353 lines
14 KiB
JavaScript
353 lines
14 KiB
JavaScript
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/**
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* OpenCV 便捷适配层
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* 将 react-native-fast-opencv 的 invoke API 封装为 MaskSegmentCanvas 所需的 async 风格接口
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*/
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import RNFS from 'react-native-fs';
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import { OpenCV, ObjectType, DataTypes, ColorConversionCodes, ThresholdTypes, MorphShapes, MorphTypes, RetrievalModes, ContourApproximationModes, InterpolationFlags, } from 'react-native-fast-opencv';
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import { PNG_COMPRESSION, ensureMat8U, ensurePngFile, isPngPath, normalizePath, pngCacheName, readPngBgrBuffer, readPngHeaderFromBase64, } from './pngImage';
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import { rgbaBufferToSkiaImage } from './skiaImage';
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const IMREAD_GRAYSCALE = 0;
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export class WrappedMat {
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mat;
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cols;
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rows;
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channels;
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constructor(mat, cols, rows, channels = 3) {
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this.mat = mat;
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this.cols = cols;
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this.rows = rows;
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this.channels = channels;
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}
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release() {
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OpenCV.releaseBuffers([this.mat.id]);
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}
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async clone() {
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const cloned = OpenCV.invoke('clone', this.mat);
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return new WrappedMat(cloned, this.cols, this.rows, this.channels);
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}
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}
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export class ContourWrapper {
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pointVector;
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constructor(pointVector) {
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this.pointVector = pointVector;
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}
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release() {
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OpenCV.releaseBuffers([this.pointVector.id]);
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}
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}
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function createScalar(a, b, c) {
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if (b === undefined) {
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return OpenCV.createObject(ObjectType.Scalar, a);
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}
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if (c === undefined) {
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return OpenCV.createObject(ObjectType.Scalar, a, b, 0);
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}
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return OpenCV.createObject(ObjectType.Scalar, a, b, c);
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}
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async function readImageFromPath(path, grayscale = false) {
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const filePath = normalizePath(path);
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const base64 = await RNFS.readFile(filePath, 'base64');
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const srcMat = OpenCV.base64ToMat(base64);
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// 16-bit PNG 降级: toJSValue 可能崩溃，先解析 PNG 头
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let pngHeader;
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try {
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pngHeader = readPngHeaderFromBase64(base64);
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}
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catch {
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// 非 PNG 不传
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}
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const { mat, extraReleaseIds } = ensureMat8U(srcMat, pngHeader);
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const info = OpenCV.toJSValue(mat);
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if (grayscale) {
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const gray = OpenCV.createObject(ObjectType.Mat, info.rows, info.cols, DataTypes.CV_8UC1);
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OpenCV.invoke('cvtColor', mat, gray, ColorConversionCodes.COLOR_BGR2GRAY);
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OpenCV.releaseBuffers([
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...new Set([srcMat.id, mat.id, ...extraReleaseIds]),
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]);
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return new WrappedMat(gray, info.cols, info.rows, 1);
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}
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const channels = info.type === DataTypes.CV_8UC1
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? 1
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: info.type === DataTypes.CV_8UC4
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? 4
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: 3;
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if (mat.id !== srcMat.id) {
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OpenCV.releaseBuffers([srcMat.id]);
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}
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return new WrappedMat(mat, info.cols, info.rows, channels);
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}
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function createSize(width, height) {
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return OpenCV.createObject(ObjectType.Size, width, height);
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}
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/** OpenCV GaussianBlur 要求核宽高为正奇数 */
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function normalizeGaussianKernel(size) {
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const n = Math.max(1, Math.round(size));
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return n % 2 === 0 ? n + 1 : n;
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}
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const cv = {
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IMREAD_GRAYSCALE,
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THRESH_BINARY: ThresholdTypes.THRESH_BINARY,
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MORPH_RECT: MorphShapes.MORPH_RECT,
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MORPH_ELLIPSE: MorphShapes.MORPH_ELLIPSE,
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MORPH_OPEN: MorphTypes.MORPH_OPEN,
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MORPH_CLOSE: MorphTypes.MORPH_CLOSE,
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RETR_EXTERNAL: RetrievalModes.RETR_EXTERNAL,
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CHAIN_APPROX_SIMPLE: ContourApproximationModes.CHAIN_APPROX_SIMPLE,
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CHAIN_APPROX_NONE: ContourApproximationModes.CHAIN_APPROX_NONE,
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COLOR_BGR2GRAY: ColorConversionCodes.COLOR_BGR2GRAY,
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COLOR_BGR2Lab: ColorConversionCodes.COLOR_BGR2Lab,
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COLOR_Lab2BGR: ColorConversionCodes.COLOR_Lab2BGR,
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COLOR_GRAY2BGR: ColorConversionCodes.COLOR_GRAY2BGR,
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CV_8UC1: DataTypes.CV_8UC1,
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CV_16SC1: DataTypes.CV_16SC1,
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INTER_LINEAR: InterpolationFlags.INTER_LINEAR,
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INTER_NEAREST: InterpolationFlags.INTER_NEAREST,
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async ensurePngPath(path, cacheFileName) {
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const name = cacheFileName ?? pngCacheName(path, 'img');
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return ensurePngFile(path, name);
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},
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async imread(path, flags) {
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const filePath = normalizePath(path);
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if (isPngPath(filePath) && (await RNFS.exists(filePath))) {
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if (flags === IMREAD_GRAYSCALE) {
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return readImageFromPath(filePath, true);
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}
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const { buffer, cols, rows } = await readPngBgrBuffer(filePath);
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return cv.bgrBufferToMat(buffer, cols, rows);
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}
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const pngPath = await ensurePngFile(path, pngCacheName(path, 'imread'));
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if (flags === IMREAD_GRAYSCALE) {
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return readImageFromPath(pngPath, true);
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}
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const { buffer, cols, rows } = await readPngBgrBuffer(pngPath);
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return cv.bgrBufferToMat(buffer, cols, rows);
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},
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createMat(cols, rows, channels = 1) {
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const type = channels === 1
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? DataTypes.CV_8UC1
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: channels === 3
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? DataTypes.CV_8UC3
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: DataTypes.CV_8UC4;
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const mat = OpenCV.createObject(ObjectType.Mat, rows, cols, type);
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return new WrappedMat(mat, cols, rows, channels);
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},
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async cvtColor(src, code) {
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const dst = cv.createMat(src.cols, src.rows, 1);
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OpenCV.invoke('cvtColor', src.mat, dst.mat, code);
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return dst;
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},
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/** 三通道色彩空间转换（BGR/Lab 等） */
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cvtColorBgr(src, code) {
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const dst = cv.createMat(src.cols, src.rows, 3);
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OpenCV.invoke('cvtColor', src.mat, dst.mat, code);
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return dst;
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},
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/** 灰度 Mat → 三通道 BGR（供 Skia 显示） */
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grayToBgr(src) {
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const dst = cv.createMat(src.cols, src.rows, 3);
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OpenCV.invoke('cvtColor', src.mat, dst.mat, ColorConversionCodes.COLOR_GRAY2BGR);
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return dst;
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},
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/** 掩码统一为三通道 BGR；已是 3 通道则原样返回，色序由分割侧 swapBr 检测 */
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async ensureBgr3(src) {
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if (src.channels === 3) {
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return src;
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}
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const dst = cv.createMat(src.cols, src.rows, 3);
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const code = src.channels === 4
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? ColorConversionCodes.COLOR_BGRA2BGR
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: ColorConversionCodes.COLOR_GRAY2BGR;
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OpenCV.invoke('cvtColor', src.mat, dst.mat, code);
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return dst;
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},
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/** JS 二值缓冲（0/255）→ 单通道 Mat */
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binaryBufferToMat(buffer, cols, rows) {
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const mat = OpenCV.bufferToMat('uint8', rows, cols, 1, buffer);
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return new WrappedMat(mat, cols, rows, 1);
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},
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/** 连续 BGR 缓冲 → 三通道 Mat */
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bgrBufferToMat(buffer, cols, rows) {
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const mat = OpenCV.bufferToMat('uint8', rows, cols, 3, buffer);
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return new WrappedMat(mat, cols, rows, 3);
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},
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/** 将 JS 侧生成的灰度二值图写入临时 PGM 并读回 Mat */
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async grayBufferToMat(gray, cols, rows) {
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const path = `${RNFS.CachesDirectoryPath}/seg_bin_${Date.now()}.pgm`;
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const header = `P5\n${cols} ${rows}\n255\n`;
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const headerBytes = new TextEncoder().encode(header);
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const fileBytes = new Uint8Array(headerBytes.length + gray.length);
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fileBytes.set(headerBytes, 0);
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fileBytes.set(gray, headerBytes.length);
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let binary = '';
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const chunkSize = 8192;
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for (let i = 0; i < fileBytes.length; i += chunkSize) {
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const slice = fileBytes.subarray(i, i + chunkSize);
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binary += String.fromCharCode(...slice);
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}
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await RNFS.writeFile(path, btoa(binary), 'base64');
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try {
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return readImageFromPath(path, true);
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}
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finally {
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if (await RNFS.exists(path)) {
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await RNFS.unlink(path);
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}
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}
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},
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/**
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* 导出 Mat 像素。先 clone 保证内存连续，避免原生 matToBuffer 忽略 step 导致行错位。
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*/
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matToBuffer(src) {
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const continuous = OpenCV.invoke('clone', src.mat);
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try {
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const { buffer, cols, rows, channels } = OpenCV.matToBuffer(continuous, 'uint8');
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return { buffer, cols, rows, channels };
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}
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finally {
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OpenCV.releaseBuffers([continuous.id]);
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}
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},
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async inRangeBgr(src, color, tolerance, dst) {
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const lower = createScalar(Math.max(0, color.b - tolerance), Math.max(0, color.g - tolerance), Math.max(0, color.r - tolerance));
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const upper = createScalar(Math.min(255, color.b + tolerance), Math.min(255, color.g + tolerance), Math.min(255, color.r + tolerance));
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OpenCV.invoke('inRange', src.mat, lower, upper, dst.mat);
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},
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async resize(src, dst, size, interpolation = InterpolationFlags.INTER_LINEAR) {
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const dsize = createSize(size.width, size.height);
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OpenCV.invoke('resize', src.mat, dst.mat, dsize, 0, 0, interpolation);
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dst.cols = size.width;
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dst.rows = size.height;
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},
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/** BGR 缓冲原生缩放（掩码用语义色，默认最近邻） */
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async resizeBgrBuffer(buffer, srcCols, srcRows, dstCols, dstRows, interpolation = InterpolationFlags.INTER_NEAREST) {
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if (srcCols === dstCols && srcRows === dstRows) {
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return buffer;
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}
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const srcMat = cv.bgrBufferToMat(buffer, srcCols, srcRows);
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const dstMat = cv.createMat(dstCols, dstRows, 3);
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try {
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await cv.resize(srcMat, dstMat, { width: dstCols, height: dstRows }, interpolation);
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return cv.matToBuffer(dstMat).buffer;
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}
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finally {
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srcMat.release();
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dstMat.release();
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}
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},
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/** BGR Mat → RGBA 连续缓冲（供 Skia 直传） */
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async matToRgbaBuffer(src) {
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const dst = cv.createMat(src.cols, src.rows, 4);
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try {
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OpenCV.invoke('cvtColor', src.mat, dst.mat, ColorConversionCodes.COLOR_BGR2RGBA);
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const { buffer, cols, rows } = cv.matToBuffer(dst);
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return { buffer, cols, rows };
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}
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finally {
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dst.release();
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}
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},
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/** BGR Mat → Skia 图像（跳过低频/高频 PNG 编码） */
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async matToSkiaImage(src) {
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const { buffer, cols, rows } = await cv.matToRgbaBuffer(src);
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return rgbaBufferToSkiaImage(buffer, cols, rows);
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},
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/** 单通道灰度 Mat → Skia RGBA（跳过 BGR 伪彩 + 四通道 matToBuffer） */
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grayMatToSkiaImage(src) {
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const { buffer, cols, rows } = cv.matToBuffer(src);
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const pixelCount = cols * rows;
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const rgba = new Uint8Array(pixelCount * 4);
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for (let i = 0; i < pixelCount; i++) {
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const value = buffer[i];
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const offset = i * 4;
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rgba[offset] = value;
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rgba[offset + 1] = value;
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rgba[offset + 2] = value;
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rgba[offset + 3] = 255;
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}
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return rgbaBufferToSkiaImage(rgba, cols, rows);
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},
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/** 连续 BGR 缓冲 → Skia 图像（工作分辨率原图 / 高低频，复用 OpenCV 解码结果） */
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async bgrBufferToSkiaImage(buffer, cols, rows) {
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const mat = cv.bgrBufferToMat(buffer, cols, rows);
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try {
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return await cv.matToSkiaImage(mat);
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}
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finally {
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mat.release();
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}
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},
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async threshold(src, dst, thresh, maxval, type) {
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OpenCV.invoke('threshold', src.mat, dst.mat, thresh, maxval, type);
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},
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async getStructuringElement(shape, ksize) {
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const size = createSize(ksize.width, ksize.height);
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const kernel = OpenCV.invoke('getStructuringElement', shape, size);
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return new WrappedMat(kernel, ksize.width, ksize.height, 1);
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},
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async morphologyEx(src, dst, op, kernel) {
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OpenCV.invoke('morphologyEx', src.mat, dst.mat, op, kernel.mat);
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},
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async findContours(image, mode, method) {
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const contours = OpenCV.createObject(ObjectType.PointVectorOfVectors);
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OpenCV.invoke('findContours', image.mat, contours, mode, method);
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const data = OpenCV.toJSValue(contours);
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const wrappers = data.array.map((_, index) => {
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const pv = OpenCV.copyObjectFromVector(contours, index);
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return new ContourWrapper(pv);
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});
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OpenCV.releaseBuffers([contours.id]);
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return wrappers;
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},
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async contourArea(contour) {
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const result = OpenCV.invoke('contourArea', contour.pointVector, false);
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return result.value;
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},
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async boundingRect(contour) {
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const rect = OpenCV.invoke('boundingRect', contour.pointVector);
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const js = OpenCV.toJSValue(rect);
|
|||
|
|
return { x: js.x, y: js.y, width: js.width, height: js.height };
|
|||
|
|
},
|
|||
|
|
async arcLength(contour, closed) {
|
|||
|
|
const result = OpenCV.invoke('arcLength', contour.pointVector, closed);
|
|||
|
|
return result.value;
|
|||
|
|
},
|
|||
|
|
async approxPolyDP(contour, epsilon, closed) {
|
|||
|
|
const approx = OpenCV.createObject(ObjectType.PointVector);
|
|||
|
|
try {
|
|||
|
|
OpenCV.invoke('approxPolyDP', contour.pointVector, approx, epsilon, closed);
|
|||
|
|
return OpenCV.toJSValue(approx).array;
|
|||
|
|
}
|
|||
|
|
finally {
|
|||
|
|
OpenCV.releaseBuffers([approx.id]);
|
|||
|
|
}
|
|||
|
|
},
|
|||
|
|
async GaussianBlur(src, dst, ksize, sigma) {
|
|||
|
|
const width = normalizeGaussianKernel(ksize.width);
|
|||
|
|
const height = normalizeGaussianKernel(ksize.height);
|
|||
|
|
const size = createSize(width, height);
|
|||
|
|
OpenCV.invoke('GaussianBlur', src.mat, dst.mat, size, sigma);
|
|||
|
|
},
|
|||
|
|
extractChannel(src, dst, channel) {
|
|||
|
|
OpenCV.invoke('extractChannel', src.mat, dst.mat, channel);
|
|||
|
|
},
|
|||
|
|
convertTo(src, dst, rtype, alpha = 1, beta = 0) {
|
|||
|
|
OpenCV.invoke('convertTo', src.mat, dst.mat, rtype, alpha, beta);
|
|||
|
|
},
|
|||
|
|
async subtract(src1, src2, dst) {
|
|||
|
|
OpenCV.invoke('subtract', src1.mat, src2.mat, dst.mat);
|
|||
|
|
},
|
|||
|
|
async addWeighted(src1, alpha, src2, beta, gamma, dst) {
|
|||
|
|
if (src2) {
|
|||
|
|
OpenCV.invoke('addWeighted', src1.mat, alpha, src2.mat, beta, gamma, dst.mat);
|
|||
|
|
}
|
|||
|
|
else {
|
|||
|
|
OpenCV.invoke('addWeighted', src1.mat, alpha, src1.mat, 0, gamma, dst.mat);
|
|||
|
|
}
|
|||
|
|
},
|
|||
|
|
async imwrite(path, mat) {
|
|||
|
|
const filePath = normalizePath(path);
|
|||
|
|
OpenCV.saveMatToFile(mat.mat, filePath, 'png', PNG_COMPRESSION);
|
|||
|
|
},
|
|||
|
|
};
|
|||
|
|
export default cv;
|
|||
|
|
//# sourceMappingURL=opencvAdapter.js.map
|