refine

app.py

@@ -177,13 +177,154 @@ def select_columns(df: pd.DataFrame, columns_1: list) -> pd.DataFrame:
 
 demo = gr.Blocks(css=custom_css)
 with demo:
-    gr.HTML(TITLE)
+    with gr.Row():
+        gr.Image("./assets/logo.png", height="175px", width="675px", scale=0.2,
+                 show_download_button=False, container=False)
+        gr.HTML(TITLE, elem_id="title")
     gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text")
     gr.Markdown(EVALUATION_QUEUE_TEXT,elem_classes="eval-text")
     gr.Markdown(LLM_BENCHMARKS_TEXT, elem_classes="reference-text")
 
     with gr.Tabs(elem_classes="tab-buttons") as tabs:
-        with gr.TabItem("UnlearnDiffAtk Benchmark", elem_id="UnlearnDiffAtk-benchmark-tab-table", id=0):
+        with gr.TabItem("🔞 NSFW", elem_id="UnlearnDiffAtk-benchmark-tab-table", id=0):
+            files = ['nudity']
+            with gr.Row():
+                with gr.Column():
+                    with gr.Row():
+                        search_bar = gr.Textbox(
+                            placeholder=" 🔍 Search for your model (separate multiple queries with `;`) and press ENTER...",
+                            show_label=False,
+                            elem_id="search-bar",
+                        )
+                    with gr.Row():
+                        model1_column = gr.CheckboxGroup(
+                        label="Evaluation Metrics",
+                        choices=['Pre-ASR','Post-ASR','FID','CLIP-Score'],
+                        interactive=True,
+                        elem_id="column-select",
+                    )
+                   
+            for i in range(len(files)):
+                
+                if files[i] == 'nudity':
+                    name = "### [Unlearned  Concept]: "+" Nudity"
+                    csv_path = './assets/'+files[i]+'.csv'
+                # elif files[i] == 'violence':
+                #     name = "### Unlearned Concepts "+" Violence"
+                #     csv_path = './assets/'+files[i]+'.csv'
+                # elif files[i] == 'illegal_activity':
+                #     name = "### Unlearned Concepts "+" Illgal Activity"
+                #     csv_path = './assets/'+files[i]+'.csv'
+                
+            
+                gr.Markdown(name)
+                df_results = load_data(csv_path)
+                df_results_init = df_results.copy()[show_columns]
+                leaderboard_table = gr.components.Dataframe(
+                value = df_results,
+                datatype = TYPES,
+                elem_id = "leaderboard-table",
+                interactive = False,
+                visible=True,
+                )
+
+            
+                hidden_leaderboard_table_for_search = gr.components.Dataframe(
+                    value=df_results_init,
+                    # value=df_results,
+                    interactive=False,
+                    visible=False,
+                )
+        
+                search_bar.submit(
+                    update_table,
+                    [   
+                        
+                        hidden_leaderboard_table_for_search,
+                        model1_column,
+                        search_bar,
+                    ],
+                    leaderboard_table,
+                )
+
+                for selector in [model1_column]:
+                    selector.change(
+                        update_table,
+                        [   
+                            hidden_leaderboard_table_for_search,
+                            model1_column,
+                            search_bar,
+                        ],
+                        leaderboard_table,
+                )
+                    
+        with gr.TabItem("🎨 Style", elem_id="Style", id=1):
+            files = ['vangogh']
+            with gr.Row():
+                with gr.Column():
+                    with gr.Row():
+                        search_bar = gr.Textbox(
+                            placeholder=" 🔍 Search for your model (separate multiple queries with `;`) and press ENTER...",
+                            show_label=False,
+                            elem_id="search-bar",
+                        )
+                    with gr.Row():
+                        model1_column = gr.CheckboxGroup(
+                        label="Evaluation Metrics",
+                        choices=['Pre-ASR','Post-ASR','FID','CLIP-Score'],
+                        interactive=True,
+                        elem_id="column-select",
+                    )
+                   
+            for i in range(len(files)):
+                
+                if files[i] == 'vangogh':
+                    name = "### [Unlearned Style]: "+" Van Gogh"
+                    csv_path = './assets/'+files[i]+'.csv'
+                
+                gr.Markdown(name)
+                df_results = load_data(csv_path)
+                df_results_init = df_results.copy()[show_columns]
+                leaderboard_table = gr.components.Dataframe(
+                value = df_results,
+                datatype = TYPES,
+                elem_id = "leaderboard-table",
+                interactive = False,
+                visible=True,
+                )
+
+            
+                hidden_leaderboard_table_for_search = gr.components.Dataframe(
+                    value=df_results_init,
+                    # value=df_results,
+                    interactive=False,
+                    visible=False,
+                )
+        
+                search_bar.submit(
+                    update_table,
+                    [   
+                        
+                        hidden_leaderboard_table_for_search,
+                        model1_column,
+                        search_bar,
+                    ],
+                    leaderboard_table,
+                )
+
+                for selector in [model1_column]:
+                    selector.change(
+                        update_table,
+                        [   
+                            hidden_leaderboard_table_for_search,
+                            model1_column,
+                            search_bar,
+                        ],
+                        leaderboard_table,
+                )
+        
+        with gr.TabItem("🪂 Object", elem_id="UnlearnDiffAtk-benchmark-tab-table", id=2):
+            files = ['church','garbage','parachute','tench']
             with gr.Row():
                 with gr.Column():
                     with gr.Row():
@@ -202,29 +343,17 @@ with demo:
                    
             for i in range(len(files)):
                 if files[i] == "church":
-                    name = "### [Unlearned Objects] "+" Church" 
+                    name = "### [Unlearned Object]: "+" Church" 
                     csv_path = './assets/'+files[i]+'.csv'
                 elif files[i] == 'garbage':
-                    name = "### [Unlearned Objects] "+" Garbage"
+                    name = "### [Unlearned Object]: "+" Garbage"
                     csv_path = './assets/'+files[i]+'.csv'
                 elif files[i] == 'tench':
-                    name = "### [Unlearned Objects] "+" Tench"
+                    name = "### [Unlearned Object]: "+" Tench"
                     csv_path = './assets/'+files[i]+'.csv'
                 elif files[i] == 'parachute':
-                    name = "### [Unlearned Objects] "+" Parachute"
+                    name = "### [Unlearned Object]: "+" Parachute"
                     csv_path = './assets/'+files[i]+'.csv'
-                elif files[i] == 'vangogh':
-                    name = "### [Unlearned Style] "+" Van Gogh"
-                    csv_path = './assets/'+files[i]+'.csv'
-                elif files[i] == 'nudity':
-                    name = "### Unlearned  Concepts "+" Nudity"
-                    csv_path = './assets/'+files[i]+'.csv'
-                # elif files[i] == 'violence':
-                #     name = "### Unlearned Concepts "+" Violence"
-                #     csv_path = './assets/'+files[i]+'.csv'
-                # elif files[i] == 'illegal_activity':
-                #     name = "### Unlearned Concepts "+" Illgal Activity"
-                #     csv_path = './assets/'+files[i]+'.csv'
                 
             
                 gr.Markdown(name)