Streamlit - Drawable Canvas
Streamlit component which provides a sketching canvas using Fabric.js.
Features
- 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
Installation
pip install streamlit-drawable-canvas
Example Usage
Copy this code snippet:
import pandas as pd
from PIL import Image
import streamlit as st
from streamlit_drawable_canvas import st_canvas
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)
canvas_result = st_canvas(
fill_color="rgba(255, 165, 0, 0.3)",
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",
)
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"])
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.
API
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.
Development
Install
cd frontend
npm install
conda create -n streamlit-drawable-canvas python=3.7
conda activate streamlit-drawable-canvas
pip install -e .
Run
Both webpack dev server and Streamlit should run at the same time.
cd frontend
npm run start
streamlit run app.py
Cypress integration tests
- 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
References