private void UploadImage_Btn_Click(object sender, RoutedEventArgs e)
{
// Create OpenFileDialog
SWF.OpenFileDialog dlg = new SWF.OpenFileDialog();
// Set filter for file extension and default file extension
dlg.DefaultExt = ".png";
dlg.Filter = "Image Files|*.jpg;*.png;*.bmp;*.jpeg;*.gif;";
// Get the selected file name and display in a TextBox
if (dlg.ShowDialog() == SWF.DialogResult.OK)
{
Image_PB.Image = SD.Image.FromFile(dlg.FileName);
ImageBytes = File.ReadAllBytes(dlg.FileName);
ObjectDected();
//填写
var result = ImageClassifyHelper.AdvancedGeneralDemo(ImageBytes);
var info = JsonConvert.DeserializeObject <ImageClassifyResult <CarItem> >(result.ToString());
List <string> items = new List <string>();
info.result.ForEach(item => { items.Add(String.Format("{0}\n{1}\n", item.keyword, item?.baike_info?.description)); });
SetRichTextBoxValue(relationInfo_Rtb, items);
}
}
private void ObjectDected()
{
String with_face = "0";
if (DectectFace_CB.IsChecked ?? false)
{
with_face = "1";
}
var options = new Dictionary <string, object>()
{
{ "with_face", with_face }
};
var imageResult = ImageClassifyHelper.ObjectDetectDemo(ImageBytes, options);
location = JsonConvert.DeserializeObject <LocationInfo>(imageResult["result"].ToString());
ResetLocation(location, Image_PB.Image.Width, Image_PB.Image.Height);
}
private void feature_Btn_Click(object sender, RoutedEventArgs e)
{
if (sender is Button btn)
{
List <string> items = new List <string>();
switch (btn.DataContext)
{
case FeatureType.菜品识别:
var dishResult = ImageClassifyHelper.DishDetectDemo(ImageBytes);
var dishDectectResult = JsonConvert.DeserializeObject <ImageClassifyResult <DishItem> >(dishResult.ToString());
dishDectectResult.result.ForEach(item => { items.Add(String.Format("菜名：{0}\n 卡路里：{1}\n 置信度：{2}", item.name, item.calorie, item.probability)); });
break;
case FeatureType.车型识别:
var carResult = ImageClassifyHelper.CarDetectDemo(ImageBytes);
var carDectectResult = JsonConvert.DeserializeObject <ImageClassifyResult <CarItem> >(carResult.ToString());
carDectectResult.result.ForEach(item => { items.Add(String.Format("车型：{0}\n 年份：{1}\n 置信度：{2}", item.name, item.year, item.score)); });
break;
case FeatureType.商标识别:
var logoResult = ImageClassifyHelper.LogoDetectDemo(ImageBytes);
var logoDectectResult = JsonConvert.DeserializeObject <ImageClassifyResult <LogoItem> >(logoResult.ToString());
logoDectectResult.result.ForEach(item => { items.Add(String.Format("商标：{0}\n 置信度：{1}", item.name, item.probability)); });
break;
case FeatureType.动物识别:
var animalResult = ImageClassifyHelper.AnimalDetectDemo(ImageBytes);
var animalDectectResult = JsonConvert.DeserializeObject <ImageClassifyResult <CarItem> >(animalResult.ToString());
animalDectectResult.result.ForEach(item => { items.Add(String.Format("动物：{0}\n 置信度：{1}", item.name, item.score)); });
break;
case FeatureType.物识别:
var plantResult = ImageClassifyHelper.PlantDetectDemo(ImageBytes);
var plantDectectResult = JsonConvert.DeserializeObject <ImageClassifyResult <CarItem> >(plantResult.ToString());
plantDectectResult.result.ForEach(item => { items.Add(String.Format("植物：{0}\n 置信度：{1}\n", item.name, item.score)); });
break;
}
SetRichTextBoxValue(detectResult_Rtb, items);
}
}
