mirror of
https://github.com/visioncortex/vtracer.git
synced 2026-09-12 15:16:08 -07:00
Chris Tsang
46a1b90ccd
An alternative region-forming frontend selected by --clustering watershed (the color_mode field is replaced by clustering: color-cluster | bw | watershed across CLI, Rust, Python, and Node — it selects the algorithm, not a color space). The algorithm is the watershed hierarchy by volume on the 4-adjacency pixel graph, implemented from the papers: Cousty, Bertrand, Najman, Couprie, "Watershed Cuts: Minimum Spanning Forests and the Drop of Water Principle", IEEE TPAMI 31(8), 2009. Najman, Cousty, Perret, "Playing with Kruskal", ISMM 2013. Edge weights are the max per-channel color difference between adjacent pixels (no gradient image); a counting-sorted Kruskal pass builds the binary partition tree as a flat parents array; a leaves-to-root pass computes subtree area and volume; each merge's persistence (the volume of the smaller side, plateau-corrected) becomes its MST edge's saliency; and cutting the hierarchy is single-linkage over MST edges below the cut level. Watershed cuts label every pixel — no watershed-line pixel class — so the output is a strict, gapless partition that drops straight into both stacked and cutout modes. Integer arithmetic and flat u32 arrays throughout; deterministic across platforms; ~66 ms on a 1400x775 photo. The one dial, --watershed-detail (0..=255), maps exponentially to a target region count (each +25.5 doubles it) since the persistence distribution is far too skewed for a linear threshold. filter_speckle absorbs undersized basins into their most color-similar neighbour rather than dropping them, preserving the partition. The largest region is emitted first as a solid full-canvas background layer so stacked mode keeps its seam-free overdraw; the mosaic flatten is unaffected. Tests: partition invariant (disjoint masks tiling the canvas), detail monotonicity, min-area absorption, determinism, watershed cases in the pipeline/golden suites, stacked-vs-cutout interior equivalence, a watershed seam test, and SegmentKey coverage for the new params.
66 lines
2.5 KiB
Python
66 lines
2.5 KiB
Python
from typing import Optional
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__version__: str
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class Config:
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"""Conversion configuration. Construct with keyword arguments or a preset,
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mutate via properties, then call one of the ``convert_*`` methods."""
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def __init__(
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self,
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clustering: str = "color-cluster", # "color-cluster" | "bw" | "watershed"
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hierarchical: str = "stacked", # "stacked" | "cutout" (mosaic)
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mode: str = "spline", # "pixel" | "polygon" | "spline"
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filter_speckle: int = 4,
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color_precision: int = 6,
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layer_difference: int = 16,
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corner_threshold: int = 60,
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length_threshold: float = 4.0,
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max_iterations: int = 10,
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splice_threshold: int = 45,
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path_precision: int = 2,
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palette: Optional[list[str]] = None, # e.g. ["#112233", "#445566"]
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max_colors: Optional[int] = None, # auto-quantize target
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optimize: int = 1, # 0 | 1 | 2
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binary_threshold: int = 128, # bw: fixed cutoff 0..=255
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adaptive: bool = False, # bw: Bradley–Roth adaptive
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adaptive_window: int = 0, # bw adaptive: window px (0 = auto)
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adaptive_t: float = 15.0, # bw adaptive: % below local mean
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watershed_detail: int = 128, # watershed: cut level 0..=255
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) -> None: ...
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@staticmethod
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def bw() -> "Config": ...
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@staticmethod
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def poster() -> "Config": ...
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@staticmethod
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def photo() -> "Config": ...
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clustering: str
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hierarchical: str
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mode: str
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filter_speckle: int
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color_precision: int
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layer_difference: int
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corner_threshold: int
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length_threshold: float
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max_iterations: int
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splice_threshold: int
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path_precision: Optional[int]
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palette: list[str]
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max_colors: Optional[int]
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optimize: int
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binary_threshold: int
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adaptive: bool
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adaptive_window: int
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adaptive_t: float
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watershed_detail: int
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def convert_file(self, input_path: str, output_path: str) -> None: ...
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def convert_bytes(self, data: bytes, format: Optional[str] = None) -> str: ...
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def convert_pixels(self, rgba: bytes, width: int, height: int) -> str: ...
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def convert_file(input_path: str, output_path: str, config: Optional[Config] = None) -> None: ...
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def convert_bytes(data: bytes, config: Optional[Config] = None, format: Optional[str] = None) -> str: ...
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def convert_pixels(rgba: bytes, width: int, height: int, config: Optional[Config] = None) -> str: ...
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