Spaces:
Sleeping
Sleeping
File size: 843 Bytes
ad47766 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 |
import streamlit as st
from transformers import pipline
pipe = pipeline("image-to-text", model="Salesforce/blip2-opt-2.7b")
def answer_question(image, question):
# Integrate your model logic here
answer = "This is where the answer will appear."
return answer
st.title("Image Question Answering")
# File uploader for the image
image = st.file_uploader("Upload an image", type=["png", "jpg", "jpeg"])
# Text input for the question
question = st.text_input("Enter your question about the image:")
if st.button("Get Answer"):
if image is not None and question:
# Display the image
st.image(image, use_column_width=True)
# Get and display the answer
answer = answer_question(image, question)
st.write(answer)
else:
st.write("Please upload an image and enter a question.")
|