Update app.py

app.py

@@ -76,7 +76,7 @@ def return_num_columns(img):
     return num_col
 
 def return_scaled_image(img, num_col, width_early, model_name):
-        if model_name== ("SBB/eynollah-main-regions-aug-rotation" | "SBB/eynollah-main-regions-aug-scaling" | "SBB/eynollah-main-regions-ensembled"):
+    if model_name== ("SBB/eynollah-main-regions-aug-rotation" | "SBB/eynollah-main-regions-aug-scaling" | "SBB/eynollah-main-regions-ensembled"):
         if num_col == 1 and width_early < 1100:
             img_w_new = 2000
             img_h_new = int(img.shape[0] / float(img.shape[1]) * 2000)
@@ -129,7 +129,7 @@ def return_scaled_image(img, num_col, width_early, model_name):
             img_w_new = width_early
             img_h_new = int(img.shape[0] / float(img.shape[1]) * width_early)
         img_new = resize_image(img, img_h_new, img_w_new)
-    if model_name=="SBB/eynollah-main-regions":
+    elif model_name=="SBB/eynollah-main-regions":
         if num_col == 1:
             img_w_new = 1000
             img_h_new = int(img_org.shape[0] / float(img_org.shape[1]) * img_w_new)
@@ -153,8 +153,8 @@ def return_scaled_image(img, num_col, width_early, model_name):
             img_h_new = int(img_org.shape[0] / float(img_org.shape[1]) * img_w_new)
         img_resized = resize_image(img,img_h_new, img_w_new )
 
-        img = otsu_copy_binary(img_resized)
-    return img
+        img_new = otsu_copy_binary(img_resized)
+    return img_new
         
 def do_prediction(model_name, img):
     img_org = np.copy(img)