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import io |
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import os |
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import streamlit as st |
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import requests |
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from PIL import Image |
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from model import get_caption_model, generate_caption |
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from googletrans import Translator |
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translator = Translator() |
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@st.cache_resource |
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def get_model(): |
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return get_caption_model() |
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caption_model = get_model() |
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def translate_caption(caption, target_language='en'): |
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translated = translator.translate(caption, dest=target_language) |
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return translated.text |
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def predict(cap_col): |
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captions = [] |
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pred_caption = generate_caption('tmp.jpg', caption_model) |
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cap_col.markdown('#### Predicted Captions:') |
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translated_caption = translate_caption(pred_caption, target_language) |
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captions.append(translated_caption) |
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for _ in range(4): |
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pred_caption = generate_caption('tmp.jpg', caption_model, add_noise=True) |
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if pred_caption not in captions: |
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translated_caption = translate_caption(pred_caption, target_language) |
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captions.append(translated_caption) |
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cap_col.markdown('<div class="caption-container">', unsafe_allow_html=True) |
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for c in captions: |
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cap_col.markdown(f'<div class="cap-line" style="color: black; background-color: light grey; padding: 5px; margin-bottom: 5px; font-family: \'Palatino Linotype\', \'Book Antiqua\', Palatino, serif;">{c}</div>', unsafe_allow_html=True) |
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cap_col.markdown('</div>', unsafe_allow_html=True) |
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st.markdown('<h1 style="text-align:center; font-family:Arial; width:fit-content; font-size:3em; color:black; text-shadow: 2px 2px 4px #000000;">IMAGE CAPTION GENERATOR</h1>', unsafe_allow_html=True) |
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col1, col2 = st.columns(2) |
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img_url = st.text_input(label='Enter Image URL') |
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img_upload = st.file_uploader(label='Upload Image', type=['jpg', 'png', 'jpeg']) |
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target_language = st.selectbox('Select Target Language', ['en', 'ta', 'hi', 'es', 'fr', 'zh-cn'], index=0) |
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if img_url: |
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img = Image.open(requests.get(img_url, stream=True).raw) |
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img = img.convert('RGB') |
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col1.image(img, caption="Input Image", use_column_width=True) |
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img.save('tmp.jpg') |
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predict(col2) |
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st.markdown('<center style="opacity: 70%">OR</center>', unsafe_allow_html=True) |
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elif img_upload: |
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img = img_upload.read() |
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img = Image.open(io.BytesIO(img)) |
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img = img.convert('RGB') |
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col1.image(img, caption="Input Image", use_column_width=True) |
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img.save('tmp.jpg') |
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predict(col2) |
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if img_url or img_upload: |
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os.remove('tmp.jpg') |
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