Streamlit Drawable Konva

Live demo: drawable-konva-demo.streamlit.app

Streamlit custom component (Components v2) that provides a sketching canvas using Konva.js / react-konva.

The public Python API is intentionally compatible with streamlit-drawable-canvas-fix (st_canvas → CanvasResult(image_data, json_data)). Object JSON uses Konva-oriented fields (x/y/points/…), not Fabric.js schemas.

Features

• Freehand, line, rect, circle, point, polygon, spline (Catmull-Rom through clicks) drawing
• Rect crop — single crop region with dimmed overlay (rect_crop mode)
• Image comparison (0.5) — st_image_comparison before/after slider companion
• Interaction locks & groups (0.3) — per-object locked, groupId, axis dragConstraint, transform_options
• Transform mode (move / scale / rotate); double-click to delete
• Viewport zoom, pan, and tilt (display-only; see below)
• Background color or image
• Realtime or on-demand updates to Streamlit
• Undo / redo / clear toolbar
• Returns RGBA image_data and scene json_data
• Host-agnostic mount (0.4) — standalone.js / DrawableKonvaCanvas.mount for Violit embeds

Viewport: zoom / pan / tilt

Enabled by default (enable_viewport_controls=True). These change how the canvas is viewed, not the stored object coordinates or exported image_data.

Try them in the demo page Zoom / pan / tilt.

Why Konva.js (vs Fabric.js)?

Konva is not universally “better” than Fabric — both are mature 2D canvas libraries. For this Streamlit component, Konva is the better fit.

Why we chose Konva here

1. React + Streamlit Components v2 — the official CCv2 React template maps cleanly onto react-konva. Drawing state stays in React; updates go out via setStateValue without fighting an imperative canvas singleton.
2. Layered export — background images can live on a non-exported layer while strokes/shapes export cleanly to image_data, matching the upstream “background is not round-tripped” behavior with less glue code.
3. Maintainability — freerdraw / shapes / polygon / transform are ordinary React event handlers and Konva nodes, which is easier to evolve next to a modern Vite + TypeScript frontend than a Fabric-centric CRA-era stack.
4. Performance for annotation UIs — Konva’s layer/stage model scales well for ROI / sketching workloads typical in Streamlit apps.

When Fabric may still win

• You need byte-compatible Fabric JSON (existing pipelines, demos, or tutorials that assume left/top/path Fabric schemas).
• You want Fabric’s mature free-transform / skew / complex text editing out of the box without reimplementing edge cases.

This package keeps a compatible Python API (st_canvas → CanvasResult) so apps can migrate from streamlit-drawable-canvas-fix, while accepting that json_data is Konva-oriented rather than a Fabric dump.

Install (uv)

uv sync

Build the frontend once (required before first Streamlit run):

cd streamlit_drawable_konva/frontend
npm install
npm run build
cd ../../

Editable install is handled by uv sync via the local pyproject.toml.

Demo

uv run streamlit run app.py

Development

CCv2 watches a production-style build into frontend/build (no separate webpack dev server URL). Use two terminals:

Terminal A — frontend watch build

cd streamlit_drawable_konva/frontend
npm install
npm run dev

Terminal B — Streamlit

uv sync
uv run streamlit run app.py

Refresh the browser after frontend rebuilds.

API

from streamlit_drawable_konva import st_canvas

result = st_canvas(
    fill_color="rgba(255, 165, 0, 0.3)",
    stroke_width=3,
    stroke_color="#000000",
    background_color="#eee",
    background_image=None,
    update_streamlit=True,
    height=400,
    width=600,
    drawing_mode="freedraw",  # freedraw|line|rect|rect_crop|circle|point|polygon|spline|transform|pan
    initial_drawing=None,
    display_toolbar=True,
    point_display_radius=3,
    enable_viewport_controls=True,
    key="canvas",
)

# result.image_data -> np.ndarray | None
# result.json_data  -> dict | None

Image comparison (st_image_comparison)

Before/after slider companion (same package; also available on Violit as vl_image_comparison):

from streamlit_drawable_konva import st_image_comparison

st_image_comparison(
    img1,  # PIL / path / ndarray / data URL
    img2,
    label1="Before",
    label2="After",
    width=700,
    starting_position=50,
)

Crop controls (rect_crop)

• Draw one rectangle; a new draw replaces the previous crop
• Drag the box or use handles to move / resize
• Double-click the crop box to remove it
• Read coordinates with crop_box_from_json(result.json_data) → (x, y, width, height)
• Crop overlay is excluded from exported image_data

Spline data (spline)

json_data stores control points only — the clicks you placed:

from streamlit_drawable_konva import splines_from_json, spline_control_points, sample_spline

splines = splines_from_json(result.json_data)
control = spline_control_points(splines[0])   # [(x, y), ...] from JSON
dense = sample_spline(splines[0], samples_per_segment=16)  # interpolated polyline

Each spline object looks like:

{"id": "...", "type": "spline", "points": [x1, y1, x2, y2, ...], "tension": 0.5}

The smooth curve is not in JSON; use sample_spline() (Catmull-Rom, same tension) when you need a dense path for masking, metrics, or export.

Interaction locks, groups, handles (0.3)

Object fields (in initial_drawing / json_data):

• locked: true — visible, not interactive in transform mode
• groupId + optional type: "group" descriptor — move/rotate together
• dragConstraint: { type: "axis", axis: {x, y}, min, max } — constrained handle drag
• Per-object: draggable, selectable, scalable, rotatable, deletable

Python kwarg:

st_canvas(..., transform_options={"allow_scale": False})

Polygon controls

• Left-click: add point
• Right-click: close polygon
• Double-click: remove latest point

Transform controls

• Click object to select
• Drag / resize / rotate with the transformer
• Double-click selected object to delete

Viewport controls

• Wheel / Zoom ±: zoom toward cursor (wheel) or canvas center (buttons)
• Pan mode / Alt-drag / middle-mouse: move the view
• Tilt ↶↷: rotate the view
• Reset view: 100% zoom, 0° tilt, centered pan

Migrating from Fabric drawable canvas

See MIGRATION.md for import renames, JSON field mapping, and behavioral differences vs streamlit-drawable-canvas / -fix.

Packaging notes

• Registered as streamlit-drawable-konva.st_canvas and streamlit-drawable-konva.st_image_comparison via the in-package streamlit_drawable_konva/pyproject.toml manifest (asset_dir = frontend/build).
• Requires Streamlit >= 1.51 (Components v2).
• Frontend toolchain targets Node >= 18 (Vite 6).
• Host-agnostic mount: frontend/build/standalone.js exposes window.DrawableKonvaCanvas.mount and window.DrawableKonvaCanvas.mountImageComparison for non-Streamlit hosts (e.g. Violit). Streamlit uses build/index.js and build/comparison.js.

Publishing (GitHub / PyPI / Streamlit Cloud / gallery)

Step-by-step instructions: PUBLISHING.md (includes updating GitHub / PyPI / Streamlit Cloud / gallery after the first release).

Current version: 0.5.0.

Order: push to GitHub → publish to PyPI → deploy app.py on Community Cloud → submit gallery/streamlit-drawable-konva.json as a PR to streamlit/gallery.

License

MIT