import io import os import streamlit as st import requests from PIL import Image from model import get_caption_model, generate_caption @st.cache(allow_output_mutation=True) def get_model(): return get_caption_model() caption_model = get_model() def predict(): captions = [] pred_caption = generate_caption('tmp.jpg', caption_model) st.markdown('#### Predicted Captions:') captions.append(pred_caption) for _ in range(4): pred_caption = generate_caption('tmp.jpg', caption_model, add_noise=True) if pred_caption not in captions: captions.append(pred_caption) for c in captions: st.write(c) st.markdown('
OR
', unsafe_allow_html=True) img_upload = st.file_uploader(label='Upload Image', type=['jpg', 'png', 'jpeg']) if img_upload != None: img = img_upload.read() img = Image.open(io.BytesIO(img)) img = img.convert('RGB') img.save('tmp.jpg') st.image(img) predict() os.remove('tmp.jpg')