final touches

app.py

@@ -39,11 +39,6 @@ projects = {
         "project": "melanoma-testnet",
         "description": "This is a testnet competition for melanoma detection."
     },
-    "Simple-cnn": {
-        "entity": "urbaniak-bruno-safescanai",
-        "project": "simple-cnn",
-        "description": "This is a testnen."
-    },
     
     # Add more projects as needed
 }
@@ -141,9 +136,7 @@ def main():
                         st.session_state.leader_info[competition] = update_leader_info(st.session_state.leader_info, competition, best_model)
                     else:
                         st.warning(f"No model found for the best hotkey: {best_hotkey} in competition {competition}.")
-                    # # get the best model with the winning hotkey
-                    # best_model = model_evaluations[competition][model_evaluations[competition]["Hotkey"] == best_hotkey].iloc[0]
-                    # st.session_state.leader_info[competition] = update_leader_info(st.session_state.leader_info, competition, best_model)
+
             else:
                 st.session_state.leader_info[competition] = {
                     "Username": "N/A", "Hotkey": "N/A",
@@ -226,7 +219,6 @@ def main():
         competition_summary_df = competition_summaries.get(competition_name, pd.DataFrame())
 
         if not competition_summary_df.empty:
-            # st.markdown('<div class="table-container">' + competition_summary_df.to_html(classes='dataframe', escape=False) + '</div>', unsafe_allow_html=True)
             st.dataframe(competition_summary_df)
         else:
             st.warning("No competition summary data available.")
@@ -236,7 +228,6 @@ def main():
         st.subheader("Models Evaluation")
         models_evaluation_df = model_evaluations.get(competition_name, pd.DataFrame())
         if not models_evaluation_df.empty:
-            # st.markdown('<div class="table-container">' + models_evaluation_df.to_html(classes='dataframe', escape=False) + '</div>', unsafe_allow_html=True)
             st.dataframe(models_evaluation_df.style.apply(highlight_score_column, axis=0))
         else:
             st.warning("No models evaluation data available.")

utils.py

@@ -71,7 +71,6 @@ def fetch_models_evaluation(api, projects, selected_project):
                     "Precision": summary.get("precision"),
 
                     "Tested entries": summary.get("tested_entries"),
-                    # "Run Time (s)": summary.get("run_time_s"),
 
                     "ROC AUC": summary.get("roc_auc"),
                     "Confusion Matrix": summary.get("confusion_matrix"),