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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") | |