outputs. If the function returns no outputs, this should be an empty list. |
api_name
str | None | Literal[False] default: None |
Defines how the endpoint appears in the API docs. Can be a string, None, or False. If False, the endpoint will not be exposed in the api docs. If set to None, the endpoint will be exposed in the api docs as an unnamed endpoint, although this behavior will be changed in Gradio 4.0. If set to a string, the endpoint will be exposed in the api docs with the given name. |
status_tracker
None default: None |
|
scroll_to_output
bool default: False |
If True, will scroll to output component on completion |
show_progress
Literal['full', 'minimal', 'hidden'] default: "full" |
If True, will show progress animation while pending |
queue
bool | None default: None |
If True, will place the request on the queue, if the queue has been enabled. If False, will not put this event on the queue, even if the queue has been enabled. If None, will use the queue setting of the gradio app. |
batch
bool default: False |
If True, then the function should process a batch of inputs, meaning that it should accept a list of input values for each parameter. The lists should be of equal length (and be up to length `max_batch_size`). The function is then *required* to return a tuple of lists (even if there is only 1 output component), with each list in the tuple corresponding to one output component. |
max_batch_size
int default: 4 |
Maximum number of inputs to batch together if this is called from the queue (only relevant if batch=True) |
preprocess
bool default: True |
If False, will not run preprocessing of component data before running 'fn' (e.g. leaving it as a base64 string if this method is called with the `Image` component). |
postprocess
bool default: True |
If False, will not run postprocessing of component data before returning 'fn' output to the browser. |
cancels
dict[str, Any] | list[dict[str, Any]] | None default: None |
A list of other events to cancel when This listener is triggered. For example, setting cancels=[click_event] will cancel the click_event, where click_event is the return value of another components .click method. Functions that have not yet run (or generators that are iterating) will be cancelled, but functions that are currently running will be allowed to finish. |
every
float | None default: None |
Run this event 'every' number of seconds while the client connection is open. Interpreted in seconds. Queue must be enabled. |
gradio.Audio.play(fn, ยทยทยท)
Description
This listener is triggered when the user plays the component (e.g. audio or video). This method can be used when this component is in a Gradio Blocks.
Agruments
Parameter | Description |
---|---|
fn
Callable | None required |
the function to wrap an interface around. Often a machine learning model's prediction function. Each parameter of the function corresponds to one input component, and the function should return a single value or a tuple of values, with each element in the tuple corresponding to one output component. |
inputs
Component | list[Component] | set[Component] | None default: None |
List of gradio.components to use as inputs. If the function takes no inputs, this should be an empty list. |
outputs
Component | list[Component] | None default: None |
List of gradio.components to use as outputs. If the function returns no outputs, this should be an empty list. |
api_name
str | None | Literal[False] default: None |
Defines how the endpoint appears in the API docs. Can be a string, None, or False. If False, the endpoint will not be exposed in the api docs. If set to None, the endpoint will be exposed in the api docs as an unnamed endpoint, although this behavior will be changed in Gradio 4.0. If set to a string, the endpoint will be exposed in the api docs with the given name. |
status_tracker
None default: None |
|
scroll_to_output
bool default: False |
If True, will scroll to output component on completion |
show_progress
Literal['full', 'minimal', 'hidden'] default: "full" |
If True, will show progress animation while pending |
queue
bool | None default: None |
If True, will place the request on the queue, if the queue has been enabled. If False, will not put this event on the queue, even if the queue has been enabled. If None, will use the queue setting of the gradio app. |
batch
bool default: False |
If True, then the function should process a batch of inputs, meaning that it should accept a list of input values for each parameter. The lists should be of equal length (and be up to length `max_batch_size`). The function is then *required* to return a tuple of lists (even if there is only 1 output component), with each list in the tuple corresponding to one output component. |
max_batch_size
int default: 4 |
Maximum number of inputs to batch together if this is called from the queue (only relevant if batch=True) |
preprocess
bool default: True |
If False, will not run preprocessing of component data before running 'fn' (e.g. leaving it as a base64 string if this method is called with the `Image` component). |
postprocess
bool default: True |
If False, will not run postprocessing of component data before returning 'fn' output to the browser. |
cancels
dict[str, Any] | list[dict[str, Any]] | None default: None |
A list of other events to cancel when This listener is triggered. For example, setting cancels=[click_event] will cancel the click_event, where click_event is the return value of another components .click method. Functions that have not yet run (or generators that are iterating) will be cancelled, but functions that are currently running will be allowed to finish. |
every
float | None default: None |
Run this event 'every' number of seconds while the client connection is open. Interpreted in seconds. Queue must be enabled. |
gradio.Audio.pause(fn, ยทยทยท)
Description
This listener is triggered when the media stops playing for any reason (e.g. audio or video). This method can be used when this component is in a Gradio Blocks.
Agruments
Parameter | Description |
---|---|
fn
Callable | None required |
the function to wrap an interface around. Often a machine learning model's prediction function. Each parameter of the function corresponds to one input component, and the function should return a single value or a tuple of values, with each element in the tuple corresponding to one output component. |
inputs
Component | list[Component] | set[Component] | None default: None |
List of gradio.components to use as inputs. If the function takes no inputs, this should be an empty list. |
outputs
Component | list[Component] | None default: None |
List of gradio.components to use as outputs. If the function returns no outputs, this should be an empty list. |
api_name
str | None | Literal[False] default: None |
Defines how the endpoint appears in the API docs. Can be a string, None, or False. If False, the endpoint will not be exposed in the api docs. If set to None, the endpoint will be exposed in the api docs as an unnamed endpoint, although this behavior will be changed in Gradio 4.0. If set to a string, the endpoint will be exposed in the api docs with the given name. |
status_tracker
None default: None |
|
scroll_to_output
bool default: False |
If True, will scroll to output component on completion |
show_progress
Literal['full', 'minimal', 'hidden'] default: "full" |
If True, will show progress animation while pending |
queue
bool | None default: None |
If True, will place the request on the queue, if the queue has been enabled. If False, will not put this event on the queue, even if the queue has been enabled. If None, will use the queue setting of the gradio app. |
batch
bool default: False |
If True, then the function should process a batch of inputs, meaning that it should accept a list of input values for each parameter. The lists should be of equal length (and be up to length `max_batch_size`). The function is then *required* to return a tuple of lists (even if there is only 1 output component), with each list in the tuple corresponding to one output component. |
max_batch_size
int default: 4 |
Maximum number of inputs to batch together if this is called from the queue (only relevant if batch=True) |
preprocess
bool default: True |
If False, will not run preprocessing of component data before running 'fn' (e.g. leaving it as a base64 string if this method is called with the `Image` component). |
postprocess
bool default: True |
If False, will not run postprocessing of component data before returning 'fn' output to the browser. |
cancels
dict[str, Any] | list[dict[str, Any]] | None default: None |
A list of other events to cancel when This listener is triggered. For example, setting cancels=[click_event] will cancel the click_event, where click_event is the return value of another components .click method. Functions that have not yet run (or generators that are iterating) will be cancelled, but functions that are currently running will be allowed to finish. |
every
float | None default: None |
Run this event 'every' number of seconds while the client connection is open. Interpreted in seconds. Queue must be enabled. |
gradio.Audio.stop(fn, ยทยทยท)
Description
This listener is triggered when the user reaches the end of the media track (e.g. audio or video). This method can be used when this component is in a Gradio Blocks.
Agruments
Parameter | Description |
---|---|
fn
Callable | None required |
the function to wrap an interface around. Often a machine learning model's prediction function. Each parameter of the function corresponds to one input component, and the function should return a single value or a tuple of values, with each element in the tuple corresponding to one output component. |
inputs
Component | list[Component] | set[Component] | None default: None |
List of gradio.components to use as inputs. If the function takes no inputs, this should be an empty list. |
outputs
Component | list[Component] | None default: None |
List of gradio.components to use as outputs. If the function returns no outputs, this should be an empty list. |
api_name
str | None | Literal[False] default: None |
Defines how the endpoint appears in the API docs. Can be a string, None, or False. If False, the endpoint will not be exposed in the api docs. If set to None, the endpoint will be exposed in the api docs as an unnamed endpoint, although this behavior will be changed in Gradio 4.0. If set to a string, the endpoint will be exposed in the api docs with the given name. |
status_tracker
None default: None |
|
scroll_to_output
bool default: False |
If True, will scroll to output component on completion |
show_progress
Literal['full', 'minimal', 'hidden'] default: "full" |
If True, will show progress animation while pending |
queue
bool | None default: None |
If True, will place the request on the queue, if the queue has been enabled. If False, will not put this event on the queue, even if the queue has been enabled. If None, will use the queue setting of the gradio app. |
batch
bool default: False |
If True, then the function should process a batch of inputs, meaning that it should accept a list of input values for each parameter. The lists should be of equal length (and be up to length `max_batch_size`). The function is then *required* to return a tuple of lists (even if there is only 1 output component), with each list in the tuple corresponding to one output component. |
max_batch_size
int default: 4 |
Maximum number of inputs to batch together if this is called from the queue (only relevant if batch=True) |
preprocess
bool default: True |
If False, will not run preprocessing of component data before running 'fn' (e.g. leaving it as a base64 string if this method is called with the `Image` component). |
postprocess
bool default: True |
If False, will not run postprocessing of component data before returning 'fn' output to the browser. |
cancels
dict[str, Any] | list[dict[str, Any]] | None default: None |
A list of other events to cancel when This listener is triggered. For example, setting cancels=[click_event] will cancel the click_event, where click_event is the return value of another components .click method. Functions that have not yet run (or generators that are iterating) will be cancelled, but functions that are currently running will be allowed to finish. |
every
float | None default: None |
Run this event 'every' number of seconds while the client connection is open. Interpreted in seconds. Queue must be enabled. |
gradio.Audio.end(fn, ยทยทยท)
Description
This listener is triggered when the user reaches the end of the media track (e.g. audio or video). This method can be used when this component is in a Gradio Blocks.
Agruments
Parameter | Description |
---|---|
fn
Callable | None required |
the function to wrap an interface around. Often a machine learning model's prediction function. Each parameter of the function corresponds to one input component, and the function should return a single value or a tuple of values, with each element in the tuple corresponding to one output component. |
inputs
Component | list[Component] | set[Component] | None default: None |
List of gradio.components to use as inputs. If the function takes no inputs, this should be an empty list. |
outputs
Component | list[Component] | None default: None |
List of gradio.components to use as outputs. If the function returns no outputs, this should be an empty list. |
api_name
str | None | Literal[False] default: None |
Defines how the endpoint appears in the API docs. Can be a string, None, or False. If False, the endpoint will not be exposed in the api docs. If set to None, the endpoint will be exposed in the api docs as an unnamed endpoint, although this behavior will be changed in Gradio 4.0. If set to a string, the endpoint will be exposed in the api docs with the given name. |
status_tracker
None default: None |
|
scroll_to_output
bool default: False |
If True, will scroll to output component on completion |
show_progress
Literal['full', 'minimal', 'hidden'] default: "full" |
If True, will show progress animation while pending |
queue
bool | None default: None |
If True, will place the request on the queue, if the queue has been enabled. If False, will not put this event on the queue, even if the queue has been enabled. If None, will use the queue setting of the gradio app. |
batch
bool default: False |
If True, then the function should process a batch of inputs, meaning that it should accept a list of input values for each parameter. The lists should be of equal length (and be up to length `max_batch_size`). The function is then *required* to return a tuple of lists (even if there is only 1 output component), with each list in the tuple corresponding to one output component. |
max_batch_size
int default: 4 |
Maximum number of inputs to batch together if this is called from the queue (only relevant if batch=True) |
preprocess
bool default: True |
If False, will not run preprocessing of component data before running 'fn' (e.g. leaving it as a base64 string if this method is called with the `Image` component). |
postprocess
bool default: True |
If False, will not run postprocessing of component data before returning 'fn' output to the browser. |
cancels
dict[str, Any] | list[dict[str, Any]] | None default: None |
A list of other events to cancel when This listener is triggered. For example, setting cancels=[click_event] will cancel the click_event, where click_event is the return value of another components .click method. Functions that have not yet run (or generators that are iterating) will be cancelled, but functions that are currently running will be allowed to finish. |
every
float | None default: None |
Run this event 'every' number of seconds while the client connection is open. Interpreted in seconds. Queue must be enabled. |
gradio.Audio.stream(fn, ยทยทยท)
Description
This listener is triggered when the user streams the component (e.g. a live webcam component). This method can be used when this component is in a Gradio Blocks.
Agruments
Parameter | Description |
---|---|
fn
Callable | None required |
the function to wrap an interface around. Often a machine learning model's prediction function. Each parameter of the function corresponds to one input component, and the function should return a single value or a tuple of values, with each element in the tuple corresponding to one output component. |
inputs
Component | list[Component] | set[Component] | None default: None |
List of gradio.components to use as inputs. If the function takes no inputs, this should be an empty list. |
outputs
Component | list[Component] | None default: None |
List of gradio.components to use as outputs. If the function returns no outputs, this should be an empty list. |
api_name
str | None | Literal[False] default: None |
Defines how the endpoint appears in the API docs. Can be a string, None, or False. If False, the endpoint will not be exposed in the api docs. If set to None, the endpoint will be exposed in the api docs as an unnamed endpoint, although this behavior will be changed in Gradio 4.0. If set to a string, the endpoint will be exposed in the api docs with the given name. |
status_tracker
None default: None |
|
scroll_to_output
bool default: False |
If True, will scroll to output component on completion |
show_progress
Literal['full', 'minimal', 'hidden'] default: "full" |
If True, will show progress animation while pending |
queue
bool | None default: None |
If True, will place the request on the queue, if the queue has been enabled. If False, will not put this event on the queue, even if the queue has been enabled. If None, will use the queue setting of the gradio app. |
batch
bool default: False |
If True, then the function should process a batch of inputs, meaning that it should accept a list of input values for each parameter. The lists should be of equal length (and be up to length `max_batch_size`). The function is then *required* to return a tuple of lists (even if there is only 1 output component), with each list in the tuple corresponding to one output component. |
max_batch_size
int default: 4 |
Maximum number of inputs to batch together if this is called from the queue (only relevant if batch=True) |
preprocess
bool default: True |
If False, will not run preprocessing of component data before running 'fn' (e.g. leaving it as a base64 string if this method is called with the `Image` component). |
postprocess
bool default: True |
If False, will not run postprocessing of component data before returning 'fn' output to the browser. |
cancels
dict[str, Any] | list[dict[str, Any]] | None default: None |
A list of other events to cancel when This listener is triggered. For example, setting cancels=[click_event] will cancel the click_event, where click_event is the return value of another components .click method. Functions that have not yet run (or generators that are iterating) will be cancelled, but functions that are currently running will be allowed to finish. |
every
float | None default: None |
Run this event 'every' number of seconds while the client connection is open. Interpreted in seconds. Queue must be enabled. |
gradio.Audio.start_recording(fn, ยทยทยท)
Description
This listener is triggered when the user starts recording with the component (e.g. audio or video). This method can be used when this component is in a Gradio Blocks.
Agruments
Parameter | Description |
---|---|
fn
Callable | None required |
the function to wrap an interface around. Often a machine learning model's prediction function. Each parameter of the function corresponds to one input component, and the function should return a single value or a tuple of values, with each element in the tuple corresponding to one output component. |
inputs
Component | list[Component] | set[Component] | None default: None |
List of gradio.components to use as inputs. If the function takes no inputs, this should be an empty list. |
outputs
Component | list[Component] | None default: None |
List of gradio.components to use as outputs. If the function returns no outputs, this should be an empty list. |
api_name
str | None | Literal[False] default: None |
Defines how the endpoint appears in the API docs. Can be a string, None, or False. If False, the endpoint will not be exposed in the api docs. If set to None, the endpoint will be exposed in the api docs as an unnamed endpoint, although this behavior will be changed in Gradio 4.0. If set to a string, the endpoint will be exposed in the api docs with the given name. |
status_tracker
None default: None |
|
scroll_to_output
bool default: False |
If True, will scroll to output component on completion |
show_progress
Literal['full', 'minimal', 'hidden'] default: "full" |
If True, will show progress animation while pending |
queue
bool | None default: None |
If True, will place the request on the queue, if the queue has been enabled. If False, will not put this event on the queue, even if the queue has been enabled. If None, will use the queue setting of the gradio app. |
batch
bool default: False |
If True, then the function should process a batch of inputs, meaning that it should accept a list of input values for each parameter. The lists should be of equal length (and be up to length `max_batch_size`). The function is then *required* to return a tuple of lists (even if there is only 1 output component), with each list in the tuple corresponding to one output component. |
max_batch_size
int default: 4 |
Maximum number of inputs to batch together if this is called from the queue (only relevant if batch=True) |
preprocess
bool default: True |
If False, will not run preprocessing of component data before running 'fn' (e.g. leaving it as a base64 string if this method is called with the `Image` component). |
postprocess
bool default: True |
If False, will not run postprocessing of component data before returning 'fn' output to the browser. |
cancels
dict[str, Any] | list[dict[str, Any]] | None default: None |
A list of other events to cancel when This listener is triggered. For example, setting cancels=[click_event] will cancel the click_event, where click_event is the return value of another components .click method. Functions that have not yet run (or generators that are iterating) will be cancelled, but functions that are currently running will be allowed to finish. |
every
float | None default: None |
Run this event 'every' number of seconds while the client connection is open. Interpreted in seconds. Queue must be enabled. |
gradio.Audio.stop_recording(fn, ยทยทยท)
Description
This listener is triggered when the user stops recording with the component (e.g. audio or video). This method can be used when this component is in a Gradio Blocks.
Agruments
Parameter | Description |
---|---|
fn
Callable | None required |
the function to wrap an interface around. Often a machine learning model's prediction function. Each parameter of the function corresponds to one input component, and the function should return a single value or a tuple of values, with each element in the tuple corresponding to one output component. |
inputs
Component | list[Component] | set[Component] | None default: None |
List of gradio.components to use as inputs. If the function takes no inputs, this should be an empty list. |
outputs
Component | list[Component] | None default: None |
List of gradio.components to use as outputs. If the function returns no outputs, this should be an empty list. |
api_name
str | None | Literal[False] default: None |
Defines how the endpoint appears in the API docs. Can be a string, None, or False. If False, the endpoint will not be exposed in the api docs. If set to None, the endpoint will be exposed in the api docs as an unnamed endpoint, although this behavior will be changed in Gradio 4.0. If set to a string, the endpoint will be exposed in the api docs with the given name. |
status_tracker
None default: None |
|
scroll_to_output
bool default: False |
If True, will scroll to output component on completion |
show_progress
Literal['full', 'minimal', 'hidden'] default: "full" |
If True, will show progress animation while pending |
queue
bool | None default: None |
If True, will place the request on the queue, if the queue has been enabled. If False, will not put this event on the queue, even if the queue has been enabled. If None, will use the queue setting of the gradio app. |
batch
bool default: False |
If True, then the function should process a batch of inputs, meaning that it should accept a list of input values for each parameter. The lists should be of equal length (and be up to length `max_batch_size`). The function is then *required* to return a tuple of lists (even if there is only 1 output component), with each list in the tuple corresponding to one output component. |
max_batch_size
int default: 4 |
Maximum number of inputs to batch together if this is called from the queue (only relevant if batch=True) |
preprocess
bool default: True |
If False, will not run preprocessing of component data before running 'fn' (e.g. leaving it as a base64 string if this method is called with the `Image` component). |
postprocess
bool default: True |
If False, will not run postprocessing of component data before returning 'fn' output to the browser. |
cancels
dict[str, Any] | list[dict[str, Any]] | None default: None |
A list of other events to cancel when This listener is triggered. For example, setting cancels=[click_event] will cancel the click_event, where click_event is the return value of another components .click method. Functions that have not yet run (or generators that are iterating) will be cancelled, but functions that are currently running will be allowed to finish. |
every
float | None default: None |
Run this event 'every' number of seconds while the client connection is open. Interpreted in seconds. Queue must be enabled. |
gradio.Audio.upload(fn, ยทยทยท)
Description
This listener is triggered when the user uploads a file into the component (e.g. when the user uploads a video into a video component). This method can be used when this component is in a Gradio Blocks.
Agruments
Parameter | Description |
---|---|
fn
Callable | None required |
the function to wrap an interface around. Often a machine learning model's prediction function. Each parameter of the function corresponds to one input component, and the function should return a single value or a tuple of values, with each element in the tuple corresponding to one output component. |
inputs
Component | list[Component] | set[Component] | None default: None |
List of gradio.components to use as inputs. If the function takes no inputs, this should be an empty list. |
outputs
Component | list[Component] | None default: None |
List of gradio.components to use as outputs. If the function returns no outputs, this should be an empty list. |
api_name
str | None | Literal[False] default: None |
Defines how the endpoint appears in the API docs. Can be a string, None, or False. If False, the endpoint will not be exposed in the api docs. If set to None, the endpoint will be exposed in the api docs as an unnamed endpoint, although this behavior will be changed in Gradio 4.0. If set to a string, the endpoint will be exposed in the api docs with the given name. |
status_tracker
None default: None |
|
scroll_to_output
bool default: False |
If True, will scroll to output component on completion |
show_progress
Literal['full', 'minimal', 'hidden'] default: "full" |
If True, will show progress animation while pending |
queue
bool | None default: None |
If True, will place the request on the queue, if the queue has been enabled. If False, will not put this event on the queue, even if the queue has been enabled. If None, will use the queue setting of the gradio app. |
batch
bool default: False |
If True, then the function should process a batch of inputs, meaning that it should accept a list of input values for each parameter. The lists should be of equal length (and be up to length `max_batch_size`). The function is then *required* to return a tuple of lists (even if there is only 1 output component), with each list in the tuple corresponding to one output component. |
max_batch_size
int default: 4 |
Maximum number of inputs to batch together if this is called from the queue (only relevant if batch=True) |
preprocess
bool default: True |
If False, will not run preprocessing of component data before running 'fn' (e.g. leaving it as a base64 string if this method is called with the `Image` component). |
postprocess
bool default: True |
If False, will not run postprocessing of component data before returning 'fn' output to the browser. |
cancels
dict[str, Any] | list[dict[str, Any]] | None default: None |
A list of other events to cancel when This listener is triggered. For example, setting cancels=[click_event] will cancel the click_event, where click_event is the return value of another components .click method. Functions that have not yet run (or generators that are iterating) will be cancelled, but functions that are currently running will be allowed to finish. |
every
float | None default: None |
Run this event 'every' number of seconds while the client connection is open. Interpreted in seconds. Queue must be enabled. |