commit

app.py

@@ -21,9 +21,6 @@ def generate_caption_and_analyze_emotions(image):
     # Decode the output caption
     decoded_caption = caption_processor.decode(caption[0], skip_special_tokens=True)
 
-    # Debug print for the raw output caption
-    print("Raw Generated Caption:", decoded_caption)
-
     # Analyze emotions of the generated caption
     # Preprocess the caption for emotion analysis
     emotion_inputs = emotion_tokenizer.encode_plus(
@@ -36,11 +33,9 @@ def generate_caption_and_analyze_emotions(image):
     emotion_outputs = emotion_model(**emotion_inputs)
 
     # Get the predicted emotion label
-    emotion_label = emotion_tokenizer.decode(emotion_outputs.logits.argmax())
+    emotion_label_id = emotion_outputs.logits.argmax().item()
+    emotion_label = emotion_tokenizer.decode(emotion_label_id)
 
-    # Debug print for caption and emotion label
-    #print("Generated Caption:", decoded_caption)
-    #print("Predicted Emotion Label:", emotion_label)
 
     # Prepare the final output with sentiment information
     final_output = f"The sentiment in the provided image shows: {emotion_label}.\n\nGenerated Caption: {decoded_caption}"