Streamlit component which provides a sketching canvas using Fabric.js.

• Draw freely, lines, circles, boxes and polygons on the canvas, with options on stroke & fill
• Rotate, skew, scale, move any object of the canvas on demand
• Select a background color or image to draw on
• Get image data and every drawn object properties back to Streamlit !
• Choose to fetch back data in realtime or on demand with a button
• Undo, Redo or Delete canvas contents
• Save canvas data as JSON to reuse for another session

pip install streamlit-drawable-canvas

Copy this code snippet:

import pandas as pd
from PIL import Image
import streamlit as st
from streamlit_drawable_canvas import st_canvas

# Specify canvas parameters in application
drawing_mode = st.sidebar.selectbox(
    "Drawing tool:", ("point", "freedraw", "line", "rect", "circle", "transform")
)

stroke_width = st.sidebar.slider("Stroke width: ", 1, 25, 3)
if drawing_mode == 'point':
    point_display_radius = st.sidebar.slider("Point display radius: ", 1, 25, 3)
stroke_color = st.sidebar.color_picker("Stroke color hex: ")
bg_color = st.sidebar.color_picker("Background color hex: ", "#eee")
bg_image = st.sidebar.file_uploader("Background image:", type=["png", "jpg"])

realtime_update = st.sidebar.checkbox("Update in realtime", True)

    

# Create a canvas component
canvas_result = st_canvas(
    fill_color="rgba(255, 165, 0, 0.3)",  # Fixed fill color with some opacity
    stroke_width=stroke_width,
    stroke_color=stroke_color,
    background_color=bg_color,
    background_image=Image.open(bg_image) if bg_image else None,
    update_streamlit=realtime_update,
    height=150,
    drawing_mode=drawing_mode,
    point_display_radius=point_display_radius if drawing_mode == 'point' else 0,
    key="canvas",
)

# Do something interesting with the image data and paths
if canvas_result.image_data is not None:
    st.image(canvas_result.image_data)
if canvas_result.json_data is not None:
    objects = pd.json_normalize(canvas_result.json_data["objects"]) # need to convert obj to str because PyArrow
    for col in objects.select_dtypes(include=['object']).columns:
        objects[col] = objects[col].astype("str")
    st.dataframe(objects)

You will find more detailed examples on the demo app.

st_canvas(
    fill_color: str
    stroke_width: int
    stroke_color: str
    background_color: str
    background_image: Image
    update_streamlit: bool
    height: int
    width: int
    drawing_mode: str
    initial_drawing: dict
    display_toolbar: bool
    point_display_radius: int
    key: str
)

• fill_color : Color of fill for Rect in CSS color property. Defaults to "#eee".
• stroke_width : Width of drawing brush in CSS color property. Defaults to 20.
• stroke_color : Color of drawing brush in hex. Defaults to "black".
• background_color : Color of canvas background in CSS color property. Defaults to "" which is transparent. Overriden by background_image. Changing background_color will reset the drawing.
• background_image : Pillow Image to display behind canvas. Automatically resized to canvas dimensions. Being behind the canvas, it is not sent back to Streamlit on mouse event. Overrides background_color. Changes to this will reset canvas contents.
• update_streamlit : Whenever True, send canvas data to Streamlit when object/selection is updated or mouse up.
• height : Height of canvas in pixels. Defaults to 400.
• width : Width of canvas in pixels. Defaults to 600.
• drawing_mode : Enable free drawing when "freedraw", object manipulation when "transform", otherwise create new objects with "line", "rect", "circle" and "polygon". Defaults to "freedraw".
  • On "polygon" mode, double-clicking will remove the latest point and right-clicking will close the polygon.
• initial_drawing : Initialize canvas with drawings from here. Should be the json_data output from other canvas. Beware: if you try to import a drawing from a bigger/smaller canvas, no rescaling is done in the canvas and the import could fail.
• point_display_radius : To make points visible on the canvas, they are drawn as circles. This parameter modifies the radius of the displayed circle.
• display_toolbar : If False, don't display the undo/redo/delete toolbar.

Example:

import streamlit as st
from streamlit_drawable_canvas import st_canvas

canvas_result = st_canvas()
st_canvas(initial_drawing=canvas_result.json_data)

• display_toolbar : Display the undo/redo/reset toolbar.
• key : An optional string to use as the unique key for the widget. Assign a key so the component is not remount every time the script is rerun.

• JS side

cd frontend
npm install

• Python side

conda create -n streamlit-drawable-canvas python=3.7
conda activate streamlit-drawable-canvas
pip install -e .

Both webpack dev server and Streamlit should run at the same time.

• JS side

cd frontend
npm run start

• Python side

streamlit run app.py

• Install Cypress: cd e2e; npm i or npx install cypress (with --force if cache problem)
• Start Streamlit frontend server: cd streamlit_drawable_canvas/frontend; npm run start
• Start Streamlit test script: streamlit run e2e/app_to_test.py
• Start Cypress app: cd e2e; npm run cypress:open

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• Drawing with FabricJS and TypeScript Part 7: Undo/Redo
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