Update app.py

app.py

@@ -39,7 +39,7 @@ def get_filename():
         choice = np.random.choice(range(len(p)),p=p)
         st.session_state.pred = st.session_state.preds[choice]
         return embeddings.index[choice]
-    st.toast('Random for now')
+    # st.toast('Random for now')
     return np.random.choice(embeddings.index)
 
 st.title('What does attractive mean to you?')
@@ -61,7 +61,7 @@ def get_train_data():
     false_files = list(map(clean,glob(f'./users/{st.session_state.name}/likes/*.F')))
     true_embeddings = embeddings.loc[true_files].values
     false_embeddings = embeddings.loc[false_files].values
-    st.toast(f'Found {len(true_files)} positives and {len(false_files)} negatives')
+    # st.toast(f'Found {len(true_files)} positives and {len(false_files)} negatives')
     labels = np.array([1 for _ in true_embeddings] + [0 for _ in false_embeddings])
     st.session_state.labels = pd.Series(labels,index=true_files+false_files).rename('label')
     X = np.vstack([true_embeddings,false_embeddings])
@@ -125,7 +125,7 @@ def get_strange(n=4):
         labels = st.session_state.labels
         preds = pd.Series(st.session_state.preds,index=embeddings.index).loc[labels.index].rename('pred')
         data = pd.concat([labels, preds],axis=1)
-        st.toast(data.columns)
+        # st.toast(data.columns)
         
         data['diff'] = data['pred'] - data['label']
         data = data.sort_values('diff',ascending=False)['diff'] 
@@ -141,6 +141,7 @@ if st.session_state.name:
     setup_user()
     
     st.subheader(f"Let's start {st.session_state.name}")
+    my_bar = st.progress(min(st.session_state.count/40,1.))
     filename = get_filename()