DamonDemon commited on
Commit
c701b95
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1 Parent(s): ae59f2a
Files changed (1) hide show
  1. app.py +147 -18
app.py CHANGED
@@ -177,13 +177,154 @@ def select_columns(df: pd.DataFrame, columns_1: list) -> pd.DataFrame:
177
 
178
  demo = gr.Blocks(css=custom_css)
179
  with demo:
180
- gr.HTML(TITLE)
 
 
 
181
  gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text")
182
  gr.Markdown(EVALUATION_QUEUE_TEXT,elem_classes="eval-text")
183
  gr.Markdown(LLM_BENCHMARKS_TEXT, elem_classes="reference-text")
184
 
185
  with gr.Tabs(elem_classes="tab-buttons") as tabs:
186
- with gr.TabItem("UnlearnDiffAtk Benchmark", elem_id="UnlearnDiffAtk-benchmark-tab-table", id=0):
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
187
  with gr.Row():
188
  with gr.Column():
189
  with gr.Row():
@@ -202,29 +343,17 @@ with demo:
202
 
203
  for i in range(len(files)):
204
  if files[i] == "church":
205
- name = "### [Unlearned Objects] "+" Church"
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  csv_path = './assets/'+files[i]+'.csv'
207
  elif files[i] == 'garbage':
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- name = "### [Unlearned Objects] "+" Garbage"
209
  csv_path = './assets/'+files[i]+'.csv'
210
  elif files[i] == 'tench':
211
- name = "### [Unlearned Objects] "+" Tench"
212
  csv_path = './assets/'+files[i]+'.csv'
213
  elif files[i] == 'parachute':
214
- name = "### [Unlearned Objects] "+" Parachute"
215
  csv_path = './assets/'+files[i]+'.csv'
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- elif files[i] == 'vangogh':
217
- name = "### [Unlearned Style] "+" Van Gogh"
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- csv_path = './assets/'+files[i]+'.csv'
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- elif files[i] == 'nudity':
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- name = "### Unlearned Concepts "+" Nudity"
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- csv_path = './assets/'+files[i]+'.csv'
222
- # elif files[i] == 'violence':
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- # name = "### Unlearned Concepts "+" Violence"
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- # csv_path = './assets/'+files[i]+'.csv'
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- # elif files[i] == 'illegal_activity':
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- # name = "### Unlearned Concepts "+" Illgal Activity"
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- # csv_path = './assets/'+files[i]+'.csv'
228
 
229
 
230
  gr.Markdown(name)
 
177
 
178
  demo = gr.Blocks(css=custom_css)
179
  with demo:
180
+ with gr.Row():
181
+ gr.Image("./assets/logo.png", height="175px", width="675px", scale=0.2,
182
+ show_download_button=False, container=False)
183
+ gr.HTML(TITLE, elem_id="title")
184
  gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text")
185
  gr.Markdown(EVALUATION_QUEUE_TEXT,elem_classes="eval-text")
186
  gr.Markdown(LLM_BENCHMARKS_TEXT, elem_classes="reference-text")
187
 
188
  with gr.Tabs(elem_classes="tab-buttons") as tabs:
189
+ with gr.TabItem("πŸ”ž NSFW", elem_id="UnlearnDiffAtk-benchmark-tab-table", id=0):
190
+ files = ['nudity']
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+ with gr.Row():
192
+ with gr.Column():
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+ with gr.Row():
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+ search_bar = gr.Textbox(
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+ placeholder=" πŸ” Search for your model (separate multiple queries with `;`) and press ENTER...",
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+ show_label=False,
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+ elem_id="search-bar",
198
+ )
199
+ with gr.Row():
200
+ model1_column = gr.CheckboxGroup(
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+ label="Evaluation Metrics",
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+ choices=['Pre-ASR','Post-ASR','FID','CLIP-Score'],
203
+ interactive=True,
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+ elem_id="column-select",
205
+ )
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+
207
+ for i in range(len(files)):
208
+
209
+ if files[i] == 'nudity':
210
+ name = "### [Unlearned Concept]: "+" Nudity"
211
+ csv_path = './assets/'+files[i]+'.csv'
212
+ # elif files[i] == 'violence':
213
+ # name = "### Unlearned Concepts "+" Violence"
214
+ # csv_path = './assets/'+files[i]+'.csv'
215
+ # elif files[i] == 'illegal_activity':
216
+ # name = "### Unlearned Concepts "+" Illgal Activity"
217
+ # csv_path = './assets/'+files[i]+'.csv'
218
+
219
+
220
+ gr.Markdown(name)
221
+ df_results = load_data(csv_path)
222
+ df_results_init = df_results.copy()[show_columns]
223
+ leaderboard_table = gr.components.Dataframe(
224
+ value = df_results,
225
+ datatype = TYPES,
226
+ elem_id = "leaderboard-table",
227
+ interactive = False,
228
+ visible=True,
229
+ )
230
+
231
+
232
+ hidden_leaderboard_table_for_search = gr.components.Dataframe(
233
+ value=df_results_init,
234
+ # value=df_results,
235
+ interactive=False,
236
+ visible=False,
237
+ )
238
+
239
+ search_bar.submit(
240
+ update_table,
241
+ [
242
+
243
+ hidden_leaderboard_table_for_search,
244
+ model1_column,
245
+ search_bar,
246
+ ],
247
+ leaderboard_table,
248
+ )
249
+
250
+ for selector in [model1_column]:
251
+ selector.change(
252
+ update_table,
253
+ [
254
+ hidden_leaderboard_table_for_search,
255
+ model1_column,
256
+ search_bar,
257
+ ],
258
+ leaderboard_table,
259
+ )
260
+
261
+ with gr.TabItem("🎨 Style", elem_id="Style", id=1):
262
+ files = ['vangogh']
263
+ with gr.Row():
264
+ with gr.Column():
265
+ with gr.Row():
266
+ search_bar = gr.Textbox(
267
+ placeholder=" πŸ” Search for your model (separate multiple queries with `;`) and press ENTER...",
268
+ show_label=False,
269
+ elem_id="search-bar",
270
+ )
271
+ with gr.Row():
272
+ model1_column = gr.CheckboxGroup(
273
+ label="Evaluation Metrics",
274
+ choices=['Pre-ASR','Post-ASR','FID','CLIP-Score'],
275
+ interactive=True,
276
+ elem_id="column-select",
277
+ )
278
+
279
+ for i in range(len(files)):
280
+
281
+ if files[i] == 'vangogh':
282
+ name = "### [Unlearned Style]: "+" Van Gogh"
283
+ csv_path = './assets/'+files[i]+'.csv'
284
+
285
+ gr.Markdown(name)
286
+ df_results = load_data(csv_path)
287
+ df_results_init = df_results.copy()[show_columns]
288
+ leaderboard_table = gr.components.Dataframe(
289
+ value = df_results,
290
+ datatype = TYPES,
291
+ elem_id = "leaderboard-table",
292
+ interactive = False,
293
+ visible=True,
294
+ )
295
+
296
+
297
+ hidden_leaderboard_table_for_search = gr.components.Dataframe(
298
+ value=df_results_init,
299
+ # value=df_results,
300
+ interactive=False,
301
+ visible=False,
302
+ )
303
+
304
+ search_bar.submit(
305
+ update_table,
306
+ [
307
+
308
+ hidden_leaderboard_table_for_search,
309
+ model1_column,
310
+ search_bar,
311
+ ],
312
+ leaderboard_table,
313
+ )
314
+
315
+ for selector in [model1_column]:
316
+ selector.change(
317
+ update_table,
318
+ [
319
+ hidden_leaderboard_table_for_search,
320
+ model1_column,
321
+ search_bar,
322
+ ],
323
+ leaderboard_table,
324
+ )
325
+
326
+ with gr.TabItem("πŸͺ‚ Object", elem_id="UnlearnDiffAtk-benchmark-tab-table", id=2):
327
+ files = ['church','garbage','parachute','tench']
328
  with gr.Row():
329
  with gr.Column():
330
  with gr.Row():
 
343
 
344
  for i in range(len(files)):
345
  if files[i] == "church":
346
+ name = "### [Unlearned Object]: "+" Church"
347
  csv_path = './assets/'+files[i]+'.csv'
348
  elif files[i] == 'garbage':
349
+ name = "### [Unlearned Object]: "+" Garbage"
350
  csv_path = './assets/'+files[i]+'.csv'
351
  elif files[i] == 'tench':
352
+ name = "### [Unlearned Object]: "+" Tench"
353
  csv_path = './assets/'+files[i]+'.csv'
354
  elif files[i] == 'parachute':
355
+ name = "### [Unlearned Object]: "+" Parachute"
356
  csv_path = './assets/'+files[i]+'.csv'
 
 
 
 
 
 
 
 
 
 
 
 
357
 
358
 
359
  gr.Markdown(name)