// Type definitions for AutoJs6 internal module images // // Definitions by: SuperMonster003 // TypeScript Version: 4.3.5 // // Last modified: Oct 21, 2021 /// /** * @Source %AutoJs6Assets%/modules/__images__.js */ declare namespace Internal { import ColorInt = Colors.ColorInt; import DetectionAlgorithm = Colors.DetectionAlgorithm; import ConversionCodes = Colors.ConversionCodes; interface Images { (); /** * @see org.autojs.autojs.runtime.api.Images.captureScreen */ captureScreen(): ImageWrapper; /** * @see org.autojs.autojs.runtime.api.Images.captureScreen */ captureScreen(path: string): boolean; /** * @see org.autojs.autojs.runtime.api.Images.read */ read(path: string): ImageWrapper; /** * @see org.autojs.autojs.runtime.api.Images.copy */ copy(image: ImageWrapper): ImageWrapper; /** * @see org.autojs.autojs.runtime.api.Images.load */ load(src: string): ImageWrapper; /** * @see org.autojs.autojs.runtime.api.Images.clip */ clip(image: ImageWrapper, x: number, y: number, w: number, h: number): ImageWrapper; clip(image: ImageWrapper, region: OmniRegion): ImageWrapper; /** * @see org.autojs.autojs.runtime.api.Images.pixel */ pixel(image: ImageWrapper, x: number, y: number): ColorInt; /** * Applies an adaptive threshold to an array. * zh-CN: 自适应阈值化 * @param src - source 8-bit single-channel image. * zh-CN: 输入图像, 8 位单通道浮点类型 * @param maxValue - non-zero value assigned to the pixels for which the condition is satisfied. * zh-CN: 预设满足条件的最大值 * @param adaptiveMethod - adaptive thresholding algorithm to use (without "ADAPTIVE_THRESH_" prefix). * zh-CN: 指定自适应阈值算法 (参数不包含 "ADAPTIVE_THRESH_" 前缀) * @param thresholdType - thresholding type that must be either THRESH_BINARY or THRESH_BINARY_INV (without "THRESH_" prefix). * zh-CN: 指定阈值类型, 二进制阈值或反二进制阈值 (参数不包含 "THRESH_" 前缀) * @param blockSize - size of a pixel neighborhood that is used to calculate a threshold value for the pixel: 3, 5, 7, and so on. * zh-CN: 表示邻域块大小, 用来计算区域阈值, 一般选 3, 5, 7 等 * @param C - constant subtracted from the mean or weighted mean. Normally, it is positive but may be zero or negative as well. * zh-CN: 参数 C 表示与算法有关的参数, 它是一个从均值或加权均值提取的常数, 可以是负数 * @example * images.requestScreenCapture(false); * images.adaptiveThreshold( * images.grayscale(images.captureScreen()), 255, "GAUSSIAN_C", "BINARY_INV", 9, 6 * ); * @example Source code summary (zh-CN: 源代码摘要) * let javaImages = runtime.getImages(); * function initIfNeeded() { * javaImages.initOpenCvIfNeeded(); * } * images.adaptiveThreshold = function (src, maxValue, adaptiveMethod, thresholdType, blockSize, C) { * initIfNeeded(); * let mat = new Mat(); * adaptiveMethod = Imgproc["ADAPTIVE_THRESH_" + adaptiveMethod]; * thresholdType = Imgproc["THRESH_" + thresholdType]; * Imgproc.adaptiveThreshold(src.mat, mat, maxValue, adaptiveMethod, thresholdType, blockSize, C); * return images.matToImage(mat); * }; * @see org.opencv.imgproc.Imgproc * @see org.autojs.autojs.core.opencv.Mat * @see https://blog.csdn.net/sinat_36264666/article/details/77586964 * @see https://blog.csdn.net/abcvincent/article/details/78822191 */ adaptiveThreshold( src: ImageWrapper, maxValue: number, adaptiveMethod: Images.AdaptiveThresholdTypes, thresholdType: 'BINARY' | 'BINARY_INV', blockSize: number, C: number, ): ImageWrapper; /** * Blurs an image using the normalized box filter. * zh-CN: 均值滤波: 使用标准化的盒式过滤器平滑图像 * @param src - input image; it can have any number of channels, * which are processed independently, but the depth should be CV_8U, CV_16U, CV_16S, CV_32F or CV_64F. * zh-CN: 源图像: 通道数不限, 但位深应为 CV_8U / CV_16U / CV_16S / CV_32F 或 CV_64F * @param ksize - blurring kernel size. * zh-CN: 滤波模板尺寸: 用于平滑操作的模板大小 * @param [anchor=[-1, -1]] - anchor point; default value Point(-1,-1) means that the anchor is at the kernel center. * zh-CN: 锚点: 默认值为 Point(-1, -1), 表示锚点在模板中心 * @param [type="DEFAULT"] - border mode used to extrapolate pixels outside of the image (without "BORDER_" prefix). * BORDER_WRAP is not supported. * zh-CN: 边界模式: 指定处理边界像素时如何确定图像范围外像素的取值 (参数不包含 "BORDER_" 前缀) , 不支持 BORDER_WRAP * @example * images.requestScreenCapture(false); * let dst = images.blur(images.captureScreen(), [3, 3]); * @example Source code summary (zh-CN: 源代码摘要) * let javaImages = runtime.getImages(); * images.blur = function (src, ksize, anchor, type) { * initIfNeeded(); * let mat = new Mat(); * ksize = newSize(ksize); * type = Core["BORDER_" + (type || "DEFAULT")]; * if (anchor === undefined) { * Imgproc.blur(src.mat, mat, ksize); * } else { * Imgproc.blur(src.mat, mat, ksize, new Point(anchor[0], anchor[1]), type); * } * return images.matToImage(mat); * }; * function initIfNeeded() { * javaImages.initOpenCvIfNeeded(); * } * function newSize(size) { * if (!Array.isArray(size)) { * size = [size, size]; * } * if (size.length === 1) { * size = [size[0], size[0]]; * } * return new Size(size[0], size[1]); * } * @see org.autojs.autojs.core.opencv.Mat * @see org.opencv.imgproc.Imgproc * @see org.opencv.core.Core * @see org.opencv.core.Size * @see org.opencv.core.Point * @see https://docs.opencv.org/3.4/javadoc/org/opencv/imgproc/Imgproc.html#blur(org.opencv.core.Mat,org.opencv.core.Mat,org.opencv.core.Size,org.opencv.core.Point,int) * @see https://blog.csdn.net/keith_bb/article/details/54382426 */ blur( src: ImageWrapper, ksize: Side | [Width, Height?], anchor?: [X, Y], type?: Images.BorderTypes, ): ImageWrapper; /** * Concatenate (combine) two images vertically and horizontally. * This method does not change the existing images, but instead returns a new concatenated image. * zh-CN: 连接两个图像. 若两图像连接处的尺寸不同, 则尺寸较小的图像将适当居中 (未验证 by SuperMonster003 as of Jul 25, 2020) * @param imgA - source image 1 * @param imgB - source image 2 * @param [direction="RIGHT"] - direction of concatenation * @example * images.requestScreenCapture(false); * let dst = images.concat(images.captureScreen(), images.read(files.path("./test.png")), "BOTTOM"); * @example Source code summary (zh-CN: 源代码摘要) * let javaImages = runtime.getImages(); * images.concat = function (imgA, imgB, direction) { * initIfNeeded(); * direction = direction || "right"; * return javaImages.concat(imgA, imgB, android.view.Gravity[direction.toUpperCase()]); * }; * function initIfNeeded() { * javaImages.initOpenCvIfNeeded(); * } * @see org.autojs.autojs.runtime.api.Images.concat */ concat( imgA: ImageWrapper, imgB: ImageWrapper, direction?: 'LEFT' | 'RIGHT' | 'TOP' | 'BOTTOM', ): ImageWrapper; /** * Converts an image from one color space to another. * zh-CN: 颜色空间转换 * @param src - input image: 8-bit unsigned, 16-bit unsigned (CV_16UC...), or single-precision floating-point. * zh-CN: 输入图像, 支持 8 位无符号整形, 16 位无符号整形或单精度浮点数 * @param code - color space conversion code (without "COLOR_" prefix). * zh-CN: 颜色空间转换标识符 (参数不包含 "COLOR_" 前缀) * @param dstCn - number of channels in the destination image; * if the parameter is 0, the number of the channels is derived automatically from src and code. * zh-CN: 目标图像的通道数, 该参数为 0 时, 目标图像根据源图像的通道数和具体操作自动决定 * @example * images.requestScreenCapture(false); * let dst = images.cvtColor(images.captureScreen(), "BGR2BGRA"); * @example Source code summary (zh-CN: 源代码摘要) * let javaImages = runtime.getImages(); * images.cvtColor = function (src, code, dstCn) { * initIfNeeded(); * let mat = new Mat(); * code = Imgproc["COLOR_" + code]; * if (dstCn === undefined) { * Imgproc.cvtColor(src.mat, mat, code); * } else { * Imgproc.cvtColor(src.mat, mat, code, dstCn); * } * return images.matToImage(mat); * }; * function initIfNeeded() { * javaImages.initOpenCvIfNeeded(); * } * @see org.opencv.imgproc.Imgproc * @see org.opencv.imgproc.Imgproc.cvtColor * @see https://docs.opencv.org/3.1.0/d7/d1b/group__imgproc__misc.html#ga4e0972be5de079fed4e3a10e24ef5ef0 */ cvtColor(src: ImageWrapper, code: ConversionCodes, dstCn?: number): ImageWrapper; /** * @param img * @param color * @param x * @param y * @param [threshold=4] * @param [algorithm="diff"] * @example * images.requestScreenCapture(false); * let like = idMatches(/.*like_icon/).findOnce(); * if (like) { * let bounds = like.bounds(); * let [x, y] = [bounds.centerX(), bounds.centerY()]; * if (!images.detectsColor(images.captureScreen(), "#FED9A8", x, y)) { * like.click(); * } * } * @example Source code summary (zh-CN: 源代码摘要) * const defaultColorThreshold = 4; * let javaImages = runtime.getImages(); * images.detectsColor = function (img, color, x, y, threshold, algorithm) { * initIfNeeded(); * color = parseColor(color); * algorithm = algorithm || "diff"; * threshold = threshold || defaultColorThreshold; * let colorDetector = getColorDetector(color, algorithm, threshold); * let pixel = images.pixel(img, x, y); * return colorDetector.detectsColor(colors.red(pixel), colors.green(pixel), colors.blue(pixel)); * }; * function initIfNeeded() { * javaImages.initOpenCvIfNeeded(); * } * function parseColor(color) { * if (typeof (color) === 'string') { * color = colors.parseColor(color); * } * return color; * } * function getColorDetector(color, algorithm, threshold) { * switch (algorithm) { * case "rgb": * return new org.autojs.autojs.core.image.ColorDetector.RGBDistanceDetector(color, threshold); * case "equal": * return new org.autojs.autojs.core.image.ColorDetector.EqualityDetector(color); * case "diff": * return new org.autojs.autojs.core.image.ColorDetector.DifferenceDetector(color, threshold); * case "rgb+": * return new org.autojs.autojs.core.image.ColorDetector.WeightedRGBDistanceDetector(color, threshold); * case "hs": * return new org.autojs.autojs.core.image.ColorDetector.HSDistanceDetector(color, threshold); * } * throw new Error("Unknown algorithm: " + algorithm); * } */ detectsColor( img: ImageWrapper, color: Color$, x: number, y: number, threshold?: number, algorithm?: DetectionAlgorithm, ): boolean; /** * @example * images.requestScreenCapture(false); * let capt = images.captureScreen(); * let points_1 = images.findAllPointsForColor(capt, "#FF0000", {threshold: 51}); * let points_2 = images.findAllPointsForColor(capt, "#FF0000", {similarity: 0.8}); // same as above * let points_3 = images.findAllPointsForColor(capt, "#00FF00", { * region: [400, 500, 300, 200], * threshold: 4, * }); * if (points_3.length) { * points_3.forEach((point_3) => { * console.log(point_3.x + ", " + point_3.y); * }); * } * @example Source code summary (zh-CN: 源代码摘要) * const defaultColorThreshold = 4; * let javaImages = runtime.getImages(); * let colorFinder = javaImages.colorFinder; * images.findAllPointsForColor = function (img, color, options) { * initIfNeeded(); * color = parseColor(color); * options = options || {}; * let threshold; * if (options.similarity) { * threshold = parseInt(255 * (1 - options.similarity)); * } else { * threshold = options.threshold || defaultColorThreshold; * } * if (options.region) { * return toPointArray(colorFinder.findAllPointsForColor(img, color, threshold, buildRegion(options.region, img))); * } else { * return toPointArray(colorFinder.findAllPointsForColor(img, color, threshold, null)); * } * }; * function initIfNeeded() { * javaImages.initOpenCvIfNeeded(); * } * function parseColor(color) { * if (typeof (color) === 'string') { * color = colors.parseColor(color); * } * return color; * } * function buildRegion(region, img) { * if (region === undefined) { * region = []; * } * let x = region[0] === undefined ? 0 : region[0]; * let y = region[1] === undefined ? 0 : region[1]; * let width = region[2] === undefined ? img.getWidth() - x : region[2]; * let height = region[3] === undefined ? (img.getHeight() - y) : region[3]; * let r = new org.opencv.core.Rect(x, y, width, height); * if (x < 0 || y < 0 || x + width > img.width || y + height > img.height) { * throw new Error('out of region: region = [' + [x, y, width, height] + "], image.size = [' + [img.width, img.height] + ']"); * } * return r; * } * function toPointArray(points) { * let arr = []; * for (let i = 0; i < points.length; i++) { * arr.push(points[i]); * } * return arr; * } * @see findPointsByColor */ findAllPointsForColor(img: ImageWrapper, color: Color$, options?: { similarity?: number, threshold?: number, region?: OmniRegion, }): OpenCV.Points; /** * @param grayImg - 8-bit, single-channel, grayscale input image. * zh-CN: 源图像: 单通道 8 位灰度图像 * @param [options={}] * @param [options.region] * @param [options.dp=1] - Inverse ratio of the accumulator resolution to the image resolution. * For example, if dp=1 , the accumulator has the same resolution as the input image. * If dp=2 , the accumulator has half as big width and height. * zh-CN: 图像分辨率与累加器 (参数空间) 分辨率的比值 (圆弧圆心的累计分辨率). * dp=1, 累加器 (参数空间) 与图像像素空间的分辨率相同. * dp=2, 累加器 (参数空间) 的分辨率为像素空间的一半 (即累加器分辨率受影响更小) * @param [options.minDst=grayImg.height/8] - Minimum distance between the centers of the detected circles. * If the parameter is too small, multiple neighbor circles may be falsely detected in addition to a true one. * If it is too large, some circles may be missed. * zh-CN: 圆心之间最小距离. 若距离太小会产生很多相交的圆. 若距离太大则会漏掉正确的圆 * @param [options.param1=100] - First method-specific parameter. * It is the higher threshold of the two passed to the Canny edge detector (the lower one is twice smaller). * zh-CN: 用于 Canny 的边缘阀值上限. (下限为上限的一半) * @param [options.param2=100] - Second method-specific parameter. * It is the accumulator threshold for the circle centers at the detection stage. * The smaller it is, the more false circles may be detected. * Circles, corresponding to the larger accumulator values, will be returned first. * zh-CN: 累加器阈值 (基于圆心的最小投票数). 阈值越小, 检测到的圆越多 * @param [options.minRadius=0] - Minimum circle radius. * zh-CN: 最小圆半径 * @param [options.maxRadius=0] - Maximum circle radius. * If <= 0, uses the maximum image dimension. * If < 0, returns centers without finding the radius. * zh-CN: 最大圆半径 * @example * images.requestScreenCapture(false); * let capt = images.captureScreen(); * let results = images.findCircles(images.grayscale(capt), { * region: [120, 144, 720 - 120 * 2, 1280 - 144 * 2], * dp: 1, * minDst: 720 * 0.091, * param1: 15, * param2: 15, * minRadius: 720 * 0.06, * maxRadius: 720 * 0.078, * }).map((o) => { * o.radius = +o.radius.toFixed(2); * return o; * }); * console.log(results); * @example Source code summary (zh-CN: 源代码摘要) * let javaImages = runtime.getImages(); * images.findCircles = function (grayImg, options) { * initIfNeeded(); * options = options || {}; * let mat = options.region === undefined ? grayImg.mat : new Mat(grayImg.mat, buildRegion(options.region, grayImg)); * let resultMat = new Mat(); * let dp = options.dp === undefined ? 1 : options.dp; * let minDst = options.minDst === undefined ? grayImg.height / 8 : options.minDst; * let param1 = options.param1 === undefined ? 100 : options.param1; * let param2 = options.param2 === undefined ? 100 : options.param2; * let minRadius = options.minRadius === undefined ? 0 : options.minRadius; * let maxRadius = options.maxRadius === undefined ? 0 : options.maxRadius; * Imgproc.HoughCircles(mat, resultMat, Imgproc.CV_HOUGH_GRADIENT, dp, minDst, param1, param2, minRadius, maxRadius); * let result = []; * for (let i = 0; i < resultMat.rows(); i++) { * for (let j = 0; j < resultMat.cols(); j++) { * let d = resultMat.get(i, j); * result.push({x: d[0], y: d[1], radius: d[2]}); * } * } * if (options.region !== undefined) { * mat.release(); * } * resultMat.release(); * return result; * }; * function initIfNeeded() { * javaImages.initOpenCvIfNeeded(); * } * function buildRegion(region, img) { * if (region === undefined) { * region = []; * } * let x = region[0] === undefined ? 0 : region[0]; * let y = region[1] === undefined ? 0 : region[1]; * let width = region[2] === undefined ? img.getWidth() - x : region[2]; * let height = region[3] === undefined ? (img.getHeight() - y) : region[3]; * let r = new org.opencv.core.Rect(x, y, width, height); * if (x < 0 || y < 0 || x + width > img.width || y + height > img.height) { * throw new Error('out of region: region = [' + [x, y, width, height] + "], image.size = [' + [img.width, img.height] + ']"); * } * return r; * } * @see org.opencv.imgproc.Imgproc.HoughCircles * @see org.autojs.autojs.core.opencv.Mat * @see org.opencv.imgproc.Imgproc * @see https://docs.opencv.org/3.4/javadoc/org/opencv/imgproc/Imgproc.html#HoughCircles(org.opencv.core.Mat,org.opencv.core.Mat,int,double,double,double,double,int,int) */ findCircles(grayImg: ImageWrapper, options?: Images.Circles.Options): Images.Circles.Result; /** * @example * images.requestScreenCapture(false); * let capt = images.captureScreen(); * let point_1 = images.findColor(capt, "#FF0000", {threshold: 51}); * let point_2 = images.findColor(capt, "#FF0000", {similarity: 0.8}); // same as above * let point_3 = images.findColor(capt, "#00FF00", { * region: [400, 500, 300, 200], * threshold: 4, * }); * if (point_3) { * toastLog(point_3.x + ", " + point_3.y); * } * @example Source code summary (zh-CN: 源代码摘要) * const defaultColorThreshold = 4; * let javaImages = runtime.getImages(); * let colorFinder = javaImages.colorFinder; * images.findColor = function (img, color, options) { * initIfNeeded(); * color = parseColor(color); * options = options || {}; * let threshold; * if (options.similarity) { * threshold = parseInt(255 * (1 - options.similarity)); * } else { * threshold = options.threshold || defaultColorThreshold; * } * if (options.region) { * return colorFinder.findColor(img, color, threshold, buildRegion(options.region, img)); * } else { * return colorFinder.findColor(img, color, threshold, null); * } * }; * function initIfNeeded() { * javaImages.initOpenCvIfNeeded(); * } * function parseColor(color) { * if (typeof (color) === 'string') { * color = colors.parseColor(color); * } * return color; * } * function buildRegion(region, img) { * if (region === undefined) { * region = []; * } * let x = region[0] === undefined ? 0 : region[0]; * let y = region[1] === undefined ? 0 : region[1]; * let width = region[2] === undefined ? img.getWidth() - x : region[2]; * let height = region[3] === undefined ? (img.getHeight() - y) : region[3]; * let r = new org.opencv.core.Rect(x, y, width, height); * if (x < 0 || y < 0 || x + width > img.width || y + height > img.height) { * throw new Error('out of region: region = [' + [x, y, width, height] + "], image.size = [' + [img.width, img.height] + ']"); * } * return r; * } */ findColor(img: ImageWrapper, color: Color$, options?: { similarity?: number, threshold?: number, region?: OmniRegion, }): OpenCV.Point | null; /** * @param img * @param color * @param [x=0] * @param [y=0] * @param [width=img.getWidth()-x] * @param [height=img.getHeight()-y] * @example * images.requestScreenCapture(false); * let capt = images.captureScreen(); * let point = images.findColorEquals(capt, "#FFFFFF"); * if (point) { * toastLog(point.x + ", " + point.y); * } * @example Source code summary (zh-CN: 源代码摘要) * images.findColorEquals = function (img, color, x, y, width, height) { * return findColor(img, color, { * region: [x, y, width, height], * threshold: 0 * }); * }; * @see findColor */ findColorEquals(img: ImageWrapper, color: Color$, x?: X, y?: Y, width?: Width, height?: Height): OpenCV.Point | null; /** * @param img * @param color * @param [x=0] * @param [y=0] * @param [width=img.getWidth()-x] * @param [height=img.getHeight()-y] * @param [threshold=4] * @example * images.requestScreenCapture(false); * let capt = images.captureScreen(); * let point = images.findColorInRegion(capt, "#FFFFFF"); * if (point) { * toastLog(point.x + ", " + point.y); * } * @example Source code summary (zh-CN: 源代码摘要) * images.findColorInRegion = function (img, color, x, y, width, height, threshold) { * return findColor(img, color, { * region: [x, y, width, height], * threshold: threshold * }); * }; * @see findColor */ findColorInRegion(img: ImageWrapper, color: Color$, x?: X, y?: Y, width?: Width, height?: Height, threshold?: number): OpenCV.Point | null; /** * @param img * @param template * @param [options={}] * @param [options.threshold=0.9] * @param [options.weakThreshold=0.6] * @param [options.level=-1] * @param [options.region] * @example * images.requestScreenCapture(false); * let capt = images.captureScreen(); * let img = images.read("/sdcard/capture.png"); * let templ = images.read("/sdcard/template.png"); * let point = images.findImage(img, templ); * if (point) { * console.log(point.x + ", " + point.y); * } * @example Source code summary (zh-CN: 源代码摘要) * let javaImages = runtime.getImages(); * images.findImage = function (img, template, options) { * initIfNeeded(); * options = options || {}; * let threshold = options.threshold || 0.9; * let maxLevel = -1; * if (typeof (options.level) === 'number') { * maxLevel = options.level; * } * let weakThreshold = options.weakThreshold || 0.6; * if (options.region) { * return javaImages.findImage(img, template, weakThreshold, threshold, buildRegion(options.region, img), maxLevel); * } else { * return javaImages.findImage(img, template, weakThreshold, threshold, null, maxLevel); * } * }; * function initIfNeeded() { * javaImages.initOpenCvIfNeeded(); * } * function buildRegion(region, img) { * if (region === undefined) { * region = []; * } * let x = region[0] === undefined ? 0 : region[0]; * let y = region[1] === undefined ? 0 : region[1]; * let width = region[2] === undefined ? img.getWidth() - x : region[2]; * let height = region[3] === undefined ? (img.getHeight() - y) : region[3]; * let r = new org.opencv.core.Rect(x, y, width, height); * if (x < 0 || y < 0 || x + width > img.width || y + height > img.height) { * throw new Error('out of region: region = [' + [x, y, width, height] + "], image.size = [' + [img.width, img.height] + ']"); * } * return r; * } * @see org.autojs.autojs.runtime.api.Images.findImage */ findImage(img: ImageWrapper, template: ImageWrapper, options?: { threshold?: number, weakThreshold?: number, level?: number, region?: OmniRegion, }): OpenCV.Point | null; /** * @param image * @param template * @param [x=0] * @param [y=0] * @param [width=img.getWidth()-x] * @param [height=img.getHeight()-y] * @param [threshold=4] * @example Source code summary (zh-CN: 源代码摘要) * images.findImageInRegion = function (img, template, x, y, width, height, threshold) { * return images.findImage(img, template, { * region: [x, y, width, height], * threshold: threshold * }); * }; * @see findImage */ findImageInRegion( image: ImageWrapper, template: ImageWrapper, x?: X, y?: Y, width?: Width, height?: Height, threshold?: number, ): OpenCV.Point | null; /** * @example * images.requestScreenCapture(false); * let capt = images.captureScreen(); * let point = images.findMultiColors( * capt, "#123456", * [[10, 20, "#FFFFFF"], [30, 40, "#000000"]], * {region: [0, 960, 1080, 960]} * ); * @example Source code summary (zh-CN: 源代码摘要) * const defaultColorThreshold = 4; * let javaImages = runtime.getImages(); * let colorFinder = javaImages.colorFinder; * images.findMultiColors = function (img, firstColor, paths, options) { * initIfNeeded(); * options = options || {}; * firstColor = parseColor(firstColor); * let list = java.lang.reflect.Array.newInstance(java.lang.Integer.TYPE, paths.length * 3); * for (let i = 0; i < paths.length; i++) { * let p = paths[i]; * list[i * 3] = p[0]; * list[i * 3 + 1] = p[1]; * list[i * 3 + 2] = parseColor(p[2]); * } * let region = options.region ? buildRegion(options.region, img) : null; * let threshold = options.threshold === undefined ? defaultColorThreshold : options.threshold; * return colorFinder.findMultiColors(img, firstColor, threshold, region, list); * }; * function initIfNeeded() { * javaImages.initOpenCvIfNeeded(); * } * function parseColor(color) { * if (typeof (color) === 'string') { * color = colors.parseColor(color); * } * return color; * } * function buildRegion(region, img) { * if (region === undefined) { * region = []; * } * let x = region[0] === undefined ? 0 : region[0]; * let y = region[1] === undefined ? 0 : region[1]; * let width = region[2] === undefined ? img.getWidth() - x : region[2]; * let height = region[3] === undefined ? (img.getHeight() - y) : region[3]; * let r = new org.opencv.core.Rect(x, y, width, height); * if (x < 0 || y < 0 || x + width > img.width || y + height > img.height) { * throw new Error('out of region: region = [' + [x, y, width, height] + "], image.size = [' + [img.width, img.height] + ']"); * } * return r; * } * @see org.autojs.autojs.core.image.ColorFinder.findMultiColors */ findMultiColors( img: ImageWrapper, firstColor: Color$, paths: [X, Y, Color$][], options?: { region?: OmniRegion; threshold?: number; }, ): OpenCV.Point | null; // noinspection SpellCheckingInspection /** * @example * // "data:\\w+/\\w+;base64," could be omitted * let base64 = "data:image/jpg;base64," + "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"; * let img = images.fromBase64(base64); * console.log(img.width + " × " + img.height); * @example Source code summary (zh-CN: 源代码摘要) * images.fromBase64 = function (base64) { * return javaImages.fromBase64(base64); * }; * @see org.autojs.autojs.runtime.api.Images.fromBase64 */ fromBase64(base64: string): ImageWrapper; /** * images.fromBytes = function (bytes) { * return javaImages.fromBytes(bytes); * }; * @see org.autojs.autojs.runtime.api.Images.fromBytes */ fromBytes(bytes: number[]): ImageWrapper; /** * Blurs an image using a Gaussian filter. * zh-CN: 高斯滤波: 使用高斯滤波器平滑图像 (高斯模糊) * @param src - input image; the image can have any number of channels, which are processed independently, * but the depth should be CV_8U, CV_16U, CV_16S, CV_32F or CV_64F. * zh-CN: 源图像: 通道数不限, 位深需为 CV_8U / CV_16U / CV_16S / CV_32F / CV_64F * @param ksize - Gaussian kernel size. * zh-CN: 高斯内核大小 (ksize[0] 和 ksize[1] 可以不相同但这值必须均为正奇数, 若两个值为 0, 他们的值将由 sigma 参数计算) * @param [sigmaX=0] - Gaussian kernel standard deviation in X direction. * zh-CN: 高斯核函数在X方向上的标准偏差 * @param [sigmaY=0] - Gaussian kernel standard deviation in Y direction; * if sigmaY is zero, it is set to be equal to sigmaX, * if both sigmas are zeros, they are computed from ksize.width and ksize.height, respectively * zh-CN: 高斯核函数在Y方向上的标准偏差 (若 sigmaY 是 0, 值将被设置为 sigmaX 值; 若 sigmaX 和 sigmaY 均为 0, 这两个值将由 ksize 计算而来) * @param [type="DEFAULT"] - pixel extrapolation method (without "BORDER_" prefix). * zh-CN: 推断图像外部像素的方法 * @example * images.requestScreenCapture(); * let dst = images.gaussianBlur(images.captureScreen(), [3, 3]); * @example Source code summary (zh-CN: 源代码摘要) * let javaImages = runtime.getImages(); * images.gaussianBlur = function (src, ksize, sigmaX, sigmaY, type) { * initIfNeeded(); * let mat = new Mat(); * ksize = newSize(ksize); * sigmaX = sigmaX === undefined ? 0 : sigmaX; * sigmaY = sigmaY === undefined ? 0 : sigmaY; * type = Core["BORDER_" + (type || "DEFAULT")]; * Imgproc.GaussianBlur(src.mat, mat, ksize, sigmaX, sigmaY, type); * return images.matToImage(mat); * }; * function initIfNeeded() { * javaImages.initOpenCvIfNeeded(); * } * function newSize(size) { * if (!Array.isArray(size)) { * size = [size, size]; * } * if (size.length === 1) { * size = [size[0], size[0]]; * } * return new Size(size[0], size[1]); * } * @see org.autojs.autojs.core.opencv.Mat * @see org.opencv.imgproc.Imgproc * @see org.opencv.core.Size * @see org.opencv.core.Core * @see https://docs.opencv.org/3.4/javadoc/org/opencv/imgproc/Imgproc.html#GaussianBlur(org.opencv.core.Mat,org.opencv.core.Mat,org.opencv.core.Size,double,double,int) * @see https://blog.csdn.net/keith_bb/article/details/54412493 */ gaussianBlur( src: ImageWrapper, ksize: Side | [Width, Height?], sigmaX?: number, sigmaY?: number, type?: Images.BorderTypes, ): ImageWrapper; /** * Applies the bilateral filter to an image * @param img - Source 8-bit or floating-point, 1-channel or 3-channel image * @param [d=0] - Diameter of each pixel neighborhood that is used during filtering. If it is non-positive, it is computed from sigmaSpace * @param [sigma_color=40] - Filter sigma in the color space. A larger value of the parameter means that farther colors within the pixel neighborhood (see sigmaSpace) will be mixed together, resulting in larger areas of semi-equal color * @param [sigma_space=20] - Filter sigma in the coordinate space. A larger value of the parameter means that farther pixels will influence each other as long as their colors are close enough (see sigmaColor ). When d>0, it specifies the neighborhood size regardless of sigmaSpace. Otherwise, d is proportional to sigmaSpace * @param [border_type='DEFAULT'] - border mode used to extrapolate pixels outside the image * @see https://docs.opencv.org/3.4.3/d4/d86/group__imgproc__filter.html#ga9d7064d478c95d60003cf839430737ed */ bilateralFilter( img: ImageWrapper, d?: number, sigma_color?: number, sigma_space?: number, border_type?: Images.BorderTypes, ): ImageWrapper; /** * Grayscale an image. * zh-CN: 灰度化 * @param src - input image: 8-bit unsigned, 16-bit unsigned (CV_16UC...), or single-precision floating-point. * zh-CN: 输入图像, 支持 8 位无符号整形, 16 位无符号整形或单精度浮点数 * @param dstCn - number of channels in the destination image; * if the parameter is 0, the number of the channels is derived automatically from src and code. * zh-CN: 目标图像的通道数, 该参数为 0 时, 目标图像根据源图像的通道数和具体操作自动决定 * @example * images.requestScreenCapture(false); * let dst = images.grayscale(images.captureScreen()); * @example Source code summary (zh-CN: 源代码摘要) * images.grayscale = function (src, dstCn) { * return images.cvtColor(src, "BGR2GRAY", dstCn); * }; * @see cvtColor */ grayscale(src: ImageWrapper, dstCn?: number): ImageWrapper; /** * Checks if array elements lie between the elements of two other arrays * @example * images.inRange(img, "#000000", "#222222"); * @example Source code summary (zh-CN: 源代码摘要) * let javaImages = runtime.getImages(); * images.inRange = function (img, lowerBound, upperBound) { * initIfNeeded(); * let lb = new Scalar( * colors.red(lowerBound), colors.green(lowerBound), * colors.blue(lowerBound), colors.alpha(lowerBound) * ); * let ub = new Scalar( * colors.red(upperBound), colors.green(upperBound), * colors.blue(upperBound), colors.alpha(lowerBound) * ); * let bi = new Mat(); * Core.inRange(img.mat, lb, ub, bi); * return images.matToImage(bi); * }; * function initIfNeeded() { * javaImages.initOpenCvIfNeeded(); * } * @see org.opencv.core.Core.inRange * @see org.autojs.autojs.core.opencv.Mat * @see org.opencv.core.Scalar */ inRange(img: ImageWrapper, lowerBound: Color$, upperBound: Color$): ImageWrapper; /** * @example * // set colors within the range of channel color value ±tolerance into #ffffff, * // and set colors out of range above to #000000 * // zh-CN: 每个通道的颜色值均为 0x88 ，加减偏差 16 之后的范围是 [0x78, 0x98] * // 因此此方法将 #787878 - #989898 范围颜色值变成 #ffffff 范围外变成 #000000 * images.interval(img, "#888888", 16); * @example Source code summary (zh-CN: 源代码摘要) * let javaImages = runtime.getImages(); * images.interval = function (img, color, tolerance) { * initIfNeeded(); * let lb = new Scalar(colors.red(color) - tolerance, colors.green(color) - tolerance, * colors.blue(color) - tolerance, colors.alpha(color)); * let ub = new Scalar(colors.red(color) + tolerance, colors.green(color) + tolerance, * colors.blue(color) + tolerance, colors.alpha(color)); * let bi = new Mat(); * Core.inRange(img.mat, lb, ub, bi); * return images.matToImage(bi); * }; * function initIfNeeded() { * javaImages.initOpenCvIfNeeded(); * } * @see org.opencv.core.Core.inRange * @see org.autojs.autojs.core.opencv.Mat * @see org.opencv.core.Scalar */ interval(img: ImageWrapper, color: Color$, tolerance: number): ImageWrapper; /** * @param img * @param template * @param [options={}] * @param [options.threshold=0.9] * @param [options.weakThreshold=0.6] * @param [options.level=-1] * @param [options.region] * @param [options.max=5] * @example * images.requestScreenCapture(false); * let capt = images.captureScreen(); * let img = images.read("/sdcard/capture.png"); * let templ = images.read("/sdcard/template.png"); * let matches = images.matchTemplate(img, templ, {threshold: 20, max: 11}); * matches.points.forEach(point => console.log(point.x + ", " + point.y)); * @example Source code summary (zh-CN: 源代码摘要) * let javaImages = runtime.getImages(); * images.matchTemplate = function (img, template, options) { * initIfNeeded(); * options = options || {}; * let threshold = options.threshold || 0.9; * let maxLevel = -1; * if (typeof (options.level) === 'number') { * maxLevel = options.level; * } * let max = options.max || 5; * let weakThreshold = options.weakThreshold || 0.6; * let result; * if (options.region) { * result = javaImages.matchTemplate(img, template, weakThreshold, threshold, buildRegion(options.region, img), maxLevel, max); * } else { * result = javaImages.matchTemplate(img, template, weakThreshold, threshold, null, maxLevel, max); * } * return new MatchingResult(result); * }; * function initIfNeeded() { * javaImages.initOpenCvIfNeeded(); * } * function buildRegion(region, img) { * if (region === undefined) { * region = []; * } * let x = region[0] === undefined ? 0 : region[0]; * let y = region[1] === undefined ? 0 : region[1]; * let width = region[2] === undefined ? img.getWidth() - x : region[2]; * let height = region[3] === undefined ? (img.getHeight() - y) : region[3]; * let r = new org.opencv.core.Rect(x, y, width, height); * if (x < 0 || y < 0 || x + width > img.width || y + height > img.height) { * throw new Error('out of region: region = [' + [x, y, width, height] + "], image.size = [' + [img.width, img.height] + ']"); * } * return r; * } * @see org.autojs.autojs.runtime.api.Images.matchTemplate */ matchTemplate(img: ImageWrapper, template: ImageWrapper, options?: { threshold?: number; weakThreshold?: number; level?: number; region?: OmniRegion; max?: number; }): Images.MatchingResult; /** * @example Source code summary (zh-CN: 源代码摘要) * let javaImages = runtime.getImages(); * images.matToImage = function (mat) { * initIfNeeded(); * return Image.ofMat(mat); * }; * function initIfNeeded() { * javaImages.initOpenCvIfNeeded(); * } */ matToImage(mat: org.autojs.autojs.core.opencv.Mat): ImageWrapper; /** * Blurs an image using the median filter. * zh-CN: 中值滤波: 使用中值滤波器平滑图像 * @param src - input 1-, 3-, or 4-channel image; * when ksize is 3 or 5, the image depth should be CV_8U, CV_16U, or CV_32F, for larger aperture sizes, it can only be CV_8U. * zh-CN: 输入图像: 图像为 1, 3, 4 通道图像; 当模板尺寸为 3 或 5 时, 图像深度只能为 CV_8U / CV_16U / CV_32F , 对于较大孔径尺寸的图片则只能是 CV_8U * @param ksize - aperture linear size; it must be odd and greater than 1, for example: 3, 5, 7 ... * zh-CN: 滤波模板尺寸: 需为大于 1 的奇数, 如 3, 5, 7... * @example * images.requestScreenCapture(false); * let dst = images.medianBlur(images.captureScreen(), 9); * @example Source code summary (zh-CN: 源代码摘要) * let javaImages = runtime.getImages(); * images.medianBlur = function (src, ksize) { * initIfNeeded(); * let mat = new Mat(); * Imgproc.medianBlur(src.mat, mat, ksize); * return images.matToImage(mat); * }; * function initIfNeeded() { * javaImages.initOpenCvIfNeeded(); * } * @see org.autojs.autojs.core.opencv.Mat * @see org.opencv.imgproc.Imgproc * @see https://docs.opencv.org/3.4/javadoc/org/opencv/imgproc/Imgproc.html#medianBlur(org.opencv.core.Mat,org.opencv.core.Mat,int) * @see https://blog.csdn.net/keith_bb/article/details/54426920 */ medianBlur(src: ImageWrapper, ksize: Side | [Side, Side]): ImageWrapper; /** * @example * console.log(images.readPixels("test.png").data.slice(0, 10)); * @example Source code summary (zh-CN: 源代码摘要) * images.readPixels = function (path) { * let img = images.read(path); * let bitmap = img.getBitmap(); * let w = bitmap.getWidth(); * let h = bitmap.getHeight(); * let pixels = util.java.array("int", w * h); * bitmap.getPixels(pixels, 0, w, 0, 0, w, h); * img.recycle(); * return {data: pixels, width: w, height: h}; * }; * @see read * @see ImageWrapper.getBitmap */ readPixels(path: string): { data: number[], width: Width, height: Height }; /** * @example * images.requestScreenCapture(); // auto orientation * @example * images.requestScreenCapture(true); // landscape orientation * @example * images.requestScreenCapture(false); // portrait orientation * @example Source code summary (zh-CN: 源代码摘要) * const ResultAdapter = require("result-adapter"); * let javaImages = runtime.getImages(); * images.requestScreenCapture = function (landscape) { * let ScreenCapturer = org.autojs.autojs.core.image.capture.ScreenCapturer; * let orientation = ScreenCapturer.ORIENTATION_AUTO; * if (landscape === true) { * orientation = ScreenCapturer.ORIENTATION_LANDSCAPE; * } * if (landscape === false) { * orientation = ScreenCapturer.ORIENTATION_PORTRAIT; * } * return ResultAdapter.wait(javaImages.requestScreenCapture(orientation)); * }; * @see runtime.getImages * @see org.autojs.autojs.runtime.api.Images.requestScreenCapture * @see org.autojs.autojs.core.image.capture.ScreenCapturer */ requestScreenCapture(landscape?: boolean): boolean; /** * Resizes an image. * zh-CN: 缩放图像 (按尺寸) * @param src - input image. * zh-CN: 源图像 * @param dsize - output image size (Side|[Width,Height]). * zh-CN: 输出图像尺寸 * @param [interpolation="LINEAR"] - interpolation method (without "INTER_" prefix). * zh-CN: 插值方法 (参数不包含 “INTER_” 前缀) * @example * images.requestScreenCapture(false); * let dst = images.resize(images.captureScreen(), [720, 1280]); * @example Source code summary (zh-CN: 源代码摘要) * let javaImages = runtime.getImages(); * images.resize = function (src, size, interpolation) { * initIfNeeded(); * let mat = new Mat(); * interpolation = Imgproc["INTER_" + (interpolation || "LINEAR")]; * Imgproc.resize(src.mat, mat, newSize(size), 0, 0, interpolation); * return images.matToImage(mat); * }; * function initIfNeeded() { * javaImages.initOpenCvIfNeeded(); * } * function newSize(size) { * if (!Array.isArray(size)) { * size = [size, size]; * } * if (size.length === 1) { * size = [size[0], size[0]]; * } * return new Size(size[0], size[1]); * } * @see org.autojs.autojs.core.opencv.Mat * @see org.opencv.imgproc.Imgproc * @see org.opencv.core.Size * @see https://docs.opencv.org/3.4/javadoc/org/opencv/imgproc/Imgproc.html#resize(org.opencv.core.Mat,org.opencv.core.Mat,org.opencv.core.Size,double,double,int) */ resize(src: ImageWrapper, dsize: Side | [Width, Height?], interpolation?: Images.InterpolationFlags): ImageWrapper; /** * @example * images.requestScreenCapture(false); * let dst = images.rotate(images.captureScreen(), 90); // 90° anticlockwise * @example Source code summary (zh-CN: 源代码摘要) * let javaImages = runtime.getImages(); * images.rotate = function (img, degree, ctx, cty) { * initIfNeeded(); * if (ctx === undefined) {ctx = img.width / 2} * if (cty === undefined) {cty = img.height / 2} * return javaImages.rotate(img, ctx, cty, degree); * }; * function initIfNeeded() { * javaImages.initOpenCvIfNeeded(); * } * @see org.autojs.autojs.runtime.api.Images.rotate */ rotate(img: ImageWrapper, degree: number, ctx?: number, cty?: number): ImageWrapper; /** * @example * images.save(images.captureScreen(), files.cwd(), "png", 90); * images.save(images.captureScreen(), files.cwd(), undefined, 90); // same as above * images.save(images.captureScreen(), files.cwd(), "", 90); // same as above * @example Source code summary (zh-CN: 源代码摘要) * let javaImages = runtime.getImages(); * images.save = function (img, path, format, quality) { * format = format || "png"; * quality = quality === undefined ? 100 : quality; * return javaImages.save(img, path, format, quality); * }; * @param img * @param path * @param [format="png"] * @param [quality=100] * @see runtime.getImages * @see org.autojs.autojs.runtime.api.Images.save */ save(img: ImageWrapper, path: string, format?: Images.Format, quality?: number): boolean; /** @see save */ saveImage(img: ImageWrapper, path: string, format?: Images.Format, quality?: number): boolean; /** * Resizes an image. * zh-CN: 缩放图像 (按比例) * @param src - input image. * zh-CN: 源图像 * @param fx - scale factor along the horizontal axis. * zh-CN: 水平宽度放缩倍数 * @param fy - scale factor along the vertical axis. * zh-CN: 垂直高度放缩倍数 * @param [interpolation="LINEAR"] - interpolation method (without "INTER_" prefix). * zh-CN: 插值方法 (参数不包含 “INTER_” 前缀) * @example * images.requestScreenCapture(false); * let dst = images.scale(images.captureScreen(), 0.5, 0.5); * @example Source code summary (zh-CN: 源代码摘要) * let javaImages = runtime.getImages(); * images.scale = function (src, fx, fy, interpolation) { * initIfNeeded(); * let mat = new Mat(); * interpolation = Imgproc["INTER_" + (interpolation || "LINEAR")]; * Imgproc.resize(src.mat, mat, newSize([0, 0]), fx, fy, interpolation); * return images.matToImage(mat); * }; * function initIfNeeded() { * javaImages.initOpenCvIfNeeded(); * } * function newSize(size) { * if (!Array.isArray(size)) { * size = [size, size]; * } * if (size.length === 1) { * size = [size[0], size[0]]; * } * return new Size(size[0], size[1]); * } * @see org.autojs.autojs.core.opencv.Mat * @see org.opencv.imgproc.Imgproc * @see org.opencv.core.Size */ scale(src: ImageWrapper, fx: number, fy: number, interpolation?: Images.InterpolationFlags): ImageWrapper; /** * Applies a fixed-level threshold to each array element. * zh-CN: 阈值化 * @example * images.requestScreenCapture(false); * let dst = images.threshold(images.captureScreen(), 100, 255, "BINARY"); * @example Source code summary (zh-CN: 源代码摘要) * let javaImages = runtime.getImages(); * images.threshold = function (img, threshold, maxVal, type) { * initIfNeeded(); * let mat = new Mat(); * type = type || "BINARY"; * type = Imgproc["THRESH_" + type]; * Imgproc.threshold(img.mat, mat, threshold, maxVal, type); * return images.matToImage(mat); * }; * function initIfNeeded() { * javaImages.initOpenCvIfNeeded(); * } * @param src - input array (multiple-channel, 8-bit or 32-bit floating point) * zh-CN: 输入图像, 多通道 8位或32位浮点类型 * @param threshold - threshold value * zh-CN: 阈值设定值 * @param maxVal - maximum value to use with the THRESH_BINARY and THRESH_BINARY_INV thresholding types * zh-CN: 使用THRESH_BINARY及THRESH_BINARY_INV阈值的最大值 * @param [type="BINARY"] - thresholding type * zh-CN: 阈值类型 * @see org.opencv.imgproc.Imgproc * @see https://docs.opencv.org/3.4/javadoc/org/opencv/imgproc/Imgproc.html#threshold(org.opencv.core.Mat,org.opencv.core.Mat,double,double,int) */ threshold(src: ImageWrapper, threshold: number, maxVal: number, type?: Images.ThresholdTypes): ImageWrapper; /** * @param img * @param [format="png"] * @param [quality=100] * @example * images.requestScreenCapture(false); * console.log(images.toBase64(images.capt()).slice(0, 20)); * @example Source code summary (zh-CN: 源代码摘要) * let javaImages = runtime.getImages(); * images.toBase64 = function (img, format, quality) { * format = format || "png"; * quality = quality === undefined ? 100 : quality; * return javaImages.toBase64(img, format, quality); * }; * @see org.autojs.autojs.runtime.api.Images.toBase64 */ toBase64(img: ImageWrapper, format?: Images.Format, quality?: number): string; /** * @param img * @param [format="png"] * @param [quality=100] * @example * images.requestScreenCapture(false); * console.log(images.toBytes(images.capt()).slice(0, 20)); * @example Source code summary (zh-CN: 源代码摘要) * let javaImages = runtime.getImages(); * images.toBytes = function (img, format, quality) { * format = format || "png"; * quality = quality === undefined ? 100 : quality; * return javaImages.toBytes(img, format, quality); * }; * @see org.autojs.autojs.runtime.api.Images.toBytes */ toBytes(img: ImageWrapper, format?: Images.Format, quality?: number): number[]; /** * Check if all images have been recycled. */ isRecycled(...images: ImageWrapper[]): boolean; /** * Recycle all images. */ recycle(...images: ImageWrapper[]): boolean; compress(img: ImageWrapper, compressLevel: number): ImageWrapper; getSize(img: ImageWrapper | android.graphics.Bitmap | org.opencv.core.Mat | string): org.opencv.core.Size; getWidth(img: ImageWrapper | android.graphics.Bitmap | org.opencv.core.Mat | string): number; getHeight(img: ImageWrapper | android.graphics.Bitmap | org.opencv.core.Mat | string): number; buildRegion(img: ImageWrapper, region: OmniRegion): org.opencv.core.Rect | null; } } declare namespace Images { type Format = 'png' | 'jpeg' | 'jpg' | 'webp'; type Wrapper = ImageWrapper; type SizeWidth = Percentage$; type SizeHeight = Percentage$; type Size = SizeWidth | [SizeWidth] | [SizeWidth, SizeHeight]; type TemplateMatch = org.autojs.autojs.core.image.TemplateMatching.Match; type MatchingResultSortStrategy = 'left-top' | 'left-right' | 'left-bottom' | 'top-left' | 'top-right' | 'top-bottom' | 'right-left' | 'right-top' | 'right-bottom' | 'bottom-left' | 'bottom-top' | 'bottom-right'; type InterpolationFlags = 'NEAREST' | 'LINEAR' | 'CUBIC' | 'AREA' | 'LANCZOS4' | 'LINEAR_EXACT' | 'MAX'; type ThresholdTypes = 'BINARY' | 'BINARY_INV' | 'TRUNC' | 'TOZERO' | 'TOZERO_INV' | 'MASK' | 'OTSU' | 'TRIANGLE'; type AdaptiveThresholdTypes = 'MEAN_C' | 'GAUSSIAN_C'; type BorderTypes = 'CONSTANT' | 'REPLICATE' | 'REFLECT' | 'WRAP' | 'REFLECT_101' | 'TRANSPARENT' | 'REFLECT101' | 'DEFAULT' | 'ISOLATED'; class MatchingResult { /** * @example Source code summary (zh-CN: 源代码摘要) * function MatchingResult(list) { * if (Array.isArray(list)) { * this.matches = list; * } else { * this.matches = runtime.bridges.bridges.toArray(list); * } * this.__defineGetter__("points", () => { * if (typeof (this.__points__) == 'undefined') { * this.__points__ = this.matches.map(m => m.point); * } * return this.__points__; * }); * } */ constructor(list: Images.TemplateMatch); /** * @example Source code summary (zh-CN: 源代码摘要) * function MatchingResult(list) { * if (Array.isArray(list)) { * this.matches = list; * } else { * this.matches = runtime.bridges.bridges.toArray(list); * } * this.__defineGetter__("points", () => { * if (typeof (this.__points__) == 'undefined') { * this.__points__ = this.matches.map(m => m.point); * } * return this.__points__; * }); * } */ constructor(list: Images.TemplateMatch[]); /** * @example * let result = images.matchTemplate(img, template, {max: 100}); * result.matches.forEach(match => log("point: " + match.point + ", similarity: " + match.similarity)); * @example Source code summary (zh-CN: 源代码摘要) * function MatchingResult(list) { * if (Array.isArray(list)) { * this.matches = list; * } else { * this.matches = runtime.bridges.bridges.toArray(list); * } * this.__defineGetter__("points", () => { * if (typeof (this.__points__) == 'undefined') { * this.__points__ = this.matches.map(m => m.point); * } * return this.__points__; * }); * } */ matches: Images.TemplateMatch[]; /** * @example Source code summary (zh-CN: 源代码摘要) * function MatchingResult(list) { * if (Array.isArray(list)) { * this.matches = list; * } else { * this.matches = runtime.bridges.bridges.toArray(list); * } * this.__defineGetter__("points", () => { * if (typeof (this.__points__) == 'undefined') { * this.__points__ = this.matches.map(m => m.point); * } * return this.__points__; * }); * } */ get points(): OpenCV.Points; /** * @example Source code summary (zh-CN: 源代码摘要) * MatchingResult.prototype.first = function () { * if (this.matches.length === 0) { * return null; * } * return this.matches[0]; * }; * @see matches */ first(): Images.TemplateMatch; /** * @example Source code summary (zh-CN: 源代码摘要) * MatchingResult.prototype.last = function () { * if (this.matches.length === 0) { * return null; * } * return this.matches[this.matches.length - 1]; * }; * @see matches */ last(): Images.TemplateMatch; /** * @example Source code summary (zh-CN: 源代码摘要) * MatchingResult.prototype.findMax = function (cmp) { * if (this.matches.length === 0) { * return null; * } * let target = this.matches[0]; * this.matches.forEach(m => { * if (cmp(target, m) > 0) { * target = m; * } * }); * return target; * }; * @see matches */ findMax(compareFn?: (a: Images.TemplateMatch, b: Images.TemplateMatch) => number): Images.TemplateMatch; /** * @example Source code summary (zh-CN: 源代码摘要) * let comparators = { * "left": (l, r) => l.point.x - r.point.x, * "top": (l, r) => l.point.y - r.point.y, * "right": (l, r) => r.point.x - l.point.x, * "bottom": (l, r) => r.point.y - l.point.y * }; * MatchingResult.prototype.leftmost = function () { * return this.findMax(comparators.left); * }; * @see findMax */ leftmost(): Images.TemplateMatch; /** * @example Source code summary (zh-CN: 源代码摘要) * let comparators = { * "left": (l, r) => l.point.x - r.point.x, * "top": (l, r) => l.point.y - r.point.y, * "right": (l, r) => r.point.x - l.point.x, * "bottom": (l, r) => r.point.y - l.point.y * }; * MatchingResult.prototype.topmost = function () { * return this.findMax(comparators.top); * }; * @see findMax */ topmost(): Images.TemplateMatch; /** * @example Source code summary (zh-CN: 源代码摘要) * let comparators = { * "left": (l, r) => l.point.x - r.point.x, * "top": (l, r) => l.point.y - r.point.y, * "right": (l, r) => r.point.x - l.point.x, * "bottom": (l, r) => r.point.y - l.point.y * }; * MatchingResult.prototype.rightmost = function () { * return this.findMax(comparators.right); * }; * @see findMax */ rightmost(): Images.TemplateMatch; /** * @example Source code summary (zh-CN: 源代码摘要) * let comparators = { * "left": (l, r) => l.point.x - r.point.x, * "top": (l, r) => l.point.y - r.point.y, * "right": (l, r) => r.point.x - l.point.x, * "bottom": (l, r) => r.point.y - l.point.y * }; * MatchingResult.prototype.bottommost = function () { * return this.findMax(comparators.bottom); * }; * @see findMax */ bottommost(): Images.TemplateMatch; /** * @example Source code summary (zh-CN: 源代码摘要) * MatchingResult.prototype.worst = function () { * return this.findMax((l, r) => l.similarity - r.similarity); * }; * @see findMax */ worst(): Images.TemplateMatch; /** * @example Source code summary (zh-CN: 源代码摘要) * MatchingResult.prototype.best = function () { * return this.findMax((l, r) => r.similarity - l.similarity); * }; * @see findMax */ best(): Images.TemplateMatch; /** * @example * let result = images.matchTemplate(img, template, {max: 100}); * result.sortBy("top-right"); * @example Source code summary (zh-CN: 源代码摘要) * MatchingResult.prototype.sortBy = function (cmp) { * let comparatorFn = null; * if (typeof (cmp) == 'string') { * cmp.split('-').forEach(direction => { * let buildInFn = comparators[direction]; * if (!buildInFn) { * throw new Error("unknown direction '" + direction + "' in '" + cmp + "'"); * } * (function (fn) { * if (comparatorFn == null) { * comparatorFn = fn; * } else { * comparatorFn = (function (comparatorFn, fn) { * return function (l, r) { * let cmpValue = comparatorFn(l, r); * if (cmpValue === 0) { * return fn(l, r); * } * return cmpValue; * } * })(comparatorFn, fn); * } * })(buildInFn); * }); * } else { * comparatorFn = cmp; * } * let clone = this.matches.slice(); * clone.sort(comparatorFn); * return new MatchingResult(clone); * }; */ sortBy(compareFn?: ((a: Images.TemplateMatch, b: Images.TemplateMatch) => number) | Images.MatchingResultSortStrategy): this; } interface BitmapFactoryOptions { inBitmap?: android.graphics.Bitmap, inDensity?: number, inDither?: boolean, inInputShareable?: boolean, inJustDecodeBounds?: boolean, inMutable?: boolean, inPreferQualityOverSpeed?: boolean, inPreferredColorSpace?: android.graphics.ColorSpace, inPreferredConfig?: android.graphics.Bitmap.Config, inPremultiplied?: boolean, inPurgeable?: boolean, inSampleSize?: number, inScaled?: boolean, inScreenDensity?: number, inTargetDensity?: number, inTempStorage?: number[], mCancel?: boolean, outColorSpace?: android.graphics.ColorSpace, outConfig?: android.graphics.Bitmap.Config, outHeight?: number, outMimeType?: string, outWidth?: number, requestCancelDecode?: () => void, } namespace Circles { type Result = { x: number, y: number, radius: number }[]; type Options = { region?: OmniRegion; dp?: number; minDst?: number; param1?: number; param2?: number; minRadius?: number; maxRadius?: number; }; } } declare namespace OpenCV { type Rect = org.opencv.core.Rect; type Point = org.opencv.core.Point; type Points = org.opencv.core.Point[]; } /** * @see images.requestScreenCapture */ declare function requestScreenCapture(landscape?: boolean): boolean; /** * @see images.captureScreen */ declare function captureScreen(path?: string): ImageWrapper; /** * @param img * @param template * @param [options={}] * @param [options.threshold=0.9] * @param [options.weakThreshold=0.6] * @param [options.level=-1] * @param [options.region] * @see images.findImage */ declare function findImage(img: ImageWrapper, template: ImageWrapper, options?: { threshold?: number; weakThreshold?: number; level?: number; region?: OmniRegion; }): OpenCV.Point; /** * @param image * @param template * @param [x=0] * @param [y=0] * @param [width=img.getWidth()-x] * @param [height=img.getHeight()-y] * @param [threshold=4] * @see images.findImageInRegion */ declare function findImageInRegion(image: ImageWrapper, template: ImageWrapper, x?: X, y?: Y, width?: Width, height?: Height, threshold?: number): OpenCV.Point; /** * @see images.findColor */ declare function findColor(img: ImageWrapper, color: Color$, options?: { similarity?: number; threshold?: number; region?: OmniRegion; }): OpenCV.Point; /** * @param img * @param color * @param [x=0] * @param [y=0] * @param [width=img.getWidth()-x] * @param [height=img.getHeight()-y] * @see images.findColorEquals */ declare function findColorEquals(img: ImageWrapper, color: Color$, x?: X, y?: Y, width?: Width, height?: Height): OpenCV.Point; /** * @param img * @param color * @param [x=0] * @param [y=0] * @param [width=img.getWidth()-x] * @param [height=img.getHeight()-y] * @param [threshold=4] * @see images.findColorInRegion */ declare function findColorInRegion(img: ImageWrapper, color: Color$, x?: X, y?: Y, width?: Width, height?: Height, threshold?: number): OpenCV.Point; /** * @see images.findMultiColors */ declare function findMultiColors(img: ImageWrapper, firstColor: Color$, paths: [X, Y, Color$][], options?: { region?: OmniRegion; threshold?: number; }): OpenCV.Point; declare class ImageWrapper extends org.autojs.autojs.core.image.ImageWrapper { /** * @see ImageWrapper.getMat */ public mat: org.autojs.autojs.core.opencv.Mat; /** * @see ImageWrapper.getBitmap */ public bitmap: android.graphics.Bitmap; /** * @see ImageWrapper.getWidth */ public width: number; /** * @see ImageWrapper.getHeight */ public height: number; public oneShot(): ImageWrapper; public setOneShot(b: boolean): ImageWrapper; /** * @example Source code summary (zh-CN: 源代码摘要) * private int mWidth; * private int mHeight; * private Bitmap mBitmap; * protected ImageWrapper(Bitmap bitmap) { * mBitmap = bitmap; * mWidth = bitmap.getWidth(); * mHeight = bitmap.getHeight(); * } * public static ImageWrapper ofBitmap(Bitmap bitmap) { * if (bitmap == null) { * return null; * } * return new ImageWrapper(bitmap); * } * @see android.graphics.Bitmap */ public static ofBitmap(bitmap: android.graphics.Bitmap): ImageWrapper; public static ofImage(image: android.media.Image): ImageWrapper; public static ofMat(mat: org.autojs.autojs.core.opencv.Mat): ImageWrapper; }