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| r"""gr.ImageEditor() component.""" | |
| from __future__ import annotations | |
| import dataclasses | |
| import warnings | |
| from pathlib import Path | |
| from typing import Any, Iterable, List, Literal, Optional, TypedDict, Union, cast | |
| import numpy as np | |
| from gradio_client import utils as client_utils | |
| from gradio_client.documentation import document, set_documentation_group | |
| from PIL import Image as _Image # using _ to minimize namespace pollution | |
| import gradio.image_utils as image_utils | |
| from gradio import utils | |
| from gradio.components.base import Component | |
| from gradio.data_classes import FileData, GradioModel | |
| from gradio.events import Events | |
| set_documentation_group("component") | |
| _Image.init() # fixes https://github.com/gradio-app/gradio/issues/2843 | |
| ImageType = Union[np.ndarray, _Image.Image, str] | |
| class EditorValue(TypedDict): | |
| background: Optional[ImageType] | |
| layers: list[ImageType] | |
| composite: Optional[ImageType] | |
| class EditorExampleValue(TypedDict): | |
| background: Optional[str] | |
| layers: Optional[list[str | None]] | |
| composite: Optional[str] | |
| class EditorData(GradioModel): | |
| background: Optional[FileData] = None | |
| layers: List[FileData] = [] | |
| composite: Optional[FileData] = None | |
| class Eraser: | |
| """ | |
| A dataclass for specifying options for the eraser tool in the ImageEditor component. An instance of this class can be passed to the `eraser` parameter of `gr.ImageEditor`. | |
| Parameters: | |
| default_size: The default radius, in pixels, of the eraser tool. Defaults to "auto" in which case the radius is automatically determined based on the size of the image (generally 1/50th of smaller dimension). | |
| """ | |
| default_size: int | Literal["auto"] = "auto" | |
| class Brush(Eraser): | |
| """ | |
| A dataclass for specifying options for the brush tool in the ImageEditor component. An instance of this class can be passed to the `brush` parameter of `gr.ImageEditor`. | |
| Parameters: | |
| default_size: The default radius, in pixels, of the brush tool. Defaults to "auto" in which case the radius is automatically determined based on the size of the image (generally 1/50th of smaller dimension). | |
| colors: A list of colors to make available to the user when using the brush. Defaults to a list of 5 colors. | |
| default_color: The default color of the brush. Defaults to the first color in the `colors` list. | |
| color_mode: If set to "fixed", user can only select from among the colors in `colors`. If "defaults", the colors in `colors` are provided as a default palette, but the user can also select any color using a color picker. | |
| """ | |
| colors: Union[ | |
| list[str], | |
| str, | |
| None, | |
| ] = None | |
| default_color: Union[str, Literal["auto"]] = "auto" | |
| color_mode: Literal["fixed", "defaults"] = "defaults" | |
| def __post_init__(self): | |
| if self.colors is None: | |
| self.colors = [ | |
| "rgb(204, 50, 50)", | |
| "rgb(173, 204, 50)", | |
| "rgb(50, 204, 112)", | |
| "rgb(50, 112, 204)", | |
| "rgb(173, 50, 204)", | |
| ] | |
| if self.default_color is None: | |
| self.default_color = ( | |
| self.colors[0] if isinstance(self.colors, list) else self.colors | |
| ) | |
| class ImageEditor(Component): | |
| """ | |
| Creates an image component that can be used to upload and edit images (as an input) or display images (as an output). | |
| Preprocessing: passes the uploaded images as a dictionary with keys: `background`, `layers`, and `composite`. The values corresponding to `background` and `composite` are images, while `layers` is a list of images. The images are of type PIL.Image, np.array, or str filepath, depending on the `type` parameter. | |
| Postprocessing: expects a dictionary with keys: `background`, `layers`, and `composite`. The values corresponding to `background` and `composite` should be images or None, while `layers` should be a list of images. Images can be of type PIL.Image, np.array, or str filepath/URL. Or, the value can be simply a single image, in which case it will be used as the background. | |
| Examples-format: a dictionary with keys: `background`, `layers`, and `composite`. The values corresponding to `background` and `composite` should be strings or None, while `layers` should be a list of strings. The image corresponding to `composite`, if not None, is used as the example image. Otherwise, the image corresonding to `background` is used. The strings should be filepaths or URLs. Or, the value can be simply a single string filepath/URL to an image, which is used directly as the example image. | |
| Demos: image_editor | |
| """ | |
| EVENTS = [ | |
| Events.clear, | |
| Events.change, | |
| Events.select, | |
| Events.upload, | |
| ] | |
| data_model = EditorData | |
| def __init__( | |
| self, | |
| value: EditorValue | ImageType | None = None, | |
| *, | |
| height: int | str | None = None, | |
| width: int | str | None = None, | |
| image_mode: Literal[ | |
| "1", "L", "P", "RGB", "RGBA", "CMYK", "YCbCr", "LAB", "HSV", "I", "F" | |
| ] = "RGBA", | |
| sources: Iterable[Literal["upload", "webcam", "clipboard"]] = ( | |
| "upload", | |
| "webcam", | |
| "clipboard", | |
| ), | |
| type: Literal["numpy", "pil", "filepath"] = "numpy", | |
| label: str | None = None, | |
| every: float | None = None, | |
| show_label: bool | None = None, | |
| show_download_button: bool = True, | |
| 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, | |
| mirror_webcam: bool = True, | |
| show_share_button: bool | None = None, | |
| _selectable: bool = False, | |
| crop_size: tuple[int | float, int | float] | str | None = None, | |
| transforms: Iterable[Literal["crop"]] = ("crop",), | |
| eraser: Eraser | None | Literal[False] = None, | |
| brush: Brush | None | Literal[False] = None, | |
| ): | |
| """ | |
| Parameters: | |
| value: Optional initial image(s) to populate the image editor. Should be a dictionary with keys: `background`, `layers`, and `composite`. The values corresponding to `background` and `composite` should be images or None, while `layers` should be a list of images. Images can be of type PIL.Image, np.array, or str filepath/URL. Or, the value can be a callable, in which case the function will be called whenever the app loads to set the initial value of the component. | |
| height: The height of the displayed images, specified in pixels if a number is passed, or in CSS units if a string is passed. | |
| width: The width of the displayed images, specified in pixels if a number is passed, or in CSS units if a string is passed. | |
| image_mode: "RGB" if color, or "L" if black and white. See https://pillow.readthedocs.io/en/stable/handbook/concepts.html for other supported image modes and their meaning. | |
| sources: List of sources that can be used to set the background image. "upload" creates a box where user can drop an image file, "webcam" allows user to take snapshot from their webcam, "clipboard" allows users to paste an image from the clipboard. | |
| type: The format the images are converted to before being passed into the prediction function. "numpy" converts the images to numpy arrays with shape (height, width, 3) and values from 0 to 255, "pil" converts the images to PIL image objects, "filepath" passes images as str filepaths to temporary copies of the images. | |
| label: 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: 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: if True, will display label. | |
| show_download_button: If True, will display button to download image. | |
| container: If True, will place the component in a container - providing some extra padding around the border. | |
| scale: 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: 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: 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: If False, component will be hidden. | |
| elem_id: 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: 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: 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. | |
| mirror_webcam: If True webcam will be mirrored. Default is True. | |
| show_share_button: 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. | |
| crop_size: The size of the crop box in pixels. If a tuple, the first value is the width and the second value is the height. If a string, the value must be a ratio in the form `width:height` (e.g. "16:9"). | |
| transforms: The transforms tools to make available to users. "crop" allows the user to crop the image. | |
| eraser: The options for the eraser tool in the image editor. Should be an instance of the `gr.Eraser` class, or None to use the default settings. Can also be False to hide the eraser tool. | |
| brush: The options for the brush tool in the image editor. Should be an instance of the `gr.Brush` class, or None to use the default settings. Can also be False to hide the brush tool, which will also hide the eraser tool. | |
| """ | |
| self._selectable = _selectable | |
| self.mirror_webcam = mirror_webcam | |
| valid_types = ["numpy", "pil", "filepath"] | |
| if type not in valid_types: | |
| raise ValueError( | |
| f"Invalid value for parameter `type`: {type}. Please choose from one of: {valid_types}" | |
| ) | |
| self.type = type | |
| self.height = height | |
| self.width = width | |
| self.image_mode = image_mode | |
| valid_sources = ["upload", "webcam", "clipboard"] | |
| if isinstance(sources, str): | |
| sources = [sources] # type: ignore | |
| for source in sources: | |
| if source not in valid_sources: | |
| raise ValueError( | |
| f"`sources` must be a list consisting of elements in {valid_sources}" | |
| ) | |
| self.sources = sources | |
| self.show_download_button = show_download_button | |
| self.show_share_button = ( | |
| (utils.get_space() is not None) | |
| if show_share_button is None | |
| else show_share_button | |
| ) | |
| self.crop_size = crop_size | |
| self.transforms = transforms | |
| self.eraser = Eraser() if eraser is None else eraser | |
| self.brush = Brush() if brush is None else brush | |
| 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 convert_and_format_image( | |
| self, | |
| file: FileData | None, | |
| ) -> np.ndarray | _Image.Image | str | None: | |
| if file is None: | |
| return None | |
| im = _Image.open(file.path) | |
| if file.orig_name: | |
| p = Path(file.orig_name) | |
| name = p.stem | |
| suffix = p.suffix.replace(".", "") | |
| if suffix in ["jpg", "jpeg"]: | |
| suffix = "jpeg" | |
| else: | |
| name = "image" | |
| suffix = "png" | |
| with warnings.catch_warnings(): | |
| warnings.simplefilter("ignore") | |
| im = im.convert(self.image_mode) | |
| if self.crop_size and not isinstance(self.crop_size, str): | |
| im = image_utils.crop_scale( | |
| im, int(self.crop_size[0]), int(self.crop_size[1]) | |
| ) | |
| return image_utils.format_image( | |
| im, | |
| cast(Literal["numpy", "pil", "filepath"], self.type), | |
| self.GRADIO_CACHE, | |
| format=suffix, | |
| name=name, | |
| ) | |
| def preprocess(self, payload: EditorData | None) -> EditorValue | None: | |
| if payload is None: | |
| return payload | |
| bg = self.convert_and_format_image(payload.background) | |
| layers = ( | |
| [self.convert_and_format_image(layer) for layer in payload.layers] | |
| if payload.layers | |
| else None | |
| ) | |
| composite = self.convert_and_format_image(payload.composite) | |
| return { | |
| "background": bg, | |
| "layers": [x for x in layers if x is not None] if layers else [], | |
| "composite": composite, | |
| } | |
| def postprocess(self, value: EditorValue | ImageType | None) -> EditorData | None: | |
| if value is None: | |
| return None | |
| elif isinstance(value, dict): | |
| pass | |
| elif isinstance(value, (np.ndarray, _Image.Image, str)): | |
| value = {"background": value, "layers": [], "composite": value} | |
| else: | |
| raise ValueError( | |
| "The value to `gr.ImageEditor` must be a dictionary of images or a single image." | |
| ) | |
| layers = ( | |
| [ | |
| FileData( | |
| path=image_utils.save_image( | |
| cast(Union[np.ndarray, _Image.Image, str], layer), | |
| self.GRADIO_CACHE, | |
| ) | |
| ) | |
| for layer in value["layers"] | |
| ] | |
| if value["layers"] | |
| else [] | |
| ) | |
| return EditorData( | |
| background=FileData( | |
| path=image_utils.save_image(value["background"], self.GRADIO_CACHE) | |
| ) | |
| if value["background"] is not None | |
| else None, | |
| layers=layers, | |
| composite=FileData( | |
| path=image_utils.save_image( | |
| cast(Union[np.ndarray, _Image.Image, str], value["composite"]), | |
| self.GRADIO_CACHE, | |
| ) | |
| ) | |
| if value["composite"] is not None | |
| else None, | |
| ) | |
| def as_example( | |
| self, input_data: EditorExampleValue | str | None | |
| ) -> EditorExampleValue | None: | |
| def resolve_path(file_or_url: str | None) -> str | None: | |
| if file_or_url is None: | |
| return None | |
| input_data = str(file_or_url) | |
| # If an externally hosted image or a URL, don't convert to absolute path | |
| if self.proxy_url or client_utils.is_http_url_like(input_data): | |
| return input_data | |
| return str(utils.abspath(input_data)) | |
| if input_data is None: | |
| return None | |
| elif isinstance(input_data, str): | |
| input_data = { | |
| "background": input_data, | |
| "layers": [], | |
| "composite": input_data, | |
| } | |
| input_data["background"] = resolve_path(input_data["background"]) | |
| input_data["layers"] = ( | |
| [resolve_path(f) for f in input_data["layers"]] | |
| if input_data["layers"] | |
| else [] | |
| ) | |
| input_data["composite"] = resolve_path(input_data["composite"]) | |
| return input_data | |
| def example_inputs(self) -> Any: | |
| return { | |
| "background": "https://raw.githubusercontent.com/gradio-app/gradio/main/test/test_files/bus.png", | |
| "layers": [], | |
| "composite": None, | |
| } | |