kokuma commited on
Commit
b1d7a57
·
verified ·
1 Parent(s): 2f402b2

Update app.py

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Files changed (1) hide show
  1. app.py +2 -17
app.py CHANGED
@@ -1073,7 +1073,7 @@ def select(idx, choice, correct, player_score, choices):
1073
  player_choice = choices[choice][0]
1074
  player_correct = choice == correct_value
1075
  player_score = player_score + int(player_correct)
1076
-
1077
  correct_text = gr.Text(
1078
  f"Correct was: '{correct_name}'. Question {idx+1}/{len(babel_imagenet['EN'][0])} ",
1079
  label="Game",
@@ -1111,15 +1111,12 @@ def prepare(raw_idx, class_order):
1111
  ) # precomputing script uses torch.topk which sorts in reverse here
1112
  if idx not in choices:
1113
  choices = [idx] + choices[1:]
1114
- # model_choice_idx = choices[-1]
1115
 
1116
  numpy.random.shuffle(choices)
1117
 
1118
  choice_names = [class_labels[idx] for idx in choices]
1119
  choice_values = [0, 1, 2, 3]
1120
 
1121
- # model_choice_idx = choices.index(model_choice_idx)
1122
- # model_choice = [choice_names[model_choice_idx], choice_values[model_choice_idx]]
1123
  correct_choice_idx = choices.index(idx)
1124
  correct_choice = [
1125
  choice_names[correct_choice_idx],
@@ -1158,8 +1155,7 @@ def prepare(raw_idx, class_order):
1158
  next_image,
1159
  raw_idx,
1160
  correct_choice,
1161
- # model_choice,
1162
- new_choice_values,
1163
  )
1164
 
1165
 
@@ -1168,13 +1164,10 @@ with gr.Blocks(title="Babel-ImageNet Quiz", css=css) as demo:
1168
  # setup state
1169
  class_idx = gr.State(-1)
1170
  player_score = gr.State(0)
1171
- # clip_score = gr.State(0)
1172
  class_order = gr.State([])
1173
  choices = gr.State([])
1174
 
1175
- # text_embeddings = gr.State(None)
1176
  correct_choice = gr.State(["nan", 0]) # 0, 1, 2, 3
1177
- # model_choice = gr.State(["nan", 0])
1178
 
1179
  # Title Area
1180
  gr.Markdown(
@@ -1213,17 +1206,13 @@ with gr.Blocks(title="Babel-ImageNet Quiz", css=css) as demo:
1213
  class_idx,
1214
  options,
1215
  correct_choice,
1216
- # model_choice,
1217
  player_score,
1218
- # clip_score,
1219
  choices,
1220
  ],
1221
  outputs=[
1222
  correct_text,
1223
  player_score_text,
1224
- # clip_score_text,
1225
  player_score,
1226
- # clip_score,
1227
  ],
1228
  ).then(
1229
  fn=prepare,
@@ -1238,20 +1227,16 @@ with gr.Blocks(title="Babel-ImageNet Quiz", css=css) as demo:
1238
  fn=change_language,
1239
  inputs=[],
1240
  outputs=[
1241
- # text_embeddings,
1242
  class_idx,
1243
  class_order,
1244
  correct_text,
1245
  player_score_text,
1246
- # clip_score_text,
1247
  player_score,
1248
- # clip_score,
1249
  ],
1250
  ).then(
1251
  fn=prepare,
1252
  inputs=[
1253
  class_idx,
1254
- # text_embeddings,
1255
  class_order,
1256
  ],
1257
  outputs=[options, image, class_idx, correct_choice, choices],
 
1073
  player_choice = choices[choice][0]
1074
  player_correct = choice == correct_value
1075
  player_score = player_score + int(player_correct)
1076
+
1077
  correct_text = gr.Text(
1078
  f"Correct was: '{correct_name}'. Question {idx+1}/{len(babel_imagenet['EN'][0])} ",
1079
  label="Game",
 
1111
  ) # precomputing script uses torch.topk which sorts in reverse here
1112
  if idx not in choices:
1113
  choices = [idx] + choices[1:]
 
1114
 
1115
  numpy.random.shuffle(choices)
1116
 
1117
  choice_names = [class_labels[idx] for idx in choices]
1118
  choice_values = [0, 1, 2, 3]
1119
 
 
 
1120
  correct_choice_idx = choices.index(idx)
1121
  correct_choice = [
1122
  choice_names[correct_choice_idx],
 
1155
  next_image,
1156
  raw_idx,
1157
  correct_choice,
1158
+ choice_values,
 
1159
  )
1160
 
1161
 
 
1164
  # setup state
1165
  class_idx = gr.State(-1)
1166
  player_score = gr.State(0)
 
1167
  class_order = gr.State([])
1168
  choices = gr.State([])
1169
 
 
1170
  correct_choice = gr.State(["nan", 0]) # 0, 1, 2, 3
 
1171
 
1172
  # Title Area
1173
  gr.Markdown(
 
1206
  class_idx,
1207
  options,
1208
  correct_choice,
 
1209
  player_score,
 
1210
  choices,
1211
  ],
1212
  outputs=[
1213
  correct_text,
1214
  player_score_text,
 
1215
  player_score,
 
1216
  ],
1217
  ).then(
1218
  fn=prepare,
 
1227
  fn=change_language,
1228
  inputs=[],
1229
  outputs=[
 
1230
  class_idx,
1231
  class_order,
1232
  correct_text,
1233
  player_score_text,
 
1234
  player_score,
 
1235
  ],
1236
  ).then(
1237
  fn=prepare,
1238
  inputs=[
1239
  class_idx,
 
1240
  class_order,
1241
  ],
1242
  outputs=[options, image, class_idx, correct_choice, choices],