test

app.py

@@ -15,6 +15,9 @@ DATASETS = [
 MAX_N_LABELS = 5
 SPLIT_TO_CLASSIFY = 'pasta'
 COL1, COL2 = st.columns([3, 1])
+CONTAINER_TOP = st.container()
+CONTAINER_BODY = st.container()
+
 
 
 #(image_object, classifier_pipeline)
@@ -74,43 +77,47 @@ def classify_full_dataset(shosen_dataset_name, chosen_model_name):
     return image_count
 
 def main():
-    st.title("Bulk Image Classification DEMO")
+    
+    with CONTAINER_TOP:
+        st.title("Bulk Image Classification DEMO")
     
     
     # Restart or reset your app
     # if st.button("Restart"):
     # # Code to restart or reset your app goes here
-    #     import subprocess
-    #     subprocess.call(["shutdown", "-r", "-t", "0"])
-    
-    
-    with COL1:
-        st.markdown("This app uses several 🤗 models to classify images stored in 🤗 datasets.")
-        st.write("Soon we will have a dataset template")
-        
-      
-            
-        #Model
-        chosen_model_name = st.selectbox("Select the model to use",  MODELS, index=0)
-        if chosen_model_name is not None:
-            st.write("You selected", chosen_model_name) 
-            
-        #Dataset
-        shosen_dataset_name = st.selectbox("Select the dataset to use",  DATASETS, index=0)
-        if shosen_dataset_name is not None:
-            st.write("You selected", shosen_dataset_name)
-            
-        #click to classify
-        #image_object = dataset['pasta'][0]  
-        if chosen_model_name is not None and shosen_dataset_name is not None:
-            if st.button("Classify images"):
-            
-                #classification_array =[]
-                classification_result = classify_full_dataset(shosen_dataset_name, chosen_model_name)
-                st.write(f"Classification result: {classification_result}")
-                #classification_array.append(classification_result)
-                #st.write("# FLAG 6")
-                #st.write(classification_array)   
+        #     import subprocess
+        #     subprocess.call(["shutdown", "-r", "-t", "0"])
+        CONTAINER_BODY = st.container():
+
+
+
+        with COL1:
+            st.markdown("This app uses several 🤗 models to classify images stored in 🤗 datasets.")
+            st.write("Soon we will have a dataset template")
+
+
+
+            #Model
+            chosen_model_name = st.selectbox("Select the model to use",  MODELS, index=0)
+            if chosen_model_name is not None:
+                st.write("You selected", chosen_model_name) 
+
+            #Dataset
+            shosen_dataset_name = st.selectbox("Select the dataset to use",  DATASETS, index=0)
+            if shosen_dataset_name is not None:
+                st.write("You selected", shosen_dataset_name)
+
+            #click to classify
+            #image_object = dataset['pasta'][0]  
+            if chosen_model_name is not None and shosen_dataset_name is not None:
+                if st.button("Classify images"):
+                
+                    #classification_array =[]
+                    classification_result = classify_full_dataset(shosen_dataset_name, chosen_model_name)
+                    st.write(f"Classification result: {classification_result}")
+                    #classification_array.append(classification_result)
+                    #st.write("# FLAG 6")
+                    #st.write(classification_array)   
 
 if __name__ == "__main__":
     main()