app.py

app.py

@@ -0,0 +1,53 @@
+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.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')