OpenCV图像处理与识别AIWROK软件十大功能及其实现方法

YYPOST群发软件 · 发表于 9 小时前

OpenCV图像处理与识别AIWROK软件十大功能及其实现方法..

//第一个，opencv.checkColorsEx_精简OCR识别
function safeOCRProcess() {
// 第一步：先验证目标区域是否存在
if (!opencv.checkColorsEx('多点比色.cv')) {
printl("基础区域验证未通过");
return;
}
// 第二步：执行OCR并验证返回类型
var ocrResult = opencv.OCREx('多点比色.cv');
// 双重类型验证（应对可能返回boolean的情况）
if (!ocrResult || typeof ocrResult !== 'object' || typeof ocrResult.findIncludeText !== 'function') {
printl("OCR结果异常");
return;
}
// 第三步：安全处理识别结果
try {
var resultText = ocrResult.findIncludeText('蜂');
if (resultText) {
printl("识别成功：" + resultText);
// 这里可以添加点击等后续操作
} else {
printl("文本未找到");
}
} catch (e) {
printl("结果处理异常：" + e.message);
}
}
// 执行处理流程
safeOCRProcess();
//第二个，opencv.checkColorsEx_精简区域找图
var seek = opencv.findImagesEx('区域找图.cv');
if (seek) {
seek[0].click(); //点击
} else {
printl("未找到了");
}
var seek = opencv.findImagesEx('区域找图.cv');
if (seek) {
var place = seek[0].getRealRect();
var x = place.getCenterX();
var y = place.getCenterY();
printl(x+","+y)
} else {
printl("未找到了");
}
//第三个，opencv.checkColorsEx_精简多点找色
var seek = opencv.checkColorsEx('多点比色.cv');
if (seek) {
printl("找到了");
} else {
printl("未找到了");
}
if (opencv.checkColorsEx('多点比色.cv')) {
printl("找到了");
} else {
printl("未找到了");
}
//第四个，opencv.checkColorsEx_精简多点比色
var seek = opencv.checkColorsEx('多点比色.cv');
if (seek) {
printl("找到了");
} else {
printl("未找到了");
}
if (opencv.checkColorsEx('多点比色.cv')) {
printl("找到了");
} else {
printl("未找到了");
}
//第五个，opencv.checkColors_OCR识别
var mat=screen.screenShot(720,1280,100).getMat();
var seek = opencv.OCR(mat, '小猪猪.ocr', 0.95,0);
if (seek) {
printl(ocr1.getAllString());
} else {
printl("未找到了");
}
var mat=screen.screenShot(720,1280,100).getMat();
var seek = opencv.OCR(mat, '小猪猪.ocr', 0.95,0);
if (seek) {
printl(seek.findIncludeText('小猪猪'))
} else {
printl("未找到了");
}
//第六个，opencv.checkColors_多点比色
var mat=screen.screenShot(720,1280,100).getMat();
var seek = opencv.checkColors(mat, ['351,452,#553E38', '368,449,#816D78'], 2, 4, 0.95);
if (seek) {
printl("找到了");
} else {
printl("未找到了");
}
var mat=screen.screenShot(720,1280,100).getMat();
if (opencv.checkColors(mat, ['351,452,#553E38', '368,449,#816D78'], 2, 4, 0.95)) {
printl("找到了");
} else {
printl("未找到了");
}
//第七个，opencv.findMultiColor_多点找色
var mat=screen.screenShot(720,1280,100).getMat();
var seek = opencv.findMultiColor(mat,'607,425,#264878',['601,413,#1E4276','597,428,#1E4276','591,429,#F8FBFF'],2,5,[0.80040,0.30889,0.87549,0.35667],0.95);
if (seek) {
seek[0].click(); //点击
} else {
printl("未找到了");
}
var mat=screen.screenShot(720,1280,100).getMat();
var seek = opencv.findMultiColor(mat,'607,425,#264878',['601,413,#1E4276','597,428,#1E4276','591,429,#F8FBFF'],2,5,[0.80040,0.30889,0.87549,0.35667],0.95);
if (seek) {
var place = seek[0].getRealRect();
var x = place.getCenterX();
var y = place.getCenterY();
printl(x+","+y)
} else {
printl("未找到了");
}
//第八个，opencv.templateMatch_区域找图
var mat=screen.screenShot(720,1280,100).getMat();
var seek = opencv.templateMatch(mat, ["图片1","图片2"],0.9, [0.03360,0.14222,0.08893,0.17667],true);
if (seek) {
seek[0].click(); //点击
} else {
printl("未找到了");
}
var mat=screen.screenShot(720,1280,100).getMat();
var seek = opencv.templateMatch(mat, ["图片1","图片2"],0.9, [0.03360,0.14222,0.08893,0.17667],true);
if (seek) {
var place = seek[0].getRealRect();
var x = place.getCenterX();
var y = place.getCenterY();
printl(x+","+y)
} else {
printl("未找到了");
}
//第九个，opencv.HSV颜色变换
// 截图并获取Mat对象
var mat = screen.screenShot(720, 1280, 100).getMat();
// 使用HSV方法转换
var hsvMat = opencv.HSV(mat, 0, 0, 0);
printl("HSV 转换完成！");
printl(hsvMat);
//第十个，opencv.bitmapToMat(bmp)bitmap图转mat
importPackage(org.opencv.core);
importPackage(org.opencv.imgproc);
importPackage(org.opencv.android);
importClass(android.graphics.Bitmap);
function screenshotAndBinarize(minThreshold, maxThreshold) {
// 获取屏幕截图
var bitmap = screen.screenShot(640, 960, 100).getBitmap();
// 将 Bitmap 转换为 Mat
var mat = new Mat();
Utils.bitmapToMat(bitmap, mat);
// 创建一个用于存储二值化结果的 Mat
var binaryMat = new Mat();
// 应用阈值处理
Imgproc.threshold(mat, binaryMat, minThreshold, maxThreshold, Imgproc.THRESH_BINARY);
printl(binaryMat);
// 将二值化的 Mat 转换回 Bitmap
var binaryBitmap = Bitmap.createBitmap(binaryMat.cols(), binaryMat.rows(), Bitmap.Config.ARGB_8888);
Utils.matToBitmap(binaryMat, binaryBitmap);
return binaryBitmap;
}
// 调用处理函数
var resultBitmap = screenshotAndBinarize(50, 150);
printl(resultBitmap);