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import io
import os
import streamlit as st
import requests
from PIL import Image
from model import get_caption_model, generate_caption
@st.cache_resource(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.title('Image Captioner')
img_url = st.text_input(label='Enter Image URL')
if (img_url != "") and (img_url != None):
img = Image.open(requests.get(img_url, stream=True).raw)
img = img.convert('RGB')
st.image(img)
img.save('tmp.jpg')
predict()
os.remove('tmp.jpg')
st.markdown('<center style="opacity: 70%">OR</center>', 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')
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