可以提供目标检测部分的interface代码吗 about paddlexcsharp HOT 2 CLOSED

    // 目标物种类，需根据实际情况修改！
    //string[] category = { "bocai", "changqiezi", "hongxiancai", "huluobo", "xihongshi", "xilanhua"};
    string[] category = { "meter" };

    // 定义CreatePaddlexModel接口
    [DllImport("paddlex_inference.dll", EntryPoint = "CreatePaddlexModel", CharSet = CharSet.Ansi)]
    static extern IntPtr CreatePaddlexModel(ref int modelType,
                                            string modelPath,
                                            bool useGPU,
                                            bool useTrt,
                                            bool useMkl,
                                            int mklThreadNum,
                                            int gpuID,
                                            string key,
                                            bool useIrOptim);

    // 定义检测接口
    [DllImport("paddlex_inference.dll", EntryPoint = "PaddlexDetPredict", CharSet = CharSet.Ansi, CallingConvention = CallingConvention.Cdecl)]
    static extern bool PaddlexDetPredict(IntPtr model, byte[] image, int height, int width, int channels, int max_box, float[] result, bool visualize);
    #endregion

    public static byte[] GetbyteData(Bitmap bmp)
    {
        BitmapData bmpData = null;
        bmpData = bmp.LockBits(new Rectangle(0, 0, bmp.Width, bmp.Height), ImageLockMode.ReadOnly, bmp.PixelFormat);
        int numbytes = bmpData.Stride * bmpData.Height;
        byte[] byteData = new byte[numbytes];
        IntPtr ptr = bmpData.Scan0;

        Marshal.Copy(ptr, byteData, 0, numbytes);

        return byteData;
    }

    public Bitmap Inference(Bitmap bmp)
    {
        isInference = true;
        model = CreatePaddlexModel(ref modelType, modelPath, useGPU, useTrt, useMkl, mklThreadNum, gpuID, key, useIrOptim);

        Bitmap bmpNew = bmp.Clone(new Rectangle(0, 0, bmp.Width, bmp.Height), bmp.PixelFormat);
        Bitmap resultShow = null;
        Mat img = BitmapConverter.ToMat(bmpNew);

        int channel = Image.GetPixelFormatSize(bmp.PixelFormat) / 8;
        byte[] source = GetbyteData(bmp);

        int max_box = 10;
        float[] result = new float[max_box * 6 + 1];
        bool res = PaddlexDetPredict(model, source, bmp.Height, bmp.Width, channel, max_box, result, visualize);
        if (res)
        {
            Scalar color = new Scalar(255, 0, 0);
            for (int i = 0; i < result[0]; i++)
            {
                Rect rect = new Rect((int)result[6 * i + 3], (int)result[6 * i + 4], (int)result[6 * i + 5], (int)result[6 * i + 6]);
                Cv2.Rectangle(img, rect, color, 2, LineTypes.AntiAlias);
                string text = category[(int)result[6 * i + 1]] + ": " + result[6 * i + 2].ToString("f2");
                Cv2.PutText(img, text, new OpenCvSharp.Point((int)result[6 * i + 3], (int)result[6 * i + 4] + 25), HersheyFonts.HersheyPlain, 2, Scalar.White);
            }
        }

        resultShow = new Bitmap(img.Cols, img.Rows, (int)img.Step(), PixelFormat.Format24bppRgb, img.Data);
        System.GC.Collect();
        return resultShow;
    }
}