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import streamlit as st
from PIL import Image
import requests
from io import BytesIO
from transformers import ViltProcessor, ViltForQuestionAnswering
st.set_page_config(layout='wide',page_title='VQA')
#Vilt model
processor = ViltProcessor.from_pretrained("dandelin/vilt-b32-finetuned-vqa")
model =ViltForQuestionAnswering.from_pretrained("dandelin/vilt-b32-finetuned-vqa")
def get_answer(image,text):
try:
#load and process the image
img = Image.open(BytesIO(image)).convert('RGB')
encoding = processor(img,text,return_tensors="pt")
#forward pass
outputs = model(**encoding)
logits = outputs.logits
idx = logits.argmax(-1).item()
answer = model.config.id2label[idx]
return answer
except Exception as e:
return str(e)
st.title("Visual Question Answering App")
st.write("Update an image and enter qustion to get and answer")
st.caption("Sample image...")
st.image("tulips.jpg",width=600)
col1,col2 = st.columns(2)
with col1:
uploaded_file = st.file_uploader("Upload your own image or simply drag sample image given above",type=['jpg','png','jpeg'])
st.image(uploaded_file,use_column_width=True)
with col2:
question = st.text_input("Question")
#st.text(question)
if uploaded_file and question is not None:
if st.button("Ask Question"):
image = Image.open(uploaded_file)
image_byte_array = BytesIO()
image.save(image_byte_array,format="JPEG")
image_bytes = image_byte_array.getvalue()
#st.show(answer)
st.info("Your Question is ..." + question)
answer = get_answer(image_bytes,question)
if answer is not None:
#st.text(answer)
st.info("Answer is ..."+ answer)
else:
st.text("Sorry I am not able to answer that question")
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