added sentiment analysis to the generated captions

added an api call that return the sentiment analysis (by "cardiffnlp/twitter-xlm-roberta-base-sentiment" )of the generated captions to the existing model. refined the text output.

app.py

@@ -1,18 +1,26 @@
 import gradio as gr
 from transformers import pipeline
+
 import warnings
 import logging
 warnings.simplefilter('ignore')
 logging.disable(logging.WARNING)
 
-cap = pipeline('image-to-text')
+model_path = "cardiffnlp/twitter-xlm-roberta-base-sentiment"
 
 
 def predict(image):
     cap = pipeline('image-to-text')
-    caption = cap(image)
-    output = str(caption)
-    return output[21:-4]
+    genereated_dict = cap(image)
+
+    final = str(genereated_dict)
+    def sentiment_analysis(phrase):
+      pipe = pipeline('text-classification')
+      sentiment = pipe(phrase)
+      return str(senti)
+    senti = sentiment_analysis(final)
+    output = final[20:-2]
+    return output
 
 
 input = gr.inputs.Image(
@@ -25,9 +33,8 @@ interface = gr.Interface(
     fn=predict,
     inputs=input,
     theme="grass",
-    outputs=output,
+    outputs= output,
     title=title,
-    flagging_options=["correct", "just okay", "wrong"],
 
 )
 interface.launch()