Update app.py

app.py

@@ -19,7 +19,7 @@ def process_img(img_path):
 
 st.title("Table Extract")
 file_name = st.file_uploader("Upload a repport image")
-
+print(type(file_name),file_name)
 if file_name is not None:
     col1, col2 = st.columns(2)
 
@@ -30,20 +30,20 @@ if file_name is not None:
     bbox,confidance , classes , nc  = bbox[0].numpy(),confidance[0].numpy(),classes[0].numpy(),nc[0].numpy()
     
     for i in range(nc):
-    if confidance[i] >= threshold:
-        x1,y1,x2,y2 = bbox[i]*640
-        class_name = labels[int(classes[i])]
-        if class_name =="Header":
-            color = (0,0,255) #Blue color
-            cv2.rectangle(copy_img, (int(x1), int(y1)), (int(x2), int(y2)),color, 2)
-
-        if class_name =="Column":
-            color = (0,255,0) #Green color
-            cv2.rectangle(copy_img, (int(x1), int(y1)), (int(x2), int(y2)),color, 2)
-
-        if class_name =="Table":
-            color = (255,0,0) #Red color
-            cv2.rectangle(copy_img, (int(x1), int(y1)), (int(x2), int(y2)),color, 2)
+        if confidance[i] >= threshold:
+            x1,y1,x2,y2 = bbox[i]*640
+            class_name = labels[int(classes[i])]
+            if class_name =="Header":
+                color = (0,0,255) #Blue color
+                cv2.rectangle(copy_img, (int(x1), int(y1)), (int(x2), int(y2)),color, 2)
+    
+            if class_name =="Column":
+                color = (0,255,0) #Green color
+                cv2.rectangle(copy_img, (int(x1), int(y1)), (int(x2), int(y2)),color, 2)
+    
+            if class_name =="Table":
+                color = (255,0,0) #Red color
+                cv2.rectangle(copy_img, (int(x1), int(y1)), (int(x2), int(y2)),color, 2)
 
     col2.image(copy_img, use_column_width=True)