Update app.py

app.py

@@ -66,7 +66,7 @@ def generate_questions(context, answer):
         'question: ', ' ') for g in generated_ids]
     return questions
 
-# Define the Gradio interface with Seafoam theme
+# Interface
 class Seafoam(Base):
     pass
 
@@ -76,7 +76,7 @@ def caption_question_interface(image):
     # Generate captions
     captions = generate_captions(image)
 
-    # Correct captions using the dictionary
+    # Proofread captions using the dictionary
     corrected_captions = [correct_caption(caption) for caption in captions]
 
     # Generate questions for each caption
@@ -85,32 +85,32 @@ def caption_question_interface(image):
         words = caption.split()
         # Generate questions for the first word
         if len(words) > 0:
-            answer = words[0]
-            question = generate_questions(caption, answer)
-            questions_with_answers.extend([(q, answer) for q in question])
+            keyword = words[0]
+            question = generate_questions(caption, keyword)
+            questions_with_keywords.extend([(q, keyword) for q in question])
         # Generate questions for the second word
         if len(words) > 1:
-            answer = words[1]
-            question = generate_questions(caption, answer)
-            questions_with_answers.extend([(q, answer) for q in question])
+            keyword = words[1]
+            question = generate_questions(caption, keyword)
+            questions_with_keywords.extend([(q, keyword) for q in question])
         # Generate questions for the second word + first word
         if len(words) > 1:
-            answer = " ".join(words[:2])
-            question = generate_questions(caption, answer)
-            questions_with_answers.extend([(q, answer) for q in question])
+            keyword = " ".join(words[:2])
+            question = generate_questions(caption, keyword)
+            questions_with_keywords.extend([(q, keyword) for q in question])
         # Generate questions for the third word
         if len(words) > 2:
-            answer = words[2]
-            question = generate_questions(caption, answer)
-            questions_with_answers.extend([(q, answer) for q in question])
+            keyword = words[2]
+            question = generate_questions(caption, keyword)
+            questions_with_keywords.extend([(q, keyword) for q in question])
         # Generate questions for the fourth word
         if len(words) > 3:
-            answer = words[3]
-            question = generate_questions(caption, answer)
-            questions_with_answers.extend([(q, answer) for q in question])
+            keyword = words[3]
+            question = generate_questions(caption, keyword)
+            questions_with_answers.extend([(q, keyword) for q in question])
 
     # Format questions with answers
-    formatted_questions = [f"Question: {q}\nAnswer: {a}" for q, a in questions_with_answers]
+    formatted_questions = [f"Question: {q}\nKeyword: {a}" for q, a in questions_with_keywords]
     formatted_questions = "\n".join(formatted_questions)
 
     # Return the generated captions and formatted questions with answers
@@ -121,9 +121,9 @@ gr_interface = gr.Interface(
     inputs=gr.Image(type="pil", label="Input Image"), 
     outputs=[
         gr.Textbox(label="Generated Captions"), 
-        gr.Textbox(label="Generated Questions and Answers")
+        gr.Textbox(label="Generated Questions")
     ],
-    title="Image Captioning and Question Generation",
+    title="Visual Question Generator",
     description="Generate captions and questions for images using pre-trained models.",
     theme=seafoam,
 )