之前在网上找到个 python 写的二维码摆渡程序，识别率颇高，但是 python 的 UI 界面实在难画，自己对 python 也不是很熟悉。 最近用 C#重写了一份，可以实现一些特定功能，但是发现无论是 ZXing.net 还是 Zbar ，识别效率和成功率对比之前 python 用的 CV2 打开摄像头+pyzbar 识别二维码的组合差很多很多。 python 下我是采用固定 10ms 读取摄像头识别一次，单次 6 图，效率大约是 60/s 。 c#下我是采用绑定 timer 的形式，20ms 触发一次从摄像头获取 bitmap ，送进 decoder 解码，效率只有 1/S ，甚至经常识别不出。 各位大佬帮忙看看。 C#核心代码

 private void decodeCurrentFrame()

    {
        if (graphics == null)
        {
            return;
        }
        //复制图像
        this.graphics.CopyFromScreen(Screen.PrimaryScreen.Bounds.X, Screen.PrimaryScreen.Bounds.Y, 0, 0, new Size(width, height), CopyPixelOperation.SourceCopy);
        this.pictureBox1.Image = this.bitmapSrc;
        Stopwatch sw = new Stopwatch();
        sw.Start();
        Bitmap bitmap = (Bitmap)this.bitmapSrc.Clone();
        //解码图片
        Result[] results = reader.DecodeMultiple(bitmap);
        //读取识别出来的二维码
        if (results != null)
        {
            foreach (Result result in results)
            {
                {
                    Console.WriteLine("成功识别");
                    string content = result.ToString();
                    if (content.Length <= 20)
                    {
                        return;
                    }
                    string prefix = content.Substring(0, 16); //获取文件前缀
                    string currentIndex = prefix.Substring(0, 8); //获取当前切片索引编号
                    string total = prefix.Substring(8); //获取总索引数
                    if (content.Contains("|"))
                    {
                        int prefixIndex = content.LastIndexOf("|");
                        int qrCurrentIndex = content.IndexOf("|");
                        currentIndex = content.Substring(0, qrCurrentIndex);
                        string raw = content.Substring(prefixIndex + 1);
                        content = "0000000000000000" + raw;
                        Console.WriteLine("旧版数据" + raw + "索引编号：" + currentIndex);
                    }
                    initResultMap(total);
                    dealData(currentIndex, content.Substring(16));
                    checkResultMap();
                }
            }
        }
        //统计数据
        sw.Stop();
        TimeSpan ts = sw.Elapsed;
        string costed = ts.TotalMilliseconds + "ms";
        labelTickCost.Text = costed;
    }
    

pyhon 核心代码

   def decodeDisplay(img):

        global number
        barcodes = pyzbar.decode(img)
        for barcode in barcodes:
            barcodeData = barcode.data.decode()
            try:
                i = int(barcodeData[:8])
            except ValueError:
                return img
            try:
                max = int(barcodeData[8:16])
            except ValueError:
                return img
            ll = ''

            if not os.path.exists("temp/result" + str(i) + ".txt"):
                barcodeData = barcodeData[16:]
                with open("temp/result" + str(i) + ".txt", "w+") as f:
                    f.write(barcodeData)
                    number = number + 1
                    global sat
                if number == max:
                    filecount = len(os.listdir('temp/result'))
                    if number != filecount:
                        number = filecount
                        continue
                    j = 1
                    while j <= number:
                        with open("temp/result" + str(j) + ".txt", "r+") as f:
                            txt = f.read()
                        ll = ll + txt
                        j = j + 1
                    global starttime
                    ent = time.time()
                    theLB.insert(END, "识别结束")
                    theLB.see(END)
                    with open("result/b64.txt", "w") as f:
                        f.write(ll)
                    temp = base64.b64decode(ll)
                    with open("result/result.txt", "wb") as f:
                        f.write(temp)
                    if tkinter.messagebox.askyesno(title='识别成功', message='另存为'):
                        old_path = tk.filedialog.askdirectory()
                        shutil.copy("result/result.txt", old_path)
                    theLB.insert(END, "识别成功")
                    del_file()
        return img