| import streamlit as st
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| from PIL import Image
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| import requests
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| from io import BytesIO
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| from transformers import ViltProcessor, ViltForQuestionAnswering
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| st.set_page_config(layout="wide")
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|
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| processor = ViltProcessor.from_pretrained("dandelin/vilt-b32-finetuned-vqa")
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| model = ViltForQuestionAnswering.from_pretrained("dandelin/vilt-b32-finetuned-vqa")
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|
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| def get_answer(image, text):
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| try:
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|
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| img = Image.open(BytesIO(image)).convert("RGB")
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| encoding = processor(img, text, return_tensors="pt")
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| outputs = model(**encoding)
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| logits = outputs.logits
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| idx = logits.argmax(-1).item()
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| answer = model.config.id2label[idx]
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|
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| return answer
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|
|
| except Exception as e:
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| return str(e)
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| st.title("Visual Question Answering")
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| st.write("Upload an image and enter a question to get an answer.")
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| col1, col2 = st.columns(2)
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|
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| with col1:
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| uploaded_file = st.file_uploader("Upload Image", type=["jpg", "jpeg", "png"])
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| st.image(uploaded_file, use_column_width=True)
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| with col2:
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| question = st.text_input("Question")
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| if uploaded_file and question is not None:
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| if st.button("Ask Question"):
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| image = Image.open(uploaded_file)
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| image_byte_array = BytesIO()
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| image.save(image_byte_array, format='JPEG')
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| image_bytes = image_byte_array.getvalue()
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| answer = get_answer(image_bytes, question)
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| st.success("Answer: " + answer)
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