change the title name in main.py

main.py

@@ -1,89 +1,89 @@
-import streamlit as st
-import pandas as pd
-import json
-
-# 读取 JSON 数据
-with open('GenAI-Bench_tags.json', 'r') as file:
-    data = json.load(file)
-
-# Streamlit 页面标题
-
-st.set_page_config(page_title="GenAI-Bench Dataset Viewer", page_icon=None, layout="wide", initial_sidebar_state="auto",
-                   menu_items=None)
-st.title('GenAI Bench Leaderboard')
-# 多选框
-basic_options = []
-advanced_options = []
-
-for i in data:
-    data[i]['basic'].sort()
-    data[i]['advanced'].sort()
-
-    for basic in data[i]['basic']:
-        if basic not in basic_options:
-            basic_options.append(basic)
-    for adv in data[i]['advanced']:
-        if adv not in advanced_options:
-            advanced_options.append(adv)
-    data[i]['id'] = i
-    # modles = ["DALLE_3","DeepFloyd_I_XL_v1","Midjourney_6","SDXL_2_1","SDXL_Base","SDXL_Turbo"]
-    data[i]['DALLE_3'] = f"app/static/DALLE_3/{i}.jpeg"
-    data[i]['DeepFloyd_I_XL_v1'] = f"app/static/DeepFloyd_I_XL_v1/{i}.jpeg"
-    data[i]['Midjourney_6'] = f"app/static/Midjourney_6/{i}.jpeg"
-    data[i]['SDXL_2_1'] = f"app/static/SDXL_2_1/{i}.jpeg"
-    data[i]['SDXL_Base'] = f"app/static/SDXL_Base/{i}.jpeg"
-    data[i]['SDXL_Turbo'] = f"app/static/SDXL_Turbo/{i}.jpeg"
-
-    data[i]['DALLE_3_Human'] = -1
-    data[i]['DeepFloyd_I_XL_v1_Human'] = -1
-    data[i]['Midjourney_6_Human'] = -1
-    data[i]['SDXL_2_1_Human'] = -1
-    data[i]['SDXL_Base_Human'] = -1
-    data[i]['SDXL_Turbo_Human'] = -1
-
-selected_basic = st.multiselect('Select Basic Skills:', basic_options)
-selected_advanced = st.multiselect('Select Advanced Skills:', advanced_options)
-
-# 筛选数据
-filtered_data = [
-    data[item] for item in data
-    if all(elem in data[item]['basic'] for elem in selected_basic) and
-       all(advanced in data[item]['advanced'] for advanced in selected_advanced)
-]
-
-# 显示筛选后的数据
-if filtered_data:
-    df = pd.DataFrame(filtered_data)
-    df = df.reindex(columns=["id", "prompt", "basic", "advanced", "DALLE_3", "DALLE_3_Human", "DeepFloyd_I_XL_v1",
-                             "DeepFloyd_I_XL_v1_Human", "Midjourney_6", "Midjourney_6_Human", "SDXL_2_1",
-                             "SDXL_2_1_Human", "SDXL_Base", "SDXL_Base_Human", "SDXL_Turbo", "SDXL_Turbo_Human"])
-    # df['pic'] = df['pic'].apply(lambda x: f'< img src="{x}" width="60">')
-    # st.write(df.to_html(escape=False), unsafe_allow_html=True)
-    st.dataframe(data=df, width = 4096, height = 800,
-                 column_config={
-                     "name": "Data Explorer",
-                     "id": st.column_config.NumberColumn("ID", format="%d", width="small"),
-                     'basic': st.column_config.ListColumn(label="Basic Skills", width="large", help=None),
-                     'advanced': st.column_config.ListColumn(label="Advanced Skills", width="large", help=None),
-                     'prompt': st.column_config.TextColumn(label="Prompt", width="large", help=None, disabled=None,
-                                                           required=None,
-                                                           default=None, max_chars=None, validate=None),
-                     "DALLE_3": st.column_config.ImageColumn(label="DALLE_3", width="small", help=None),
-                     "DAllE_3_Human": st.column_config.NumberColumn("Rating Human", format="%d", width="small", help="Rating Human for DALLE_3"),
-                     "DeepFloyd_I_XL_v1": st.column_config.ImageColumn(label="DeepFloyd", width="small",
-                                                                       help="DeepFloyd_I_XL_v1"),
-                     "DeepFloyd_I_XL_v1_Human": st.column_config.NumberColumn("Rating Human", format="%d",
-                                                                              width="small", help="Rating Human for DeepFloyd"),
-                     "Midjourney_6": st.column_config.ImageColumn(label="Midjourney", width="small", help="Midjourney_6"),
-                     "Midjourney_6_Human": st.column_config.NumberColumn("Rating Human", format="%d",
-                                                                         width="small", help="Rating Human for Midjourney_6"),
-                     "SDXL_2_1": st.column_config.ImageColumn(label="SDXL_2_1", width="small", help=None),
-                     "SDXL_2_1_Human": st.column_config.NumberColumn("Rating Human", format="%d", width="small", help="Rating Human for SDXL_2_1"),
-                     "SDXL_Base": st.column_config.ImageColumn(label="SDXL_Base", width="small", help=None),
-                     "SDXL_Base_Human": st.column_config.NumberColumn("Rating Human", format="%d", width="small", help="Rating Human for SDXL_Base"),
-                     "SDXL_Turbo": st.column_config.ImageColumn(label="SDXL_Turbo", width="small", help=None),
-                     "SDXL_Turbo_Human": st.column_config.NumberColumn("Rating Human", format="%d", width="small", help="Rating Human for SDXL_Turbo"),
-                 },
-                 hide_index=True, selection_mode="single-row")
-else:
-    st.write("No data matches the selected filters.")
+import streamlit as st
+import pandas as pd
+import json
+
+# 读取 JSON 数据
+with open('GenAI-Bench_tags.json', 'r') as file:
+    data = json.load(file)
+
+# Streamlit 页面标题
+
+st.set_page_config(page_title="GenAI-Bench Dataset Viewer", page_icon=None, layout="wide", initial_sidebar_state="auto",
+                   menu_items=None)
+st.title('GenAI-Bench Dataset Viewer')
+# 多选框
+basic_options = []
+advanced_options = []
+
+for i in data:
+    data[i]['basic'].sort()
+    data[i]['advanced'].sort()
+
+    for basic in data[i]['basic']:
+        if basic not in basic_options:
+            basic_options.append(basic)
+    for adv in data[i]['advanced']:
+        if adv not in advanced_options:
+            advanced_options.append(adv)
+    data[i]['id'] = i
+    # modles = ["DALLE_3","DeepFloyd_I_XL_v1","Midjourney_6","SDXL_2_1","SDXL_Base","SDXL_Turbo"]
+    data[i]['DALLE_3'] = f"app/static/DALLE_3/{i}.jpeg"
+    data[i]['DeepFloyd_I_XL_v1'] = f"app/static/DeepFloyd_I_XL_v1/{i}.jpeg"
+    data[i]['Midjourney_6'] = f"app/static/Midjourney_6/{i}.jpeg"
+    data[i]['SDXL_2_1'] = f"app/static/SDXL_2_1/{i}.jpeg"
+    data[i]['SDXL_Base'] = f"app/static/SDXL_Base/{i}.jpeg"
+    data[i]['SDXL_Turbo'] = f"app/static/SDXL_Turbo/{i}.jpeg"
+
+    data[i]['DALLE_3_Human'] = -1
+    data[i]['DeepFloyd_I_XL_v1_Human'] = -1
+    data[i]['Midjourney_6_Human'] = -1
+    data[i]['SDXL_2_1_Human'] = -1
+    data[i]['SDXL_Base_Human'] = -1
+    data[i]['SDXL_Turbo_Human'] = -1
+
+selected_basic = st.multiselect('Select Basic Skills:', basic_options)
+selected_advanced = st.multiselect('Select Advanced Skills:', advanced_options)
+
+# 筛选数据
+filtered_data = [
+    data[item] for item in data
+    if all(elem in data[item]['basic'] for elem in selected_basic) and
+       all(advanced in data[item]['advanced'] for advanced in selected_advanced)
+]
+
+# 显示筛选后的数据
+if filtered_data:
+    df = pd.DataFrame(filtered_data)
+    df = df.reindex(columns=["id", "prompt", "basic", "advanced", "DALLE_3", "DALLE_3_Human", "DeepFloyd_I_XL_v1",
+                             "DeepFloyd_I_XL_v1_Human", "Midjourney_6", "Midjourney_6_Human", "SDXL_2_1",
+                             "SDXL_2_1_Human", "SDXL_Base", "SDXL_Base_Human", "SDXL_Turbo", "SDXL_Turbo_Human"])
+    # df['pic'] = df['pic'].apply(lambda x: f'< img src="{x}" width="60">')
+    # st.write(df.to_html(escape=False), unsafe_allow_html=True)
+    st.dataframe(data=df, width = 4096, height = 800,
+                 column_config={
+                     "name": "Data Explorer",
+                     "id": st.column_config.NumberColumn("ID", format="%d", width="small"),
+                     'basic': st.column_config.ListColumn(label="Basic Skills", width="large", help=None),
+                     'advanced': st.column_config.ListColumn(label="Advanced Skills", width="large", help=None),
+                     'prompt': st.column_config.TextColumn(label="Prompt", width="large", help=None, disabled=None,
+                                                           required=None,
+                                                           default=None, max_chars=None, validate=None),
+                     "DALLE_3": st.column_config.ImageColumn(label="DALLE_3", width="small", help=None),
+                     "DAllE_3_Human": st.column_config.NumberColumn("Rating Human", format="%d", width="small", help="Rating Human for DALLE_3"),
+                     "DeepFloyd_I_XL_v1": st.column_config.ImageColumn(label="DeepFloyd", width="small",
+                                                                       help="DeepFloyd_I_XL_v1"),
+                     "DeepFloyd_I_XL_v1_Human": st.column_config.NumberColumn("Rating Human", format="%d",
+                                                                              width="small", help="Rating Human for DeepFloyd"),
+                     "Midjourney_6": st.column_config.ImageColumn(label="Midjourney", width="small", help="Midjourney_6"),
+                     "Midjourney_6_Human": st.column_config.NumberColumn("Rating Human", format="%d",
+                                                                         width="small", help="Rating Human for Midjourney_6"),
+                     "SDXL_2_1": st.column_config.ImageColumn(label="SDXL_2_1", width="small", help=None),
+                     "SDXL_2_1_Human": st.column_config.NumberColumn("Rating Human", format="%d", width="small", help="Rating Human for SDXL_2_1"),
+                     "SDXL_Base": st.column_config.ImageColumn(label="SDXL_Base", width="small", help=None),
+                     "SDXL_Base_Human": st.column_config.NumberColumn("Rating Human", format="%d", width="small", help="Rating Human for SDXL_Base"),
+                     "SDXL_Turbo": st.column_config.ImageColumn(label="SDXL_Turbo", width="small", help=None),
+                     "SDXL_Turbo_Human": st.column_config.NumberColumn("Rating Human", format="%d", width="small", help="Rating Human for SDXL_Turbo"),
+                 },
+                 hide_index=True, selection_mode="single-row")
+else:
+    st.write("No data matches the selected filters.")