update font

app.py

@@ -20,7 +20,7 @@ i2t_models = [  # Average time spent running the following example
 "gpt-4o-2024-05-13",
 "llava-hf/llava-v1.6-vicuna-7b-hf"
 ]
-perspectives = ["safety", "fairness", "hallucination", "privacy",  "adv", "ood"]
+perspectives = ["Safety", "Fairness", "Hallucination", "Privacy",  "Adv", "OOD"]
 main_scores_t2i = {}
 main_scores_i2t = {}
 
@@ -32,22 +32,22 @@ for model in t2i_models:
     for perspective in perspectives:
         if perspective not in sub_scores_t2i.keys():
             sub_scores_t2i[perspective] = {}
-        if perspective == "hallucination":
+        if perspective == "Hallucination":
             main_scores_t2i[model][perspective] = hallucination_t2i_agg(model, "./data/results")["score"]
             sub_scores_t2i[perspective][model] = hallucination_t2i_agg(model, "./data/results")["subscenarios"]   
-        elif perspective == "safety":
+        elif perspective == "Safety":
             main_scores_t2i[model][perspective] = safety_t2i_agg(model, "./data/results")["score"]
             sub_scores_t2i[perspective][model] = safety_t2i_agg(model, "./data/results")["subscenarios"]
-        elif perspective == "adv":
+        elif perspective == "Adv":
             main_scores_t2i[model][perspective] = adversarial_robustness_t2i_agg(model, "./data/results")["score"]
             sub_scores_t2i[perspective][model] = adversarial_robustness_t2i_agg(model, "./data/results")["subscenarios"]   
-        elif perspective == "fairness":
+        elif perspective == "Fairness":
             main_scores_t2i[model][perspective] = fairness_t2i_agg(model, "./data/results")["score"]
             sub_scores_t2i[perspective][model] = fairness_t2i_agg(model, "./data/results")["subscenarios"]
-        elif perspective == "privacy":
+        elif perspective == "Privacy":
             main_scores_t2i[model][perspective] = privacy_t2i_agg(model, "./data/results")["score"]
             sub_scores_t2i[perspective][model] = privacy_t2i_agg(model, "./data/results")["subscenarios"]
-        elif perspective == "ood":
+        elif perspective == "OOD":
             main_scores_t2i[model][perspective] = ood_t2i_agg(model, "./data/results")["score"]
             sub_scores_t2i[perspective][model] = ood_t2i_agg(model, "./data/results")["subscenarios"]
         else:
@@ -60,24 +60,24 @@ for model in i2t_models:
     for perspective in perspectives:
         if perspective not in sub_scores_i2t.keys():
             sub_scores_i2t[perspective] = {}
-        if perspective == "hallucination":
+        if perspective == "Hallucination":
             main_scores_i2t[model][perspective] = hallucination_i2t_agg(model, "./data/results")["score"]
             sub_scores_i2t[perspective][model] = hallucination_i2t_agg(model, "./data/results")["subscenarios"]
-        elif perspective == "safety":
+        elif perspective == "Safety":
             main_scores_i2t[model][perspective] = safety_i2t_agg(model, "./data/results")["score"]
             sub_scores_i2t[perspective][model] = safety_i2t_agg(model, "./data/results")["subscenarios"]
-        elif perspective == "adv":
+        elif perspective == "Adv":
             main_scores_i2t[model][perspective] = adversarial_robustness_i2t_agg(model, "./data/results")["score"]
             sub_scores_i2t[perspective][model] = adversarial_robustness_i2t_agg(model, "./data/results")["subscenarios"]
-        elif perspective == "fairness":
+        elif perspective == "Fairness":
             main_scores_i2t[model][perspective] = fairness_i2t_agg(model, "./data/results")["score"]
             sub_scores_i2t[perspective][model] = fairness_i2t_agg(model, "./data/results")["subscenarios"]
-        elif perspective == "privacy":
+        elif perspective == "Privacy":
             main_scores_i2t[model][perspective] = privacy_i2t_agg(model, "./data/results")["score"]
             sub_scores_i2t[perspective][model] = privacy_i2t_agg(model, "./data/results")["subscenarios"]
-        elif perspective == "ood":
+        elif perspective == "OOD":
             main_scores_i2t[model][perspective] = ood_i2t_agg(model, "./data/results")["score"]
-            sub_scores_i2t[perspective][model] = ood_i2t_agg
+            sub_scores_i2t[perspective][model] = ood_i2t_agg(model, "./data/results")["subscenarios"]
         else:
             raise ValueError("Invalid perspective")
 

generate_plot.py

@@ -52,11 +52,11 @@ def radar_plot(results, thetas, selected_models):
 
     fig.add_trace(
         go.Table(
-            header=dict(values=header_texts, font=dict(size=12), align="left"),
+            header=dict(values=header_texts, font=dict(size=14.5), align="left"),
             cells=dict(
                 values=rows,
                 align="left",
-                font=dict(size=12),
+                font=dict(size=14.5),
                 height=30
             ),
             # columnwidth=column_widths
@@ -120,11 +120,11 @@ def main_radar_plot(main_scores, selected_models):
 
     fig.add_trace(
         go.Table(
-            header=dict(values=header_texts, font=dict(size=12), align="left"),
+            header=dict(values=header_texts, font=dict(size=14.5), align="left"),
             cells=dict(
                 values=rows,
                 align="left",
-                font=dict(size=12),
+                font=dict(size=14.5),
                 height=30,
             ),
             columnwidth=column_widths,
@@ -206,7 +206,7 @@ if __name__ == "__main__":
     "gpt-4o-2024-05-13",
     "llava-hf/llava-v1.6-vicuna-7b-hf"
     ]
-    perspectives = ["safety", "fairness", "hallucination", "privacy",  "adv", "ood"]
+    perspectives = ["Safety", "Fairness", "Hallucination", "Privacy",  "Adv", "OOD"]
     main_scores_t2i = {}
     main_scores_i2t = {}
     sub_scores_t2i = {}