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); } }