using System; using System.Collections.Generic; using OpenCvSharp; using MMDeploy; namespace ocr_detection { class Program { static void CvMatToMat(OpenCvSharp.Mat[] cvMats, out MMDeploy.Mat[] mats) { mats = new MMDeploy.Mat[cvMats.Length]; unsafe { for (int i = 0; i < cvMats.Length; i++) { mats[i].Data = cvMats[i].DataPointer; mats[i].Height = cvMats[i].Height; mats[i].Width = cvMats[i].Width; mats[i].Channel = cvMats[i].Dims; mats[i].Format = PixelFormat.BGR; mats[i].Type = DataType.Int8; mats[i].Device = null; } } } static void CvWaitKey() { Cv2.WaitKey(); } static void Main(string[] args) { if (args.Length != 3) { Console.WriteLine("usage:\n ocr_detection deviceName modelPath imagePath\n"); Environment.Exit(1); } string deviceName = args[0]; string modelPath = args[1]; string imagePath = args[2]; // 1. create handle MMDeploy.TextDetector handle = new MMDeploy.TextDetector(modelPath, deviceName, 0); // 2. prepare input OpenCvSharp.Mat[] imgs = new OpenCvSharp.Mat[1] { Cv2.ImRead(imagePath, ImreadModes.Color) }; CvMatToMat(imgs, out var mats); // 3. process List output = handle.Apply(mats); // 4. show result foreach (var detect in output[0].Results) { for (int i = 0; i < 4; i++) { int sp = i; int ep = (i + 1) % 4; Cv2.Line(imgs[0], new Point((int)detect.BBox[sp].X, (int)detect.BBox[sp].Y), new Point((int)detect.BBox[ep].X, (int)detect.BBox[ep].Y), new Scalar(0, 255, 0)); } } Cv2.NamedWindow("ocr-det", WindowFlags.GuiExpanded); Cv2.ImShow("ocr-det", imgs[0]); CvWaitKey(); handle.Close(); } } }