mmdeploy/demo/csharp/ocr_recognition/Program.cs

69 lines
2.0 KiB
C#

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;
}
}
}
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();
}
}
}