Upload 2 files

app.py

@@ -0,0 +1,39 @@
+import streamlit as st
+from PIL import Image
+from transformers import BlipProcessor, BlipForConditionalGeneration
+import requests
+from io import BytesIO
+
+# Load model and processor
+processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
+model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base")
+
+def generate_caption(image):
+    inputs = processor(image, return_tensors="pt")
+    out = model.generate(**inputs)
+    return processor.decode(out[0], skip_special_tokens=True)
+
+st.title("Image Captioning")
+
+# URL input
+url = st.text_input("Enter image URL (optional):")
+if url:
+    try:
+        response = requests.get(url)
+        image = Image.open(BytesIO(response.content)).convert("RGB")
+        st.image(image, caption="Image from URL", use_column_width=True)
+        caption = generate_caption(image)
+        st.write(f"Caption: {caption}")
+    except Exception as e:
+        st.error(f"Error fetching image from URL: {e}")
+
+# File upload
+uploaded_file = st.file_uploader("Upload an image file (optional):", type=["jpg", "jpeg", "png"])
+if uploaded_file:
+    image = Image.open(uploaded_file).convert("RGB")
+    st.image(image, caption="Uploaded Image", use_column_width=True)
+    caption = generate_caption(image)
+    st.write(f"Caption: {caption}")
+
+if not url and not uploaded_file:
+    st.write("Please enter an image URL or upload an image file to get a caption.")

requirements.txt

@@ -0,0 +1,4 @@
+transformers
+torch
+pillow
+streamlit