Update app.py

app.py

@@ -20,8 +20,8 @@ def predict(image,max_length=64, num_beams=4):
   clean_text = lambda x: x.replace('<|endoftext|>','').split('\n')[0]
   caption_ids = model.generate(image, max_length = max_length)[0]
   caption_text = clean_text(tokenizer.decode(caption_ids))
-  caption_text2 = generate_captions(image)
-  return caption_text, caption_text2
+  #caption_text2 = generate_captions(image)
+  return caption_text
 
 blip_processor_large = AutoProcessor.from_pretrained("Salesforce/blip-image-captioning-large")
 blip_model_large = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-large")
@@ -60,7 +60,6 @@ input = gr.inputs.Image(label="Upload your Image", type = 'pil', optional=True)
 #Two output boxes
 
 output_1 = gr.outputs.Textbox(type="text",label="Caption - 1")
-output_2 = gr.outputs.Textbox(type="text",label="Caption - 2")
 examples = [f"example{i}.png" for i in range(1,4)]
 
 description= "Image caption Generator"
@@ -72,7 +71,7 @@ interface = gr.Interface(
         fn=predict,
         inputs = input,
         theme="grass",
-        outputs = [output_1,output_2],
+        outputs = output_1,
         examples = examples,
         title=title,
         description=description,