feat: add choose image feature

Dockerfile

@@ -19,5 +19,6 @@ RUN mkdir app
 WORKDIR $HOME/app
 COPY . $HOME/app
 
+RUN echo "hello world"
 EXPOSE 8501
 CMD streamlit run app.py

app.py

@@ -1,13 +1,16 @@
 import streamlit as st
 import streamlit.components.v1 as components
 from PIL import Image
+import requests
 
 from predict import generate_text
-from model import load_clip_model, load_gpt_model, load_model
+from model import load_model
+
+from streamlit_image_select import image_select
 
 
 # Configure Streamlit page
-st.set_page_config(page_title="Caption Machine", page_icon="💥")
+st.set_page_config(page_title="Caption Machine", page_icon="📸")
 
 # Set Session
 
@@ -42,24 +45,54 @@ st.markdown(
     "This app generates Image Caption using OpenAI's [GPT-2](https://openai.com/research/better-language-models) and [CLIP](https://openai.com/research/clip) model."
 )
 
-# st.subheader("Model Architecture")
 
-# image = Image.open('model.png')
 
-# st.image(image, caption=None, width=500)
+# Select image or upload image
+select_file = image_select(
+    label="Select a photo:",
+    images=[
+        "https://farm5.staticflickr.com/4084/5093294428_2f50d54acb_z.jpg",
+        "https://farm8.staticflickr.com/7044/6855243647_cd204d079c_z.jpg",
+        "http://farm4.staticflickr.com/3016/2650267987_f478c8d682_z.jpg",
+        "https://farm8.staticflickr.com/7249/6913786280_c145ecc433_z.jpg",
+    ],
+    # captions=["A cat", "Another cat", "Oh look, a cat!", "Guess what, a cat..."],
+)
+
+
 
 upload_file = st.file_uploader("Upload an image:", type=['png','jpg','jpeg'])
 
+st.divider()
 
 # Checking the Format of the page
-if upload_file is not None:
-    img = Image.open(upload_file)
+if upload_file or select_file:
+
+    img = None
+
+    if upload_file:
+        img = Image.open(upload_file)
+    
+    elif select_file:
+        st.text(select_file)
+        img = Image.open(requests.get(select_file, stream=True).raw)
+    
+    
     st.image(img)
-    st.write("Image Uploaded Successfully")
+    # st.write("Image Uploaded Successfully")
 
     # gpt_model, tokenizer = load_gpt_model()
-    caption = generate_text(st.session_state['model'], img, st.session_state['tokenizer'], st.session_state['image_transform'])
-
-    st.write(caption)
+    with st.spinner('Generating caption...'):
+        caption = generate_text(st.session_state['model'], img, st.session_state['tokenizer'], st.session_state['image_transform'])
+
+        st.success(f"Result: {caption}")
+    
+
+# Model information
+with st.expander("See model architecture"):
+    st.write("")
+    
+    model_img = Image.open('./model.png')
+    st.image(model_img, width=500)