Update app.py

app.py

@@ -3,9 +3,11 @@ import glob
 import torch
 import streamlit as st
 import numpy as np
+import base64
 from PIL import Image, ImageDraw
 from transformers import pipeline
 from tempfile import NamedTemporaryFile
+from st_clickable_images import clickable_images
 
 st.set_page_config(layout="wide")
 
@@ -16,6 +18,7 @@ st.title('Upload an image file to detection')
 col1, col2, col3 = st.columns([0.5, 0.3, 0.2])
 
 gibsOk = False
+totalGibs = 0
 with col1:
 
     st.header('flyer')
@@ -54,6 +57,7 @@ with col1:
                 cv2.imwrite("/tmp/cropped_image_{}.jpg".format(i), crop_img)
                 i += 1
 
+        totalGibs = i
         gibsOk = True
         imageLocation.image(image)
         st.write(predictions)
@@ -62,5 +66,15 @@ with col2:
     st.header('gibs')
     images = []
     for cropped in glob.glob('/tmp/cropped_image_*'):
-        st.write(cropped)
+        with open(cropped, "rb") as image:
+            encoded = base64.b64encode(image.read()).decode()
+            images.append(f"data:image/jpeg;base64,{encoded}")
+    clicked = clickable_images(
+        images,
+        titles=[f"Image #{str(i)}" for i in range(totalGibs)],
+        div_style={"display": "flex", "justify-content": "center", "flex-wrap": "wrap"},
+        img_style={"margin": "5px", "height": "150px"},
+    )
+
+    st.markdown(f"Image #{clicked} clicked" if clicked > -1 else "No image clicked")