commit

app.py

@@ -21,14 +21,27 @@ 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(decoded_caption, return_tensors="pt")
+    emotion_inputs = emotion_tokenizer.encode_plus(
+        decoded_caption,
+        max_length=128,
+        padding="max_length",
+        truncation=True,
+        return_tensors="pt"
+    )
     emotion_outputs = emotion_model(**emotion_inputs)
 
     # Get the predicted emotion label
     emotion_label = emotion_tokenizer.decode(emotion_outputs.logits.argmax())
 
+    # 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}"
     return final_output