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import glob | |
import streamlit as st | |
from streamlit_image_select import image_select | |
import streamlit.components.v1 as components | |
# Trick to not init function multitime | |
if "model" not in st.session_state: | |
print("INIT MODEL") | |
from src.model import Model | |
st.session_state.model = Model() | |
print("DONE INIT MODEL") | |
st.set_page_config(page_title="VQA", layout="wide") | |
hide_menu_style = """ | |
<style> | |
footer {visibility: hidden;} | |
</style> | |
""" | |
st.markdown(hide_menu_style, unsafe_allow_html=True) | |
mapper = { | |
"images/000000000645.jpg": "Đây là đâu", | |
"images/000000000661.jpg": "Tốc độ tối đa trên đoạn đường này là bao nhiêu", | |
"images/000000000674.jpg": "Còn bao xa nữa là tới Huế", | |
"images/000000000706.jpg": "Cầu này dài bao nhiêu", | |
"images/000000000777.jpg": "Chè khúc bạch giá bao nhiêu", | |
} | |
image = st.file_uploader( | |
"Choose an image file", | |
type=[ | |
"jpg", | |
"jpeg", | |
"png", | |
"webp", | |
], | |
) | |
example = image_select("Examples", glob.glob("images/*.jpg")) | |
if image: | |
bytes_data = image.getvalue() | |
with open("test.png", "wb") as f: | |
f.write(bytes_data) | |
f.close() | |
st.session_state.image = "test.png" | |
st.session_state.question = "" | |
else: | |
st.session_state.question = mapper[example] | |
st.session_state.image = example | |
if "image" in st.session_state: | |
st.image(st.session_state.image) | |
question = st.text_input("**Question:** ", value=st.session_state.question) | |
visualize = True | |
if question: | |
answer, text_attention_html, images_visualize = ( | |
st.session_state.model.inference( | |
st.session_state.image, question, visualize | |
) | |
) | |
st.write(f"**Answer:** {answer}") | |
if visualize: | |
st.write("**Explanation**") | |
col1, col2 = st.columns([1, 2]) | |
# st.markdown(text_attention_html, unsafe_allow_html=True) | |
with col1: | |
st.write("*Text Attention*") | |
components.html(text_attention_html, height=960, scrolling=True) | |
with col2: | |
st.write("*Image Attention*") | |
for image_visualize in images_visualize: | |
st.image(image_visualize) | |