Update app.py

app.py

@@ -48,22 +48,48 @@ def normalize_2d(matrix):
 def detect(imagepath):
 
     pix=model.predict(imagepath, confidence=40, overlap=30)
-    pix=np.array(pix)
+    pix=pix.json()
     img=cv2.imread(imagepath)
 
-    for a,b,c,d,_,_,_,_ in pix.items():
+    x1,x2,y1,y2=[],[],[],[]
+    for i in pix.keys():
+        if i=="predictions":
+            for j in pix["predictions"]:
+                for a,b in j.items():
+                    if a=="x":
+                        x1.append(b)
+                    if a=="y":
+                        y1.append(b)
+                    if a=="width":
+                        x2.append(b)
+                    if a=="height":
+                        y2.append(b)
+
+
+
+    for p in range(0,len(x1)):
+        x2[p]=x2[p]+x1[p]
+
+    for p in range(0,len(x1)):
+        y2[p]=y2[p]+x1[p]
+
+    for (x11,y11,x12,y12) in zip(x1,y1,x2,y2):
         cv2.rectangle(
-            img,
-            (a,b),
-            (a+c,b+d),
-            color=(0, 0, 255),
-            thickness=2,
-            lineType=cv2.LINE_AA)
+                img,
+                (x11,y11),
+                (x12,y12),
+                color=(0, 0, 255),
+                thickness=2,
+                lineType=cv2.LINE_AA
+            )
+    
+    return cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+    #cv2.imshow("kamehamehaa",img)
 
-    return cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
 
     
-        
+
+
     
 def predict(img):