using System; using System.Collections.Generic; using OpenCvSharp; using MMDeploy; namespace ocr_recognition { 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_recognition deviceName modelPath imagePath\n"); Environment.Exit(1); } string deviceName = args[0]; string modelPath = args[1]; string imagePath = args[2]; // 1. create handle TextRecognizer handle = new TextRecognizer(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<TextRecognizerOutput> output = handle.Apply(mats); //// 4. show result foreach (var box in output[0].Results) { string text = System.Text.Encoding.UTF8.GetString(box.Text); Cv2.PutText(imgs[0], text, new Point(20, 20), HersheyFonts.HersheySimplex, 0.7, new Scalar(0, 255, 0), 1); } Cv2.NamedWindow("ocr-reg", WindowFlags.GuiExpanded); Cv2.ImShow("ocr-reg", imgs[0]); CvWaitKey(); handle.Close(); } } }