Update app.py

app.py

@@ -1,7 +1,21 @@
 import gradio as gr
-from transformers import pipeline
+import requests
+from PIL import Image
+from transformers import BlipProcessor, BlipForConditionalGeneration
 
-caption = pipeline("image-to-text", model="Salesforce/blip-image-captioning-large")
+processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-large")
+model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-large")
+
+img_url = 'https://storage.googleapis.com/sfr-vision-language-research/BLIP/demo.jpg' 
+raw_image = Image.open(requests.get(img_url, stream=True).raw).convert('RGB')
+
+def caption(img):
+    raw_image = Image.open(img).convert('RGB')
+  
+    inputs = processor(raw_image, return_tensors="pt")
+    
+    out = model.generate(**inputs, min_length=30, max_length=1000)
+    return processor.decode(out[0], skip_special_tokens=True)
 
 def greet(img):
     return caption(img)