no message

app.py

@@ -15,8 +15,8 @@ DATASETS = [
 MAX_N_LABELS = 5
 SPLIT_TO_CLASSIFY = 'pasta'
 
-COLS = st.columns([3, 1]) 
-
+COLS = st.columns([0.75, 0.25]) 
+SCROLLABLE_TEXT = COLS[1].text_area("Conteúdo da segunda coluna", height=500)
 
 
 
@@ -51,27 +51,27 @@ def classify_full_dataset(shosen_dataset_name, chosen_model_name):
      
     #dataset
     dataset = load_dataset(shosen_dataset_name,"testedata_readme")
-    with COLS[1]:
+    with SCROLLABLE_TEXT:
         #Image teste load 
         image_object = dataset['pasta'][0]["image"]
         st.image(image_object, caption="Uploaded Image", width=300)
-        st.write("### FLAG 3")
+        #st.write("### FLAG 3")
         
     #modle instance
     classifier_pipeline = pipeline('image-classification', model=chosen_model_name)
-    COLS[1].write("### FLAG 4")
+    #COLS[1].write("### FLAG 4")
     
     #classification
     classification_result = classifier_pipeline(image_object)
-    COLS[1].write(classification_result)
-    COLS[1].write("### FLAG 5")
+    SCROLLABLE_TEXT.write(classification_result)
+    #COLS[1].write("### FLAG 5")
     #classification_array.append(classification_result)
     
     #save classification
     
     image_count += 1
-    COLS[1].write(f"Image count: {image_count}")
-    
+    SCROLLABLE_TEXT.write("Image count")
+    SCROLLABLE_TEXT.write(image_count)  
     return image_count
 
 
@@ -92,7 +92,8 @@ def main():
     
      
     COLS[0].write("# Bulk Image Classification App")
-        
+    
+      
     #with CONTAINER_BODY:
     with COLS[0]:
         st.markdown("This app uses several 🤗 models to classify images stored in 🤗 datasets.")