Spaces:
Runtime error
Runtime error
| """gr.Model4DGS() component.""" | |
| from __future__ import annotations | |
| from pathlib import Path | |
| from typing import Callable, List | |
| from gradio_client.documentation import document, set_documentation_group | |
| from gradio.components.base import Component | |
| from gradio.data_classes import FileData, GradioModel | |
| from gradio.events import Events | |
| set_documentation_group("component") | |
| class Model4DGSData(GradioModel): | |
| files: List[FileData] | |
| from gradio.events import Dependency | |
| class Model4DGS(Component): | |
| """ | |
| Component allows users to upload or view 4D Gaussian Splatting files (.splat). | |
| Preprocessing: This component passes the uploaded file as a {str}filepath. | |
| Postprocessing: expects function to return a {str} or {pathlib.Path} filepath of type (.splat) | |
| """ | |
| EVENTS = [Events.change, Events.upload, Events.edit, Events.clear] | |
| data_model = Model4DGSData | |
| def __init__( | |
| self, | |
| value: str | Callable | None = None, | |
| *, | |
| height: int | None = None, | |
| label: str | None = None, | |
| show_label: bool | None = None, | |
| every: float | None = None, | |
| container: bool = True, | |
| scale: int | None = None, | |
| min_width: int = 160, | |
| interactive: bool | None = None, | |
| visible: bool = True, | |
| elem_id: str | None = None, | |
| elem_classes: list[str] | str | None = None, | |
| render: bool = True, | |
| ): | |
| """ | |
| Parameters: | |
| value: path to (.splat) file to show in model4DGS viewer. If callable, the function will be called whenever the app loads to set the initial value of the component. | |
| height: height of the model4DGS component, in pixels. | |
| """ | |
| self.height = height | |
| super().__init__( | |
| label=label, | |
| every=every, | |
| show_label=show_label, | |
| container=container, | |
| scale=scale, | |
| min_width=min_width, | |
| interactive=interactive, | |
| visible=visible, | |
| elem_id=elem_id, | |
| elem_classes=elem_classes, | |
| render=render, | |
| value=value, | |
| ) | |
| def preprocess(self, payload: Model4DGSData | None) -> List[str] | None: | |
| return [file.path for file in payload.files] | |
| def postprocess(self, value: List[str] | str | None) -> Model4DGSData | None: | |
| if value is None: | |
| return value | |
| if isinstance(value, list): | |
| return Model4DGSData(files=[FileData(path=file) for file in value]) | |
| return Model4DGSData(files=[]) | |
| #example display name | |
| def as_example(self, input_data: List[str] | str | None) -> str: | |
| return Path(input_data).name if input_data else "" | |
| def example_inputs(self): | |
| return [ | |
| "assets/tiger_4d_model_0.ply", | |
| "assets/tiger_4d_model_1.ply", | |
| "assets/tiger_4d_model_2.ply", | |
| "assets/tiger_4d_model_3.ply", | |
| "assets/tiger_4d_model_4.ply", | |
| "assets/tiger_4d_model_5.ply", | |
| "assets/tiger_4d_model_6.ply", | |
| "assets/tiger_4d_model_7.ply", | |
| "assets/tiger_4d_model_8.ply", | |
| "assets/tiger_4d_model_9.ply", | |
| "assets/tiger_4d_model_10.ply", | |
| "assets/tiger_4d_model_11.ply", | |
| "assets/tiger_4d_model_12.ply", | |
| "assets/tiger_4d_model_13.ply" | |
| ]; | |
| def change(self, | |
| fn: Callable | None, | |
| inputs: Component | Sequence[Component] | set[Component] | None = None, | |
| outputs: Component | Sequence[Component] | None = None, | |
| api_name: str | None | Literal[False] = None, | |
| scroll_to_output: bool = False, | |
| show_progress: Literal["full", "minimal", "hidden"] = "full", | |
| queue: bool | None = None, | |
| batch: bool = False, | |
| max_batch_size: int = 4, | |
| preprocess: bool = True, | |
| postprocess: bool = True, | |
| cancels: dict[str, Any] | list[dict[str, Any]] | None = None, | |
| every: float | None = None, | |
| trigger_mode: Literal["once", "multiple", "always_last"] | None = None, | |
| js: str | None = None, | |
| concurrency_limit: int | None | Literal["default"] = "default", | |
| concurrency_id: str | None = None, | |
| show_api: bool = True) -> Dependency: | |
| """ | |
| Parameters: | |
| fn: the function to call when this event is triggered. 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: List of gradio.components to use as inputs. If the function takes no inputs, this should be an empty list. | |
| outputs: List of gradio.components to use as outputs. If the function returns no outputs, this should be an empty list. | |
| api_name: 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. | |
| scroll_to_output: If True, will scroll to output component on completion | |
| show_progress: If True, will show progress animation while pending | |
| queue: 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: 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: Maximum number of inputs to batch together if this is called from the queue (only relevant if batch=True) | |
| preprocess: 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: If False, will not run postprocessing of component data before returning 'fn' output to the browser. | |
| cancels: 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: Run this event 'every' number of seconds while the client connection is open. Interpreted in seconds. | |
| trigger_mode: If "once" (default for all events except `.change()`) would not allow any submissions while an event is pending. If set to "multiple", unlimited submissions are allowed while pending, and "always_last" (default for `.change()` and `.key_up()` events) would allow a second submission after the pending event is complete. | |
| js: Optional frontend js method to run before running 'fn'. Input arguments for js method are values of 'inputs' and 'outputs', return should be a list of values for output components. | |
| concurrency_limit: If set, this is the maximum number of this event that can be running simultaneously. Can be set to None to mean no concurrency_limit (any number of this event can be running simultaneously). Set to "default" to use the default concurrency limit (defined by the `default_concurrency_limit` parameter in `Blocks.queue()`, which itself is 1 by default). | |
| concurrency_id: If set, this is the id of the concurrency group. Events with the same concurrency_id will be limited by the lowest set concurrency_limit. | |
| show_api: whether to show this event in the "view API" page of the Gradio app, or in the ".view_api()" method of the Gradio clients. Unlike setting api_name to False, setting show_api to False will still allow downstream apps to use this event. If fn is None, show_api will automatically be set to False. | |
| """ | |
| ... | |
| def upload(self, | |
| fn: Callable | None, | |
| inputs: Component | Sequence[Component] | set[Component] | None = None, | |
| outputs: Component | Sequence[Component] | None = None, | |
| api_name: str | None | Literal[False] = None, | |
| scroll_to_output: bool = False, | |
| show_progress: Literal["full", "minimal", "hidden"] = "full", | |
| queue: bool | None = None, | |
| batch: bool = False, | |
| max_batch_size: int = 4, | |
| preprocess: bool = True, | |
| postprocess: bool = True, | |
| cancels: dict[str, Any] | list[dict[str, Any]] | None = None, | |
| every: float | None = None, | |
| trigger_mode: Literal["once", "multiple", "always_last"] | None = None, | |
| js: str | None = None, | |
| concurrency_limit: int | None | Literal["default"] = "default", | |
| concurrency_id: str | None = None, | |
| show_api: bool = True) -> Dependency: | |
| """ | |
| Parameters: | |
| fn: the function to call when this event is triggered. 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: List of gradio.components to use as inputs. If the function takes no inputs, this should be an empty list. | |
| outputs: List of gradio.components to use as outputs. If the function returns no outputs, this should be an empty list. | |
| api_name: 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. | |
| scroll_to_output: If True, will scroll to output component on completion | |
| show_progress: If True, will show progress animation while pending | |
| queue: 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: 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: Maximum number of inputs to batch together if this is called from the queue (only relevant if batch=True) | |
| preprocess: 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: If False, will not run postprocessing of component data before returning 'fn' output to the browser. | |
| cancels: 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: Run this event 'every' number of seconds while the client connection is open. Interpreted in seconds. | |
| trigger_mode: If "once" (default for all events except `.change()`) would not allow any submissions while an event is pending. If set to "multiple", unlimited submissions are allowed while pending, and "always_last" (default for `.change()` and `.key_up()` events) would allow a second submission after the pending event is complete. | |
| js: Optional frontend js method to run before running 'fn'. Input arguments for js method are values of 'inputs' and 'outputs', return should be a list of values for output components. | |
| concurrency_limit: If set, this is the maximum number of this event that can be running simultaneously. Can be set to None to mean no concurrency_limit (any number of this event can be running simultaneously). Set to "default" to use the default concurrency limit (defined by the `default_concurrency_limit` parameter in `Blocks.queue()`, which itself is 1 by default). | |
| concurrency_id: If set, this is the id of the concurrency group. Events with the same concurrency_id will be limited by the lowest set concurrency_limit. | |
| show_api: whether to show this event in the "view API" page of the Gradio app, or in the ".view_api()" method of the Gradio clients. Unlike setting api_name to False, setting show_api to False will still allow downstream apps to use this event. If fn is None, show_api will automatically be set to False. | |
| """ | |
| ... | |
| def edit(self, | |
| fn: Callable | None, | |
| inputs: Component | Sequence[Component] | set[Component] | None = None, | |
| outputs: Component | Sequence[Component] | None = None, | |
| api_name: str | None | Literal[False] = None, | |
| scroll_to_output: bool = False, | |
| show_progress: Literal["full", "minimal", "hidden"] = "full", | |
| queue: bool | None = None, | |
| batch: bool = False, | |
| max_batch_size: int = 4, | |
| preprocess: bool = True, | |
| postprocess: bool = True, | |
| cancels: dict[str, Any] | list[dict[str, Any]] | None = None, | |
| every: float | None = None, | |
| trigger_mode: Literal["once", "multiple", "always_last"] | None = None, | |
| js: str | None = None, | |
| concurrency_limit: int | None | Literal["default"] = "default", | |
| concurrency_id: str | None = None, | |
| show_api: bool = True) -> Dependency: | |
| """ | |
| Parameters: | |
| fn: the function to call when this event is triggered. 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: List of gradio.components to use as inputs. If the function takes no inputs, this should be an empty list. | |
| outputs: List of gradio.components to use as outputs. If the function returns no outputs, this should be an empty list. | |
| api_name: 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. | |
| scroll_to_output: If True, will scroll to output component on completion | |
| show_progress: If True, will show progress animation while pending | |
| queue: 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: 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: Maximum number of inputs to batch together if this is called from the queue (only relevant if batch=True) | |
| preprocess: 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: If False, will not run postprocessing of component data before returning 'fn' output to the browser. | |
| cancels: 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: Run this event 'every' number of seconds while the client connection is open. Interpreted in seconds. | |
| trigger_mode: If "once" (default for all events except `.change()`) would not allow any submissions while an event is pending. If set to "multiple", unlimited submissions are allowed while pending, and "always_last" (default for `.change()` and `.key_up()` events) would allow a second submission after the pending event is complete. | |
| js: Optional frontend js method to run before running 'fn'. Input arguments for js method are values of 'inputs' and 'outputs', return should be a list of values for output components. | |
| concurrency_limit: If set, this is the maximum number of this event that can be running simultaneously. Can be set to None to mean no concurrency_limit (any number of this event can be running simultaneously). Set to "default" to use the default concurrency limit (defined by the `default_concurrency_limit` parameter in `Blocks.queue()`, which itself is 1 by default). | |
| concurrency_id: If set, this is the id of the concurrency group. Events with the same concurrency_id will be limited by the lowest set concurrency_limit. | |
| show_api: whether to show this event in the "view API" page of the Gradio app, or in the ".view_api()" method of the Gradio clients. Unlike setting api_name to False, setting show_api to False will still allow downstream apps to use this event. If fn is None, show_api will automatically be set to False. | |
| """ | |
| ... | |
| def clear(self, | |
| fn: Callable | None, | |
| inputs: Component | Sequence[Component] | set[Component] | None = None, | |
| outputs: Component | Sequence[Component] | None = None, | |
| api_name: str | None | Literal[False] = None, | |
| scroll_to_output: bool = False, | |
| show_progress: Literal["full", "minimal", "hidden"] = "full", | |
| queue: bool | None = None, | |
| batch: bool = False, | |
| max_batch_size: int = 4, | |
| preprocess: bool = True, | |
| postprocess: bool = True, | |
| cancels: dict[str, Any] | list[dict[str, Any]] | None = None, | |
| every: float | None = None, | |
| trigger_mode: Literal["once", "multiple", "always_last"] | None = None, | |
| js: str | None = None, | |
| concurrency_limit: int | None | Literal["default"] = "default", | |
| concurrency_id: str | None = None, | |
| show_api: bool = True) -> Dependency: | |
| """ | |
| Parameters: | |
| fn: the function to call when this event is triggered. 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: List of gradio.components to use as inputs. If the function takes no inputs, this should be an empty list. | |
| outputs: List of gradio.components to use as outputs. If the function returns no outputs, this should be an empty list. | |
| api_name: 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. | |
| scroll_to_output: If True, will scroll to output component on completion | |
| show_progress: If True, will show progress animation while pending | |
| queue: 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: 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: Maximum number of inputs to batch together if this is called from the queue (only relevant if batch=True) | |
| preprocess: 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: If False, will not run postprocessing of component data before returning 'fn' output to the browser. | |
| cancels: 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: Run this event 'every' number of seconds while the client connection is open. Interpreted in seconds. | |
| trigger_mode: If "once" (default for all events except `.change()`) would not allow any submissions while an event is pending. If set to "multiple", unlimited submissions are allowed while pending, and "always_last" (default for `.change()` and `.key_up()` events) would allow a second submission after the pending event is complete. | |
| js: Optional frontend js method to run before running 'fn'. Input arguments for js method are values of 'inputs' and 'outputs', return should be a list of values for output components. | |
| concurrency_limit: If set, this is the maximum number of this event that can be running simultaneously. Can be set to None to mean no concurrency_limit (any number of this event can be running simultaneously). Set to "default" to use the default concurrency limit (defined by the `default_concurrency_limit` parameter in `Blocks.queue()`, which itself is 1 by default). | |
| concurrency_id: If set, this is the id of the concurrency group. Events with the same concurrency_id will be limited by the lowest set concurrency_limit. | |
| show_api: whether to show this event in the "view API" page of the Gradio app, or in the ".view_api()" method of the Gradio clients. Unlike setting api_name to False, setting show_api to False will still allow downstream apps to use this event. If fn is None, show_api will automatically be set to False. | |
| """ | |
| ... |