物联网浏览器 (IoTBrowser)- 整合机器学习 yolo 框架实现车牌识别

public AjaxResponse CarNo(string inArgs) {    var ar = new Infrastructure.Web.AjaxResponse();    var obj = Newtonsoft.Json.JsonConvert.DeserializeObject<dynamic>(inArgs);    var path = string.Empty;    var beginTime = DateTime.Now;    if (obj.path != null)    {        path = obj.path;    }    var image = System.Drawing.Image.FromFile(path);    var predictions = yolo.Predict(image);     if (predictions.Count < 1) {        ar.Error("没有检测到车牌");        return ar;    }    foreach (var prediction in predictions) // iterate predictions to draw results    {        double score = Math.Round(prediction.Score, 2);        var labelRect = prediction.Rectangle;        var twoLayers = (labelRect.Height / labelRect.Width) > 0.5;        //定义截取矩形        System.Drawing.Rectangle cropArea = new System.Drawing.Rectangle((int)labelRect.X < 0 ? 0 : (int)labelRect.X, (int)labelRect.Y < 0 ? 0 : (int)labelRect.Y, (int)labelRect.Width, (int)labelRect.Height);        //定义Bitmap对象        System.Drawing.Bitmap bmpImage = new System.Drawing.Bitmap(image);        //进行裁剪        System.Drawing.Bitmap bmpCrop = bmpImage.Clone(cropArea, bmpImage.PixelFormat);        //保存成新文件        //bmpCrop.Save(Path.Combine(path, (fileName + "_" + dtNow + num + "_clone.png")), ImageFormat.Png);         var yoloOcrpredictions = yoloOcr.Predict(bmpCrop);        if (yoloOcrpredictions.Length > 0)        {            ar.Data = (new {carNo = yoloOcrpredictions[0] ,color = yoloOcrpredictions[1] });                           }    }    return ar;}

var filePath ="";var ar = await dds.dynamic.api.exectuce({    pluginName: "CarDetectApi",    actionName: "CarNo",    actionData: JSON.stringify({        path: filePath    })})if (ar.Success && ar.Data) {    var data = ar.Data;    self.resultInfo = data.carNo + "--" + data.color} else {    self.resultInfo = ar.Message;}