Create app.py

app.py

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+import requests
+from PIL import Image
+from transformers import BlipProcessor, BlipForConditionalGeneration
+import streamlit as st
+
+processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-large")
+model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-large")
+
+file_name = st.file_uploader()
+
+# conditional image captioning
+text = "Create a poem from this image"
+inputs = processor(raw_image, text, return_tensors="pt")
+
+out = model.generate(**inputs)
+print(processor.decode(out[0], skip_special_tokens=True))