Update app.py

app.py

@@ -1145,10 +1145,8 @@ def prepare(raw_idx, text_embeddings, class_order):
     keep = random.choice(other_choices)
     new_choice_values = [correct_tuple, keep]
     random.shuffle(new_choice_values)
-    
-    warnings.warn(f"correct_choice: {correct_choice}")
-    warnings.warn(f"choice_values: {choice_values}")
-    warnings.warn(f"correct_choice: {new_choice_values}")
+
+    warnings.warn(f"model_choice: {model_choice}\n\n")
 
     next_radio = gr.Radio(
         choices=choice_values,
@@ -1163,60 +1161,7 @@ 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, choice_values
-
-
-# def reroll(raw_idx, text_embeddings, class_order):
-#     #  prepared next question, loads image, and computes choices
-
-#     idx = class_order[raw_idx]
-#     lang_class_idxs = babel_imagenet["EN"][0]
-#     class_idx = lang_class_idxs[idx]
-
-#     img_idx = 0
-#     img_idx = np.random.choice(min(len(babelnet_images[class_idx]), max_image_choices))
-#     img_url = babelnet_images[class_idx][img_idx]["url"]
-#     class_labels = openai_en_classes
-
-#     choices = list(
-#         reversed(precomputed_results["EN"][idx][img_idx])
-#     )  # precomputing script uses torch.topk which sorts in reverse here
-#     if idx not in choices:
-#         choices = [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]]
-#     correct_choice_idx = choices.index(idx)
-#     correct_choice = [
-#         choice_names[correct_choice_idx],
-#         choice_values[correct_choice_idx],
-#     ]
-
-#     choice_values = list(zip(choice_names, choice_values))
-
-#     warnings.warn(f"reroll correct_choice: {correct_choice}")
-#     warnings.warn(f"reroll choice_values: {choice_values}")
-
-#     next_radio = gr.Radio(
-#         choices=choice_values,
-#         interactive=True,
-#         label="Select the correct answer:",
-#         value=None,
-#     )
-#     next_image = gr.Image(
-#         value=img_url,
-#         width=IMG_WIDTH,
-#         height=IMG_WIDTH,
-#         label="What class does this image belong to?",
-#     )
-
-#     return next_radio, next_image, raw_idx, correct_choice, model_choice, 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:
@@ -1256,13 +1201,12 @@ with gr.Blocks(title="Babel-ImageNet Quiz", css=css) as demo:
                 choices=["Click", "start"],
                 interactive=False,
                 label="Please click start to begin.",
-                elem_classes="choices-group"
+                elem_classes="choices-group",
             )
             # 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")
-            # reroll_btn = gr.Button(value="Reroll the image (for bad images or errors)")
 
     options.select(
         fn=select,
@@ -1315,14 +1259,5 @@ with gr.Blocks(title="Babel-ImageNet Quiz", css=css) as demo:
         outputs=[options, image, class_idx, correct_choice, model_choice, choices],
     )
 
-    # reroll_btn.click(
-    #     fn=reroll,
-    #     inputs=[
-    #         class_idx,
-    #         text_embeddings,
-    #         class_order,
-    #     ],
-    #     outputs=[options, image, class_idx, correct_choice, model_choice, choices],
-    # )
 
-demo.launch()
+demo.launch()