Update app.py

app.py

@@ -1046,42 +1046,34 @@ request_header = {
 }
 
 
-def change_language(randomize_imgs, randomize_labels):
+def change_language():
     # compute text embeddings
     labels = babel_imagenet["EN"][1]
     class_order = list(range(len(labels)))
     np.random.shuffle(class_order)
-    text_features = None
     correct_text = gr.Text(
         f"Correct was: ''. Question 1/{len(babel_imagenet['EN'][0])} ", label="Game"
     )
     player_score_text = gr.Text(f"Your choice: (Score: 0) ", label="Player")
-    clip_score_text = gr.Text(f"mSigLIP chose: '' (Score: 0)", label="Opponent")
+    # clip_score_text = gr.Text(f"mSigLIP chose: '' (Score: 0)", label="Opponent")
 
     return (
-        text_features,
         -1,
         class_order,
         correct_text,
         player_score_text,
-        clip_score_text,
-        0,
+        # clip_score_text,
+        # 0,
         0,
     )
 
 
-def select(idx, choice, correct, model_choice, player_score, clip_score, choices):
-    # checks if answer choice is correct and updated scores
+def select(idx, choice, correct, player_score, choices):
     correct_name, correct_value = correct
-    model_choice_name, model_choice_value = model_choice
     player_choice = choices[choice][0]
-
     player_correct = choice == correct_value
-    model_correct = model_choice_value == correct_value
-
     player_score = player_score + int(player_correct)
-    clip_score = clip_score + int(model_correct)
-
+    
     correct_text = gr.Text(
         f"Correct was: '{correct_name}'. Question {idx+1}/{len(babel_imagenet['EN'][0])} ",
         label="Game",
@@ -1090,15 +1082,11 @@ def select(idx, choice, correct, model_choice, player_score, clip_score, choices
         f"Your choice: {player_choice} {'✅' if player_correct else '❌'} (Score: {player_score}) ",
         label="Player",
     )
-    clip_score_text = gr.Text(
-        f"mSigLIP chose: '{model_choice_name}' {'✅' if model_correct else '❌'} (Score: {clip_score})",
-        label="Opponent",
-    )
 
-    return correct_text, player_score_text, clip_score_text, player_score, clip_score
+    return correct_text, player_score_text, player_score
 
 
-def prepare(raw_idx, text_embeddings, class_order):
+def prepare(raw_idx, class_order):
     #  prepared next question, loads image, and computes choices
 
     raw_idx = (raw_idx + 1) % len(babel_imagenet["EN"][0])
@@ -1123,15 +1111,15 @@ def prepare(raw_idx, text_embeddings, class_order):
     )  # precomputing script uses torch.topk which sorts in reverse here
     if idx not in choices:
         choices = [idx] + choices[1:]
-    model_choice_idx = choices[-1]
+    # model_choice_idx = choices[-1]
 
     numpy.random.shuffle(choices)
 
     choice_names = [class_labels[idx] for idx in choices]
     choice_values = [0, 1, 2, 3]
 
-    model_choice_idx = choices.index(model_choice_idx)
-    model_choice = [choice_names[model_choice_idx], choice_values[model_choice_idx]]
+    # model_choice_idx = choices.index(model_choice_idx)
+    # model_choice = [choice_names[model_choice_idx], choice_values[model_choice_idx]]
     correct_choice_idx = choices.index(idx)
     correct_choice = [
         choice_names[correct_choice_idx],
@@ -1146,7 +1134,11 @@ def prepare(raw_idx, text_embeddings, class_order):
     new_choice_values = [correct_tuple, keep]
     random.shuffle(new_choice_values)
 
-    warnings.warn(f"model_choice: {model_choice}\n\n")
+    warnings.warn(
+        f"""\
+    choices: {choices}\n\n
+    correct_choice: {correct_choice}\n\n"""
+    )
 
     next_radio = gr.Radio(
         choices=new_choice_values,
@@ -1161,7 +1153,14 @@ def prepare(raw_idx, text_embeddings, class_order):
         label="What class does this image belong to?",
     )
 
-    return next_radio, next_image, raw_idx, correct_choice, model_choice, new_choice_values
+    return (
+        next_radio,
+        next_image,
+        raw_idx,
+        correct_choice,
+        # model_choice,
+        new_choice_values,
+    )
 
 
 with gr.Blocks(title="Babel-ImageNet Quiz", css=css) as demo:
@@ -1169,13 +1168,13 @@ with gr.Blocks(title="Babel-ImageNet Quiz", css=css) as demo:
     # setup state
     class_idx = gr.State(-1)
     player_score = gr.State(0)
-    clip_score = gr.State(0)
+    # clip_score = gr.State(0)
     class_order = gr.State([])
     choices = gr.State([])
 
-    text_embeddings = gr.State(None)
+    # text_embeddings = gr.State(None)
     correct_choice = gr.State(["nan", 0])  # 0, 1, 2, 3
-    model_choice = gr.State(["nan", 0])
+    # model_choice = gr.State(["nan", 0])
 
     # Title Area
     gr.Markdown(
@@ -1206,7 +1205,7 @@ with gr.Blocks(title="Babel-ImageNet Quiz", css=css) as demo:
             # with gr.Row():
             correct_text = gr.Text("Please click start to begin.")
             player_score_text = gr.Text(f"Player score: 0")
-            clip_score_text = gr.Text(f"mSigLIP score: 0")
+            # clip_score_text = gr.Text(f"mSigLIP score: 0")
 
     options.select(
         fn=select,
@@ -1214,49 +1213,48 @@ with gr.Blocks(title="Babel-ImageNet Quiz", css=css) as demo:
             class_idx,
             options,
             correct_choice,
-            model_choice,
+            # model_choice,
             player_score,
-            clip_score,
+            # clip_score,
             choices,
         ],
         outputs=[
             correct_text,
             player_score_text,
-            clip_score_text,
+            # clip_score_text,
             player_score,
-            clip_score,
+            # clip_score,
         ],
     ).then(
         fn=prepare,
         inputs=[
             class_idx,
-            text_embeddings,
             class_order,
         ],
-        outputs=[options, image, class_idx, correct_choice, model_choice, choices],
+        outputs=[options, image, class_idx, correct_choice, choices],
     )
 
     start_btn.click(
         fn=change_language,
         inputs=[],
         outputs=[
-            text_embeddings,
+            # text_embeddings,
             class_idx,
             class_order,
             correct_text,
             player_score_text,
-            clip_score_text,
+            # clip_score_text,
             player_score,
-            clip_score,
+            # clip_score,
         ],
     ).then(
         fn=prepare,
         inputs=[
             class_idx,
-            text_embeddings,
+            # text_embeddings,
             class_order,
         ],
-        outputs=[options, image, class_idx, correct_choice, model_choice, choices],
+        outputs=[options, image, class_idx, correct_choice, choices],
     )