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learn/templates/home.html

@@ -58,7 +58,7 @@
 
 <script>
   var dic_class={};//创建一个字典;
-  dic_class["外破"]=["外破（ljp4500张）四类v5v3", "外破（ljp4500张）四类v5v7", "外破（ljp4500张）四类v5v7m", "烟火与塔吊"]
+  dic_class["外破"]=["外破（ljp4500张）四类v5v3", "外破（ljp4500张）四类v5v7", "外破（ljp4500张）四类v5v7m", "烟火与塔吊", "外破（ljp4500张）四类v5v7m6", "yolov3-tiny四类(正式使用)", "yolov3-tiny两类(正式使用)"]
   dic_class["山火"]=["小模型", "大模型", "泛模型"]
   dic_class["绝缘子"]=["绝缘子缺陷（ljp2000张）两类v5v7"]
   dic_class["一般物体80类"]=["v5sv7"]
@@ -90,8 +90,8 @@ document.addEventListener("paste", function () {
         // 字典 dict
         var model = $('#model option:selected').val();
         var model_class = $('#class option:selected').val();
-        console.log("检测类别与使用模型：", model_class, model)
-        $.getJSON('/dlurl/', {'url':val, 'model':model, 'class':model_class},function(res){ShowResult(res);});
+        console.log("检测类别与使用模型：", Object.keys(dic_class)[model_class-1], ',',dic_class[Object.keys(dic_class)[model_class-1]][model-1])
+        $.getJSON('/dlurl/', {'url':val, 'model':model, 'class':model_class,'model_name':dic_class[Object.keys(dic_class)[model_class-1]][model-1],'class_name':Object.keys(dic_class)[model_class-1]},function(res){ShowResult(res);});
     }
 });
 </script>
@@ -116,6 +116,17 @@ layui.use('upload', function(){
           var model_class = $('#class option:selected').val();
           return model_class;
         }
+        , 'model_name':function(){
+          var model_class = $('#class option:selected').val();
+          var model = $('#model option:selected').val();
+          var model_name=dic_class[Object.keys(dic_class)[model_class-1]][model-1];
+          return model_name;
+        }
+        , 'class_name':function(){
+          var model_class = $('#class option:selected').val();
+          var class_name=Object.keys(dic_class)[model_class-1];
+          return class_name;
+        }
       }
       ,done: function(res){
       ShowResult(res);
@@ -157,7 +168,7 @@ layui.use('upload', function(){
             };  
             }
         $("#img").prepend(i);
-        $("#img").prepend('<br>' +'<br>' + '<b>'+'<font size="4">'+"检测图片："+res.code+'</font> '+"</b>"+'<br>');
+        $("#img").prepend('<br>' +'<br>' + '<b>'+'<font size="4">'+"检测信息："+res.code+'</font> '+"</b>"+'<br>');
         }
     function AutoResizeImage(maxWidth,maxHeight,objImg){
     var img = new Image();

learn/views.py

@@ -5,6 +5,7 @@ import os
 import subprocess
 from datetime import datetime
 import learn.yolov5.detect as DL
+import learn.Darknet2Pytorch2Onnx.hy_runonnx as RONNX
 from pathlib import PosixPath
 import requests, os, json
 import cv2
@@ -45,6 +46,10 @@ def upload(request):
         file = request.FILES.get('file') #获取前端上传的文件
         m_model=request.POST.get('model')
         m_class=request.POST.get('class')
+        model_name = request.POST.get("model_name")
+        class_name = request.POST.get("class_name")
+        print(request.POST["model_name"])
+        print(request.POST["class_name"])
         fix = datetime.now().strftime('%Y%m%d%H%M%S%f')+'1' #给文件加前缀防止文件名重复
 		#以下用绝对路径存储文件，之前我用相对路径一直写不对
         curPath = os.path.abspath( os.path.dirname( __file__ ) )
@@ -56,7 +61,7 @@ def upload(request):
         for i in file.chunks():
             f.write(i)
         f.close()
-        return inference(m_class, m_model, curPath, img_path_res, img_path)
+        return inference(m_class, m_model, curPath, img_path_res, img_path, model_name, class_name)
 
 
 def dlurl(request):
@@ -64,6 +69,10 @@ def dlurl(request):
         url = request.GET["url"] #获取前端上传的文件
         m_model=request.GET["model"]
         m_class=request.GET["class"]
+        model_name = request.GET.get("model_name")
+        class_name = request.GET.get("class_name")
+        print(request.GET["model_name"])
+        print(request.GET["class_name"])
         print("m_model:",m_model)
         print("url:",url)
         name = url.split(r'/')[-1]
@@ -80,7 +89,7 @@ def dlurl(request):
             f.close
         #返回给前端的图片路径用相对路径，前端用绝对路径反而加载不了图片
         img_path_res = '/static/detected/'+fix+name
-        return inference(m_class, m_model, curPath, img_path_res, img_path)
+        return inference(m_class, m_model, curPath, img_path_res, img_path, model_name, class_name)
         '''
         result = adb_shell("ImageDetect/build/ImageDetect {}".format(img_path))
         if result[0]==0:
@@ -99,31 +108,31 @@ def dlurl(request):
         if(int(m_class)==1):
             if(int(m_model)==1): #小模型
                 RR = DL.run(weights=(curPath+"/yolov5/v3s.pt"), source=img_path, project=(curPath+"/static/detected"))
-                return JsonResponse({'img_name':img_path_res,'code':"【烟火 小模型】"+RR+' <br/> '+mesg, 'flag': True})
+                return JsonResponse({'img_name':img_path_res,'code':"【烟火 小模型】"+' <br/> '+RR+' <br/> '+mesg, 'flag': True})
             if(int(m_model)==2): #大模型
                 RR = DL.run(weights=(curPath+"/yolov5/v6m6.pt"), source=img_path, imgsz=(1280, 1280), project=(curPath+"/static/detected"))
-                return JsonResponse({'img_name':img_path_res,'code':"【烟火 大模型】"+RR+' <br/> '+mesg, 'flag': True})
+                return JsonResponse({'img_name':img_path_res,'code':"【烟火 大模型】"+' <br/> '+RR+' <br/> '+mesg, 'flag': True})
             if(int(m_model)==3): #泛模型
                 RR = DL.run(weights=(curPath+"/yolov5/best.pt"), source=img_path, project=(curPath+"/static/detected"))
-                return JsonResponse({'img_name':img_path_res,'code':"【烟火 泛模型】"+RR+' <br/> '+mesg, 'flag': True})
+                return JsonResponse({'img_name':img_path_res,'code':"【烟火 泛模型】"+' <br/> '+RR+' <br/> '+mesg, 'flag': True})
         if(int(m_class)==2):
             RR = DL.run(weights=(curPath+"/yolov5/yolov5s.pt"), source=img_path, project=(curPath+"/static/detected"))
-            return JsonResponse({'img_name':img_path_res,'code':"【一般物体检测】"+RR+' <br/> '+mesg, 'flag': True})
+            return JsonResponse({'img_name':img_path_res,'code':"【一般物体检测】"+' <br/> '+RR+' <br/> '+mesg, 'flag': True})
         if(int(m_class)==3):
             RR = DL.run(weights=(curPath+"/yolov5/fire_smoke_towercrane.pt"), source=img_path, project=(curPath+"/static/detected"))
-            return JsonResponse({'img_name':img_path_res,'code':"【烟火+塔吊】"+RR+' <br/> '+mesg, 'flag': True})
+            return JsonResponse({'img_name':img_path_res,'code':"【烟火+塔吊】"+' <br/> '+RR+' <br/> '+mesg, 'flag': True})
         if(int(m_class)==4):
             RR = DL.run(weights=(curPath+"/yolov5/vehicle_4class_ljp_v3.0.pt"), source=img_path, project=(curPath+"/static/detected"))
-            return JsonResponse({'img_name':img_path_res,'code':"【外破四类】"+RR+' <br/> '+mesg, 'flag': True})
+            return JsonResponse({'img_name':img_path_res,'code':"【外破四类】"+' <br/> '+RR+' <br/> '+mesg, 'flag': True})
         if(int(m_class)==5):
             RR = DL.run(weights=(curPath+"/yolov5/vehicle_4class_ljp_v7.0.pt"), source=img_path, project=(curPath+"/static/detected"))
-            return JsonResponse({'img_name':img_path_res,'code':"【外破四类】"+RR+' <br/> '+mesg, 'flag': True})
+            return JsonResponse({'img_name':img_path_res,'code':"【外破四类】"+' <br/> '+RR+' <br/> '+mesg, 'flag': True})
         if(int(m_class)==6):
             RR = DL.run(weights=(curPath+"/yolov5/vehicle_4class_ljp_v7.0m.pt"), source=img_path, project=(curPath+"/static/detected"))
-            return JsonResponse({'img_name':img_path_res,'code':"【外破四类】"+RR+' <br/> '+mesg, 'flag': True})
+            return JsonResponse({'img_name':img_path_res,'code':"【外破四类】"+' <br/> '+RR+' <br/> '+mesg, 'flag': True})
         if(int(m_class)==7):
             RR = DL.run(weights=(curPath+"/yolov5/birdpecked_unnormal_version1.pt"), source=img_path, project=(curPath+"/static/detected"))
-            return JsonResponse({'img_name':img_path_res,'code':"【绝缘子两类】"+RR+' <br/> '+mesg, 'flag': True})
+            return JsonResponse({'img_name':img_path_res,'code':"【绝缘子两类】"+' <br/> '+RR+' <br/> '+mesg, 'flag': True})
         '''
 
 
@@ -131,7 +140,7 @@ def dlurl(request):
 def home(request):
     return render(request, 'home.html')
 
-def inference(m_class, m_model, curPath, img_path_res, img_path):
+def inference(m_class, m_model, curPath, img_path_res, img_path, model_name, class_name):
     result = adb_shell("ImageDetect/build/ImageDetect {}".format(img_path))
     if result[0]==0:
         cast = result[1].split("||")[0]
@@ -150,35 +159,44 @@ def inference(m_class, m_model, curPath, img_path_res, img_path):
     if(int(m_class)==1): #外破
         if(int(m_model)==1):
             RR = DL.run(weights=(curPath+"/yolov5/vehicle_4class_ljp_v3.0.pt"), source=img_path, project=(curPath+"/static/detected"))
-            return JsonResponse({'img_name':img_path_res,'code':"【外破四类】"+RR+' <br/> '+mesg, 'flag': True})
+            return JsonResponse({'img_name':img_path_res,'code':class_name+":"+model_name+",模型: "+"vehicle_4class_ljp_v3.0.pt"+' <br/> '+RR+' <br/> '+mesg, 'flag': True})
         if(int(m_model)==2):
             RR = DL.run(weights=(curPath+"/yolov5/vehicle_4class_ljp_v7.0.pt"), source=img_path, project=(curPath+"/static/detected"))
-            return JsonResponse({'img_name':img_path_res,'code':"【外破四类】"+RR+' <br/> '+mesg, 'flag': True})   
+            return JsonResponse({'img_name':img_path_res,'code':class_name+":"+model_name+",模型: "+"vehicle_4class_ljp_v7.0.pt"+' <br/> '+RR+' <br/> '+mesg, 'flag': True})  
         if(int(m_model)==3): 
             RR = DL.run(weights=(curPath+"/yolov5/vehicle_4class_ljp_v7.0m.pt"), source=img_path, project=(curPath+"/static/detected"))
-            return JsonResponse({'img_name':img_path_res,'code':"【外破四类】"+RR+' <br/> '+mesg, 'flag': True})  
+            return JsonResponse({'img_name':img_path_res,'code':class_name+":"+model_name+",模型: "+"vehicle_4class_ljp_v7.0m.pt"+' <br/> '+RR+' <br/> '+mesg, 'flag': True}) 
         if(int(m_model)==4): 
             RR = DL.run(weights=(curPath+"/yolov5/fire_smoke_towercrane.pt"), source=img_path, project=(curPath+"/static/detected"))
-            return JsonResponse({'img_name':img_path_res,'code':"【烟火+塔吊】"+RR+' <br/> '+mesg, 'flag': True})
+            return JsonResponse({'img_name':img_path_res,'code':class_name+":"+model_name+",模型: "+"fire_smoke_towercrane.pt"+' <br/> '+RR+' <br/> '+mesg, 'flag': True})
+        if(int(m_model)==5): 
+            RR = DL.run(weights=(curPath+"/yolov5/vehicle_4class_ljp_v7.0m6.pt"), source=img_path, project=(curPath+"/static/detected"),imgsz=(1280,1280))
+            return JsonResponse({'img_name':img_path_res,'code':class_name+":"+model_name+",模型: "+"vehicle_4class_ljp_v7.0m6.pt"+' <br/> '+RR+' <br/> '+mesg, 'flag': True})
+        if(int(m_model)==6): 
+            RR=RONNX.main(curPath+"/Darknet2Pytorch2Onnx/hy_vehicle_4class.onnx", curPath+"/Darknet2Pytorch2Onnx/hy_vehicle_4class.names", img_path, (curPath+"/static/detected"))
+            return JsonResponse({'img_name':img_path_res,'code':class_name+":"+model_name+",模型: "+"hy_vehicle_4class.onnx"+' <br/> '+RR+' <br/> '+mesg, 'flag': True})
+        if(int(m_model)==7): 
+            RR=RONNX.main(curPath+"/Darknet2Pytorch2Onnx/hy_vehicle_2class.onnx", curPath+"/Darknet2Pytorch2Onnx/hy_vehicle_2class.names", img_path, (curPath+"/static/detected"))
+            return JsonResponse({'img_name':img_path_res,'code':class_name+":"+model_name+",模型: "+"hy_vehicle_2class.onnx"+' <br/> '+RR+' <br/> '+mesg, 'flag': True})
         
     if(int(m_class)==2): #山火
         if(int(m_model)==1): # 小
             RR = DL.run(weights=(curPath+"/yolov5/v3s.pt"), source=img_path, project=(curPath+"/static/detected"))
-            return JsonResponse({'img_name':img_path_res,'code':"【烟火 小模型】"+RR+' <br/> '+mesg, 'flag': True})
+            return JsonResponse({'img_name':img_path_res,'code':class_name+":"+model_name+",模型: "+"v3s.pt"+' <br/> '+RR+' <br/> '+mesg, 'flag': True})
         if(int(m_model)==2): # 大
             RR = DL.run(weights=(curPath+"/yolov5/v6m6.pt"), source=img_path, imgsz=(1280, 1280), project=(curPath+"/static/detected"))
-            return JsonResponse({'img_name':img_path_res,'code':"【烟火 大模型】"+RR+' <br/> '+mesg, 'flag': True})
+            return JsonResponse({'img_name':img_path_res,'code':class_name+":"+model_name+",模型: "+"v6m6.pt"+' <br/> '+RR+' <br/> '+mesg, 'flag': True})
         if(int(m_model)==3): # 范模型
             RR = DL.run(weights=(curPath+"/yolov5/best.pt"), source=img_path, project=(curPath+"/static/detected"))
-            return JsonResponse({'img_name':img_path_res,'code':"【烟火 泛模型】"+RR+' <br/> '+mesg, 'flag': True}) 
+            return JsonResponse({'img_name':img_path_res,'code':class_name+":"+model_name+",模型: "+"best.pt"+' <br/> '+RR+' <br/> '+mesg, 'flag': True})
         
     if(int(m_class)==3): # 绝缘子
         if(int(m_model)==1):
             RR = DL.run(weights=(curPath+"/yolov5/birdpecked_unnormal_version1.pt"), source=img_path, project=(curPath+"/static/detected"))
-            return JsonResponse({'img_name':img_path_res,'code':"【绝缘子两类】"+RR+' <br/> '+mesg, 'flag': True})
+            return JsonResponse({'img_name':img_path_res,'code':class_name+":"+model_name+",模型: "+"birdpecked_unnormal_version1.pt"+' <br/> '+RR+' <br/> '+mesg, 'flag': True})
         
     if(int(m_class)==4): # 一般物体coco
         if(int(m_model)==1): #yolov5s
             RR = DL.run(weights=(curPath+"/yolov5/yolov5s.pt"), source=img_path, project=(curPath+"/static/detected"))
-            return JsonResponse({'img_name':img_path_res,'code':"【一般物体检测】"+RR+' <br/> '+mesg, 'flag': True})
+            return JsonResponse({'img_name':img_path_res,'code':class_name+":"+model_name+",模型: "+"yolov5s.pt"+' <br/> '+RR+' <br/> '+mesg, 'flag': True})