Convert raster images (PNG, JPG, etc.) into simplified SVG vector graphics using k-means colour quantization and contour tracing.
Installation
Requires Python 3.11+.
uv sync
Usage
uv run vectorify generate <filepath> <output> [options]
Example
uv run vectorify generate photo.png ./output.svg --n_colors 8 --smooth 2 --simplify 0.5
Update README images
Regenerate all example SVGs, PNGs, and grid images used in this README:
uv run vectorify update-readme
Arguments
| Argument | Type | Description |
|---|---|---|
filepath |
string | Path to the input image |
out_dir |
string | Directory for the output SVG |
Options
| Option | Type | Default | Description |
|---|---|---|---|
--n_colors |
int | 8 | Number of colours to quantize the image into |
--median_size |
float | 5 | Median filter kernel size for label smoothing (0 = disabled) |
--min_region |
float | 50 | Minimum connected region size in pixels (0 = disabled) |
--smooth |
float | 2 | Gaussian smoothing sigma applied to contours (0 = disabled) |
--simplify |
float | 0.5 | RDP simplification epsilon in pixels (0 = disabled) |
--buffer |
float | 1 | Outward normal offset to expand shapes and fill gaps |
Configuration
buffer
Expands each shape outward along its edge normals by the given pixel amount. Eliminates sub-pixel gaps between adjacent colour regions caused by smoothing or simplification.
median_size
Applies a median filter of this kernel size to the label map. Fills small holes, removes straggler pixels, and smooths region boundaries. Larger values produce more aggressive cleanup.
min_region
Removes connected components smaller than this many pixels, replacing them with their most common neighbouring colour. Catches isolated specks that the median filter misses.
n_colors
Number of distinct colours the image is quantized into via k-means clustering. Lower values produce a more simplified, poster-like result.
simplify
Epsilon value for the Ramer-Douglas-Peucker algorithm. Reduces the number of vertices in each contour path. Higher values = fewer vertices = simpler shapes.
smooth
Gaussian smoothing sigma applied to contour vertices. Rounds off jagged pixel-aligned edges into flowing curves. Applied before simplification.
1 maintainer
Metadata
1 maintainer
Release files for vectorify 0.1.3
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
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| vectorify-0.1.3.tar.gz | 5.3 MB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| vectorify-0.1.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 5.4 MB
Release files / vectorify-0.1.3.tar.gz
| Download URL | vectorify-0.1.3.tar.gz |
|---|---|
| Size | 5.3 MB |
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| Tags | Python 3 |
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