Sketching + Inpainting Capabilities to Gradio

demo/blocks_mask/run.py

@@ -1,25 +1,135 @@
 import gradio as gr
-import os
+from gradio.components import Markdown as md
 
-def fn(mask):
-    return [mask["image"], mask["mask"]]
+demo = gr.Blocks()
 
+io1a = gr.Interface(lambda x: x, gr.Image(), gr.Image())
+io1b = gr.Interface(lambda x: x, gr.Image(source="webcam"), gr.Image())
+
+io2a = gr.Interface(lambda x: x, gr.Image(source="canvas"), gr.Image())
+io2b = gr.Interface(lambda x: x, gr.Sketchpad(), gr.Image())
+
+io3a = gr.Interface(
+    lambda x: [x["mask"], x["image"]],
+    gr.Image(source="upload", tool="sketch"),
+    [gr.Image(), gr.Image()],
+)
+
+io3b = gr.Interface(
+    lambda x: [x["mask"], x["image"]],
+    gr.ImageMask(),
+    [gr.Image(), gr.Image()],
+)
+
+io3b2 = gr.Interface(
+    lambda x: [x["mask"], x["image"]],
+    gr.ImageMask(),
+    [gr.Image(), gr.Image()],
+)
+
+io3b3 = gr.Interface(
+    lambda x: [x["mask"], x["image"]],
+    gr.ImageMask(),
+    [gr.Image(), gr.Image()],
+)
+
+io3c = gr.Interface(
+    lambda x: [x["mask"], x["image"]],
+    gr.Image(source="webcam", tool="sketch"),
+    [gr.Image(), gr.Image()],
+)
+
+io4a = gr.Interface(
+    lambda x: x, gr.Image(source="canvas", tool="color-sketch"), gr.Image()
+)
+io4b = gr.Interface(lambda x: x, gr.Paint(), gr.Image())
+
+io5a = gr.Interface(
+    lambda x: x, gr.Image(source="upload", tool="color-sketch"), gr.Image()
+)
+io5b = gr.Interface(lambda x: x, gr.ImagePaint(), gr.Image())
+io5c = gr.Interface(
+    lambda x: x, gr.Image(source="webcam", tool="color-sketch"), gr.Image()
+)
 
-demo = gr.Blocks()
 
 with demo:
-    with gr.Row():
-        with gr.Column():
-            img = gr.Image(
-                tool="sketch", source="upload", label="Mask", value=os.path.join(os.path.dirname(__file__), "lion.jpg")
-            )
-            with gr.Row():
-                btn = gr.Button("Run")
-        with gr.Column():
-            img2 = gr.Image()
-            img3 = gr.Image()
-
-    btn.click(fn=fn, inputs=img, outputs=[img2, img3])
+    md("# Different Ways to Use the Image Input Component")
+    md(
+        "**1a. Standalone Image Upload: `gr.Interface(lambda x: x, gr.Image(), gr.Image())`**"
+    )
+    io1a.render()
+    md(
+        "**1b. Standalone Image from Webcam: `gr.Interface(lambda x: x, gr.Image(source='webcam'), gr.Image())`**"
+    )
+    io1b.render()
+    md(
+        "**2a. Black and White Sketchpad: `gr.Interface(lambda x: x, gr.Image(source='canvas'), gr.Image())`**"
+    )
+    io2a.render()
+    md(
+        "**2b. Black and White Sketchpad: `gr.Interface(lambda x: x, gr.Sketchpad(), gr.Image())`**"
+    )
+    io2b.render()
+    md("**3a. Binary Mask with image upload:**")
+    md(
+        """```python
+gr.Interface(
+    lambda x: [x['mask'], x['image']],
+    gr.Image(source='upload', tool='sketch'),
+    [gr.Image(), gr.Image()],
+)
+```
+"""
+    )
+    io3a.render()
+    md("**3b. Binary Mask with image upload:**")
+    md(
+        """```python
+gr.Interface(
+    lambda x: [x['mask'], x['image']],
+    gr.ImageMask(),
+    [gr.Image(), gr.Image()],
+)
+```
+"""
+    )
+    io3b.render()
+    md("**3c. Binary Mask with webcam upload:**")
+    md(
+        """```python
+gr.Interface(
+    lambda x: [x['mask'], x['image']],
+    gr.Image(source='webcam', tool='sketch'),
+    [gr.Image(), gr.Image()],
+)
+```
+"""
+    )
+    io3c.render()
+    md(
+        "**4a. Color Sketchpad: `gr.Interface(lambda x: x, gr.Image(source='canvas', tool='color-sketch'), gr.Image())`**"
+    )
+    io4a.render()
+    md("**4b. Color Sketchpad: `gr.Interface(lambda x: x, gr.Paint(), gr.Image())`**")
+    io4b.render()
+    md(
+        "**5a. Color Sketchpad with image upload: `gr.Interface(lambda x: x, gr.Image(source='upload', tool='color-sketch'), gr.Image())`**"
+    )
+    io5a.render()
+    md(
+        "**5b. Color Sketchpad with image upload: `gr.Interface(lambda x: x, gr.ImagePaint(), gr.Image())`**"
+    )
+    io5b.render()
+    md(
+        "**5c. Color Sketchpad with webcam upload: `gr.Interface(lambda x: x, gr.Image(source='webcam', tool='color-sketch'), gr.Image())`**"
+    )
+    io5c.render()
+    md("**Tabs**")
+    with gr.Tab("One"):
+        io3b2.render()
+    with gr.Tab("Two"):
+        io3b3.render()
 
 
 if __name__ == "__main__":

demo/filter_records/run.py

@@ -12,7 +12,7 @@ def filter_records(records, gender):
             headers=["name", "age", "gender"],
             datatype=["str", "number", "str"],
             row_count=5,
-            col_count=(3, "fixed")
+            col_count=(3, "fixed"),
         ),
         gr.Dropdown(["M", "F", "O"]),
     ],

gradio/__init__.py

@@ -60,11 +60,14 @@
 from gradio.templates import (
     Files,
     Highlight,
+    ImageMask,
+    ImagePaint,
     List,
     Matrix,
     Mic,
     Microphone,
     Numpy,
+    Paint,
     Pil,
     PlayableVideo,
     Sketchpad,

gradio/components.py

@@ -32,6 +32,7 @@ class DataframeData(TypedDict):
 import numpy as np
 import pandas as pd
 import PIL
+import PIL.ImageOps
 from ffmpy import FFmpeg
 from markdown_it import MarkdownIt
 
@@ -1175,11 +1176,11 @@ def style(
         )
 
 
-@document("edit", "clear", "change", "stream", "change")
+@document("edit", "clear", "change", "stream", "change", "style")
 class Image(Editable, Clearable, Changeable, Streamable, IOComponent, ImgSerializable):
     """
     Creates an image component that can be used to upload/draw images (as an input) or display images (as an output).
-    Preprocessing: passes the uploaded image as a {numpy.array}, {PIL.Image} or {str} filepath depending on `type` -- unless `tool` is `sketch`. In the special case, a {dict} with keys `image` and `mask` is passed, and the format of the corresponding values depends on `type`.
+    Preprocessing: passes the uploaded image as a {numpy.array}, {PIL.Image} or {str} filepath depending on `type` -- unless `tool` is `sketch` AND source is one of `upload` or `webcam`. In these cases, a {dict} with keys `image` and `mask` is passed, and the format of the corresponding values depends on `type`.
     Postprocessing: expects a {numpy.array}, {PIL.Image} or {str} or {pathlib.Path} filepath to an image and displays the image.
     Examples-format: a {str} filepath to a local file that contains the image.
     Demos: image_mod, image_mod_default_image
@@ -1194,7 +1195,7 @@ def __init__(
         image_mode: str = "RGB",
         invert_colors: bool = False,
         source: str = "upload",
-        tool: str = "editor",
+        tool: str = None,
         type: str = "numpy",
         label: Optional[str] = None,
         show_label: bool = True,
@@ -1212,7 +1213,7 @@ def __init__(
             image_mode: "RGB" if color, or "L" if black and white.
             invert_colors: whether to invert the image as a preprocessing step.
             source: Source of image. "upload" creates a box where user can drop an image file, "webcam" allows user to take snapshot from their webcam, "canvas" defaults to a white image that can be edited and drawn upon with tools.
-            tool: Tools used for editing. "editor" allows a full screen editor, "select" provides a cropping and zoom tool, "sketch" allows you to create a mask over the image and both the image and mask are passed into the function.
+            tool: Tools used for editing. "editor" allows a full screen editor (and is the default if source is "upload" or "webcam"), "select" provides a cropping and zoom tool, "sketch" allows you to create a binary sketch (and is the default if source="canvas"), and "color-sketch" allows you to created a sketch in different colors. "color-sketch" can be used with source="upload" or "webcam" to allow sketching on an image. "sketch" can also be used with "upload" or "webcam" to create a mask over an image and in that case both the image and mask are passed into the function as a dictionary with keys "image" and "mask" respectively.
             type: The format the image is converted to before being passed into the prediction function. "numpy" converts the image to a numpy array with shape (width, height, 3) and values from 0 to 255, "pil" converts the image to a PIL image object, "file" produces a temporary file object whose path can be retrieved by file_obj.name, "filepath" passes a str path to a temporary file containing the image.
             label: component name in interface.
             show_label: if True, will display label.
@@ -1228,7 +1229,10 @@ def __init__(
         self.image_mode = image_mode
         self.source = source
         requires_permissions = source == "webcam"
-        self.tool = tool
+        if tool is None:
+            self.tool = "sketch" if source == "canvas" else "editor"
+        else:
+            self.tool = tool
         self.invert_colors = invert_colors
         self.test_input = deepcopy(media_data.BASE64_IMAGE)
         self.interpret_by_tokens = True
@@ -1279,9 +1283,10 @@ def update(
         return IOComponent.add_interactive_to_config(updated_config, interactive)
 
     def _format_image(
-        self, im: Optional[PIL.Image], fmt: str
+        self, im: Optional[PIL.Image]
     ) -> np.array | PIL.Image | str | None:
         """Helper method to format an image based on self.type"""
+        fmt = im.format
         if im is None:
             return im
         if self.type == "pil":
@@ -1314,36 +1319,37 @@ def generate_sample(self):
     def preprocess(self, x: str | Dict) -> np.array | PIL.Image | str | None:
         """
         Parameters:
-            x: base64 url data, or (if tool == "sketch) a dict of image and mask base64 url data
+            x: base64 url data, or (if tool == "sketch") a dict of image and mask base64 url data
         Returns:
-            image in requested format
+            image in requested format, or (if tool == "sketch") a dict of image and mask in requested format
         """
         if x is None:
             return x
-        if self.tool == "sketch":
+        if self.tool == "sketch" and self.source in ["upload", "webcam"]:
             x, mask = x["image"], x["mask"]
-
         im = processing_utils.decode_base64_to_image(x)
-        fmt = im.format
         with warnings.catch_warnings():
             warnings.simplefilter("ignore")
             im = im.convert(self.image_mode)
         if self.shape is not None:
             im = processing_utils.resize_and_crop(im, self.shape)
         if self.invert_colors:
             im = PIL.ImageOps.invert(im)
-        if self.source == "webcam" and self.mirror_webcam is True:
+        if (
+            self.source == "webcam"
+            and self.mirror_webcam is True
+            and self.tool != "color-sketch"
+        ):
             im = PIL.ImageOps.mirror(im)
 
-        if not (self.tool == "sketch"):
-            return self._format_image(im, fmt)
+        if self.tool == "sketch" and self.source in ["upload", "webcam"]:
+            mask_im = processing_utils.decode_base64_to_image(mask)
+            return {
+                "image": self._format_image(im),
+                "mask": self._format_image(mask_im),
+            }
 
-        mask_im = processing_utils.decode_base64_to_image(mask)
-        mask_fmt = mask_im.format
-        return {
-            "image": self._format_image(im, fmt),
-            "mask": self._format_image(mask_im, mask_fmt),
-        }
+        return self._format_image(im)
 
     def postprocess(self, y: np.ndarray | PIL.Image | str | Path) -> str:
         """

gradio/templates.py

@@ -31,7 +31,7 @@ class Webcam(components.Image):
     is_template = True
 
     def __init__(self, **kwargs):
-        super().__init__(source="webcam", **kwargs)
+        super().__init__(source="webcam", interactive=True, **kwargs)
 
 
 class Sketchpad(components.Image):
@@ -47,10 +47,48 @@ def __init__(self, **kwargs):
             source="canvas",
             shape=(28, 28),
             invert_colors=True,
+            interactive=True,
             **kwargs
         )
 
 
+class Paint(components.Image):
+    """
+    Sets source="canvas", tool="color-sketch"
+    """
+
+    is_template = True
+
+    def __init__(self, **kwargs):
+        super().__init__(
+            source="canvas", tool="color-sketch", interactive=True, **kwargs
+        )
+
+
+class ImageMask(components.Image):
+    """
+    Sets source="canvas", tool="sketch"
+    """
+
+    is_template = True
+
+    def __init__(self, **kwargs):
+        super().__init__(source="upload", tool="sketch", interactive=True, **kwargs)
+
+
+class ImagePaint(components.Image):
+    """
+    Sets source="upload", tool="color-sketch"
+    """
+
+    is_template = True
+
+    def __init__(self, **kwargs):
+        super().__init__(
+            source="upload", tool="color-sketch", interactive=True, **kwargs
+        )
+
+
 class Pil(components.Image):
     """
     Sets: type="pil"

gradio/version.txt

@@ -1 +1 @@
-3.3.1
+3.4b0

ui/packages/app/test/blocks_xray.spec.ts

@@ -61,13 +61,13 @@ test("can run an api request and display the data", async ({ page }) => {
 	await page.check("label:has-text('Covid')");
 	await page.check("label:has-text('Lung Cancer')");
 
-	const run_button = await page.locator("button", { hasText: /Run/ });
+	const run_button = await page.locator("button", { hasText: /Run/ }).first();
 
 	await Promise.all([
 		run_button.click(),
 		page.waitForResponse("**/api/predict/")
 	]);
 
-	const json = await page.locator("data-testid=json");
+	const json = await page.locator("data-testid=json").first();
 	await expect(json).toContainText(`Covid: 0.75, Lung Cancer: 0.25`);
 });

ui/packages/icons/src/Brush.svelte

@@ -0,0 +1,9 @@
+<svg width="100%" height="100%" viewBox="0 0 32 32"
+	><path
+		d="M28.828 3.172a4.094 4.094 0 0 0-5.656 0L4.05 22.292A6.954 6.954 0 0 0 2 27.242V30h2.756a6.952 6.952 0 0 0 4.95-2.05L28.828 8.829a3.999 3.999 0 0 0 0-5.657zM10.91 18.26l2.829 2.829l-2.122 2.121l-2.828-2.828zm-2.619 8.276A4.966 4.966 0 0 1 4.756 28H4v-.759a4.967 4.967 0 0 1 1.464-3.535l1.91-1.91l2.829 2.828zM27.415 7.414l-12.261 12.26l-2.829-2.828l12.262-12.26a2.047 2.047 0 0 1 2.828 0a2 2 0 0 1 0 2.828z"
+		fill="currentColor"
+	/><path
+		d="M6.5 15a3.5 3.5 0 0 1-2.475-5.974l3.5-3.5a1.502 1.502 0 0 0 0-2.121a1.537 1.537 0 0 0-2.121 0L3.415 5.394L2 3.98l1.99-1.988a3.585 3.585 0 0 1 4.95 0a3.504 3.504 0 0 1 0 4.949L5.439 10.44a1.502 1.502 0 0 0 0 2.121a1.537 1.537 0 0 0 2.122 0l4.024-4.024L13 9.95l-4.025 4.024A3.475 3.475 0 0 1 6.5 15z"
+		fill="currentColor"
+	/></svg
+>