diff --git a/.gitmodules b/.gitmodules
index 81a9427..c35b84a 100644
--- a/.gitmodules
+++ b/.gitmodules
@@ -1,5 +1,8 @@
 [submodule "learn/yolov5"]
 		path = learn/yolov5
 			url = http://192.168.0.51:3000/wangchunlin/yolov5-fire.git
-				branch = use
-	depth = 1
+				branch = use2
+[submodule "learn/Darknet2Pytorch2Onnx"]
+	path = learn/Darknet2Pytorch2Onnx
+	url = http://192.168.0.51:3000/wangchunlin/Darknet2Pytorch2Onnx.git
+	branch = use
diff --git a/learn/Darknet2Pytorch2Onnx b/learn/Darknet2Pytorch2Onnx
new file mode 160000
index 0000000..1d4cf92
--- /dev/null
+++ b/learn/Darknet2Pytorch2Onnx
@@ -0,0 +1 @@
+Subproject commit 1d4cf9249f723166ceaea3573becbba4a7726916
diff --git a/learn/templates/home.html b/learn/templates/home.html
index a1024c8..ab6c3e5 100644
--- a/learn/templates/home.html
+++ b/learn/templates/home.html
@@ -6,7 +6,17 @@
     <meta charset="UTF-8">
     <title>WildFire</title>
     <script src="../static/layui/layui.js"></script>
-    <script src="http://apps.bdimg.com/libs/jquery/1.11.1/jquery.min.js"></script>
+    <!-- 新 Bootstrap4 核心 CSS 文件 -->
+<link rel="stylesheet" href="https://cdn.staticfile.org/twitter-bootstrap/4.3.1/css/bootstrap.min.css">
+ 
+<!-- jQuery文件。务必在bootstrap.min.js 之前引入 -->
+<script src="https://cdn.staticfile.org/jquery/3.2.1/jquery.min.js"></script>
+ 
+<!-- bootstrap.bundle.min.js 用于弹窗、提示、下拉菜单，包含了 popper.min.js -->
+<script src="https://cdn.staticfile.org/popper.js/1.15.0/umd/popper.min.js"></script>
+ 
+<!-- 最新的 Bootstrap4 核心 JavaScript 文件 -->
+<script src="https://cdn.staticfile.org/twitter-bootstrap/4.3.1/js/bootstrap.min.js"></script>
 </head>
 <body>
 {% csrf_token %} {#如果不加这个，程序会报错#}
@@ -19,25 +29,59 @@
 <b><font size="4">获取剪切板在无https情况下失败，直接Ctrl+V即可</b>
   <p id="mode select">
 <h1>模型选择:
-  <select id="model", style="width: 300px; font-size:30px;">
-      <option value="1">小模型</option>
-      <option value="2">大模型</option>
-      <option value="3">泛模型</option>
-  </select>
-  <select id="class", style="width: 600px; font-size:30px;">
-    <option value="1">火焰与烟雾</option>
-    <option value="2">一般物体80类</option>
-    <option value="3">烟火与塔吊</option>
-    <option value="4">外破（ljp4500张）四类v5v3</option>
-    <option value="5">外破（ljp4500张）四类v5v7</option>
-    <option value="6">外破（ljp4500张）四类v5v7m</option>
-    <option value="7">绝缘子缺陷（ljp2000张）两类v5v7</option>
-</select>
+  <select id="class" style="width: 200px; font-size:30px;"></select>
+  <select id="model" style="width: 600px; font-size:30px;"></select>
 </h1>
   </p>
 <p id="img"></p>
 
 <script>
+  $(function () {
+      $("#class").change(function () {
+          $("#model").empty();//清空回调列表;
+         var val = this.value;
+          console.log("选择的检测类别：", val);
+         $.each(dic_class, function (i, n) { //each()方法为每个匹配元素规定要运行的函数;
+              if (Object.keys(dic_class)[val-1] == i) {
+                  $.each(dic_class[i], function (j,m) {
+                     var text = document.createTextNode(m);//createTextNode()方法创建文本节点;
+                     var op = document.createElement("option");//创建class元素;
+                     op.value = j+1
+                     $(op).append(text);
+                     $("#model").append(op);
+                 })
+             }
+         })
+     })
+  })
+</script>
+
+<script>
+  var dic_class={};//创建一个字典;
+  dic_class["外破"]=["外破（ljp4500张）四类v5v3", "外破（ljp4500张）四类v5v7", "外破（ljp4500张）四类v5v7m", "烟火与塔吊"]
+  dic_class["山火"]=["小模型", "大模型", "泛模型"]
+  dic_class["绝缘子"]=["绝缘子缺陷（ljp2000张）两类v5v7"]
+  dic_class["一般物体80类"]=["v5sv7"]
+
+$(document).ready(function(){
+          $("#model").empty();//清空回调列表;
+         var dic_class_count = 1;
+          for(var key in dic_class){
+            var text = document.createTextNode(key);//createTextNode()方法创建文本节点;
+            var op = document.createElement("option");//创建class元素;
+            op.value = dic_class_count
+            $(op).append(text);
+            $("#class").append(op);
+            dic_class_count++;
+          }
+          $.each(dic_class[Object.keys(dic_class)[0]], function (j,m) {
+            var text = document.createTextNode(m);//createTextNode()方法创建文本节点;
+            var op = document.createElement("option");//创建class元素;
+            op.value = j+1
+            $(op).append(text);
+            $("#model").append(op);
+        })
+});
 document.addEventListener("paste", function () {
     if (event.clipboardData || event.originalEvent) {
         var clipboardData = (event.clipboardData || window.clipboardData);
@@ -46,11 +90,13 @@ 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);});
     }
 });
 </script>
 <script>
+
 layui.use('upload', function(){
   var upload = layui.upload;
   $ = layui.$   //注意要定义$,该符号不是jQuery中的$
diff --git a/learn/views.py b/learn/views.py
index 153d69f..0675c06 100644
--- a/learn/views.py
+++ b/learn/views.py
@@ -56,48 +56,7 @@ def upload(request):
         for i in file.chunks():
             f.write(i)
         f.close()
-        result = adb_shell("ImageDetect/build/ImageDetect {}".format(img_path))
-        if result[0]==0:
-            cast = result[1].split("||")[0]
-            da = result[1].split("||")[1]
-            satu = result[1].split("||")[2]
-            CON = result[1].split("||")[3]
-            ASM = result[1].split("||")[4]
-            ENT = result[1].split("||")[5]
-            MEAN = result[1].split("||")[6]
-            sb = result[1].split("||")[7]
-            lap = result[1].split("||")[8]
-            dev = result[1].split("||")[9]
-        print(cast, da, satu)
-        mesg = "颜色分布(0-1合理):{}&nbsp;&nbsp;&nbsp;分布方差(负数偏暗):{}&nbsp;&nbsp;&nbsp;色彩饱和度(零为补光):{}<br/>对比度:{}&nbsp;&nbsp;&nbsp;角度方向二阶矩:{}&nbsp;&nbsp;&nbsp;熵:{}&nbsp;&nbsp;&nbsp;平均值:{}&nbsp;&nbsp;&nbsp;Sobel:{}&nbsp;&nbsp;&nbsp;Lap:{}&nbsp;&nbsp;&nbsp;dev:{}".format(cast, da, satu, CON, ASM, ENT, MEAN,sb,lap,dev)
-        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})
-            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})
-            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})
-        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})
-        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})
-        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})
-        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})
-        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})
-        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 inference(m_class, m_model, curPath, img_path_res, img_path)
 
 
 def dlurl(request):
@@ -121,6 +80,8 @@ 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)
+        '''
         result = adb_shell("ImageDetect/build/ImageDetect {}".format(img_path))
         if result[0]==0:
             cast = result[1].split("||")[0]
@@ -163,8 +124,61 @@ def dlurl(request):
         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})
+        '''
 
 
 
 def home(request):
     return render(request, 'home.html')
+
+def inference(m_class, m_model, curPath, img_path_res, img_path):
+    result = adb_shell("ImageDetect/build/ImageDetect {}".format(img_path))
+    if result[0]==0:
+        cast = result[1].split("||")[0]
+        da = result[1].split("||")[1]
+        satu = result[1].split("||")[2]
+        CON = result[1].split("||")[3]
+        ASM = result[1].split("||")[4]
+        ENT = result[1].split("||")[5]
+        MEAN = result[1].split("||")[6]
+        sb = result[1].split("||")[7]
+        lap = result[1].split("||")[8]
+        dev = result[1].split("||")[9]
+    print(cast, da, satu)
+    mesg = "颜色分布(0-1合理):{}&nbsp;&nbsp;&nbsp;分布方差(负数偏暗):{}&nbsp;&nbsp;&nbsp;色彩饱和度(零为补光):{}<br/>对比度:{}&nbsp;&nbsp;&nbsp;角度方向二阶矩:{}&nbsp;&nbsp;&nbsp;熵:{}&nbsp;&nbsp;&nbsp;平均值:{}&nbsp;&nbsp;&nbsp;Sobel:{}&nbsp;&nbsp;&nbsp;Lap:{}&nbsp;&nbsp;&nbsp;dev:{}".format(cast, da, satu, CON, ASM, ENT, MEAN,sb,lap,dev)
+    
+    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})
+        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})   
+        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})  
+        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})
+        
+    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})
+        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})
+        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}) 
+        
+    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})
+        
+    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})
+            
\ No newline at end of file
