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https://github.com/visioncortex/vtracer.git
synced 2026-09-12 07:06:03 -07:00
Chris Tsang
ef9496f792
A new pipeline slot between curve fitting and composition: CurvePasses rewrite each fitted contour, so mosaic mode transforms every shared boundary segment exactly once and the tessellation stays seam-free by construction. SimplifyCurves re-fits each smooth run between corners with the fewest cubics within the tolerance (Schneider's algorithm via a current flo_curves — visioncortex's copy is pinned to an old one and block-splits at 200 points), with tangents from the chain's own ends, corners kept in place, junction endpoints pinned bit-for-bit, and rings seamed at their sharpest junction. Off by default; polylines pass through untouched. Cityscape at tolerance 1: 229 -> 138 KB stacked, 103 -> 36 KB watershed cutout, with render diffs under golden noise. CurveFitter now returns Vec<FittedGeom> (promoted from mosaic::fit) so stacked contours flow through the same pass machinery; the optimizer's SimplifyPass is renamed CleanupPass to free the word.
vtracer (Python)
Python bindings for the vtracer
raster-to-vector framework. Built with pyo3 +
maturin; the core Rust crate stays pure (no I/O), and
this crate adds image decoding and a Pythonic API.
Install
pip install vtracer
Usage
import vtracer
# one-liners
vtracer.convert_file("in.png", "out.svg")
svg = vtracer.convert_bytes(open("in.png", "rb").read()) # -> str
svg = vtracer.convert_pixels(rgba_bytes, width, height) # raw RGBA8
# a rich, reusable configuration object
cfg = vtracer.Config(mode="polygon", filter_speckle=8)
cfg.hierarchical = "cutout" # seam-free mosaic
cfg.palette = ["#1b1b1b", "#e0c088", "#5a7d3c"] # snap to a fixed palette
cfg.max_colors = 8 # or auto-quantize
cfg.optimize = 2
svg = cfg.convert_bytes(data)
# presets
vtracer.Config.poster().convert_file("photo.jpg", "poster.svg")
vtracer.Config.bw().convert_file("scan.png", "lineart.svg")
Config
Constructor keyword arguments (all optional) — also exposed as mutable
properties, plus the presets Config.bw(), Config.poster(), Config.photo():
| arg | default | notes |
|---|---|---|
clustering |
"color-cluster" |
"color-cluster", "bw", or "watershed" |
hierarchical |
"stacked" |
"stacked" or "cutout" (mosaic) |
mode |
"spline" |
"pixel", "polygon", "spline" |
filter_speckle |
4 |
discard patches smaller than X px |
color_precision |
6 |
significant bits per channel |
layer_difference |
16 |
color diff between gradient layers |
corner_threshold |
60 |
degrees |
length_threshold |
4.0 |
px |
max_iterations |
10 |
|
splice_threshold |
45 |
degrees |
path_precision |
2 |
output decimal places |
palette |
None |
list of #rrggbb strings |
max_colors |
None |
auto-quantize target |
optimize |
1 |
0 off, 1 quantize+simplify, 2 + shorthands |
binary_threshold |
128 |
bw: fixed cutoff, foreground below it |
adaptive |
False |
bw: Bradley–Roth adaptive thresholding |
adaptive_window |
0 |
bw adaptive: window px (0 = auto) |
adaptive_t |
15.0 |
bw adaptive: % below local mean |
watershed_detail |
128 |
watershed: hierarchy cut level 0..=255 |
Each Config has convert_file(input, output), convert_bytes(data, format=None) -> str,
and convert_pixels(rgba, width, height) -> str.
Build from source
maturin develop # into the active virtualenv
maturin build --release # produce a wheel