Add ML model some depen and streamlit file

README.md

@@ -1,13 +1,12 @@
 ---
-title: Saw And Tell
-emoji: 📊
+title: Image Captioning
+emoji: 🦀
 colorFrom: red
-colorTo: yellow
+colorTo: gray
 sdk: streamlit
-sdk_version: 1.17.0
+sdk_version: 1.10.0
 app_file: app.py
 pinned: false
-license: apache-2.0
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

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')

requirements.txt

@@ -0,0 +1,7 @@
+numpy==1.22.3
+pandas==1.4.3
+pandas_stubs==1.2.0.56
+Pillow==9.2.0
+requests==2.27.1
+streamlit==1.11.1
+tensorflow==2.9.1