Update app.py

app.py

@@ -15,15 +15,16 @@ df =  pd.read_csv(helper_csv)
 model = load_learner(model_path)
 
 def result(path):    
-  pred,_,probability = model.predict(path)
-  arr = ['Species','Scientific Name','Name','Habitat','Color','Found_In','Diet']
-  vals = ['','','','','','','','']
-  for x in pred:
-      val = df[df['columns'] == x]['values']
-      ind = arr.index(val)
-      vals[ind] = x 
+    pred,_,probability = model.predict(path)
+    arr = ['Species','Scientific_Name','Name','Conservation_Status','Color','habitat','Found_In','Diet']
+    vals = ['','','','','','','','']
+    pred = ['Acrantophis madagascariensis', 'Carnivore', 'Critically Endangered', 'Forest', 'Gray', 'Madagascar', 'Madagascar ground boa ', 'Snake']
+    for x in pred:
+        val = df[df['values'] == x]['columns'].values[0]
+        ind = arr.index(val)
+        vals[ind] = x
       
-  return f'{arr}-->{vals}'
+    return f'{arr[0]}:\t{vals[0]}\n{arr[1]}:\t{vals[1]}\n{arr[2]}:\t{vals[2]}\n{arr[3]}:\t{vals[3]}\n{arr[4]}:\t{vals[4]}\n{arr[5]}:\t{vals[5]}\n{arr[6]}:\t{vals[6]}\n{arr[7]}:\t{vals[7]}\n'
 
     
 path = 'test images/'