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cv-trace

A library for tracing images to SVG

npm version License: GPL v2

Install

npm install cv-trace
# or
pnpm add cv-trace

Start quickly

import { readFileSync, writeFileSync } from "fs";
import { binaryPreprocess, potrace, svgoOptimize } from "cv-trace";
import type { BinaryOptions } from "cv-trace";
// 1. Binary preprocessing
const layerData = await binaryPreprocess(imageBuffer, {
  threshold: [128, 255],
  color: "#000000",
} as BinaryOptions);
// 2. Vectorize with potrace
const result = await potrace(layerData);
// 3. Optimize SVG (optional)
result.svg = await svgoOptimize(result.svg);
writeFileSync("./output.svg", result.svg);
writeFileSync("./preview.png", result.preprocessedImage);
import { readFileSync, writeFileSync } from "fs";
import { quantizePreprocess, potrace, svgoOptimize } from "cv-trace";
import type { QuantizeOptions } from "cv-trace";
const imageBuffer = readFileSync("./test1.jpg");
// 1. Color quantization preprocessing  
const layerData = await quantizePreprocess(imageBuffer, {
  colorCount: 16,
  minPercent: 0,
  stack: true,
} as QuantizeOptions);
// 2. Vectorize with potrace
const result = await potrace(layerData);
// 3. Optimize SVG (optional)
result.svg = await svgoOptimize(result.svg);
writeFileSync("./output1.svg", result.svg);
writeFileSync("./preview1.png", result.preprocessedImage);

CommonJS : const { binaryPreprocess, potrace, optimizeSvg } = require("cv-trace");

Example

Original Image Vector Result
test.jpg output.svg
test1.jpg output1.svg
photos.png output1.svg

Core

Type

export type Layer = {
  id: string;
  zIndex: number;
  color: string;
  imageBuffer: Buffer;
}

export type OriginalMetadata = {
  width: number;
  height: number;
  format?: string;
}

export type LayerData = {
  layers: Layer[];
  preprocessedImage: Buffer;
  originalMetadata: OriginalMetadata;
}

export type VectorizeResult = {
  svg: string;
  preprocessedImage: Buffer;
  originalMetadata: OriginalMetadata;
}

Process Flow

(Image Buffer) --preprocess--> (LayerData) --trace--> (VectorizeResult) -- optimizer--> (VectorizeResult)

flowchart LR
    A[Image Buffer] --> B{Preprocess}
    B --> C[LayerData]
    C --> D{Trace}
    D --> E[VectorizeResult]
    E --> F{Optimizer}
    F --> G[Optimized SVG]

    B -.-> H[Preview Image]
Loading

Preprocess

Use Preprocessor to convert Image Buffer to LayerData ( with preprocessedImage for Preview )

Preprocessor

Convert the original image to layers of black and white binary image masks (Buffer), and carry layer and color information (although non-binary images are also supported, it is recommended to convert to binary images, because this provides better control)

Plan to support more Preprocessor in the future. And quantization according to color will be preferred (Actually, color quantization has been implemented, but we are thinking about how to make the code more elegant)

Trace

Tracer

Currently uses potrace to convert LayerData to a hierarchical SVG image

Plan to support more tracers in the future

Optimizer

Plan to use svgo to optimize svg string

Credits

LICENSE

GPL-2.0-or-later

Potrace is GPL LICENSE

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A library for tracing images to SVG

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