Update app.py

app.py

@@ -1,5 +1,4 @@
-import streamlit as st
-import numpy as np
+import gradio as gr
 import pandas as pd
 import similarSearch
 from PIL import Image
@@ -10,27 +9,24 @@ df = pd.read_csv('./gallery.csv')
 def find_similar_images(new_image):
     # Placeholder for your code to find similar image IDs based on the new_image
     similar_ids = similarSearch.predict(new_image)  # Replace with the actual logic for finding similar IDs
-    print(similar_ids)
     return similar_ids
 
 # Function to display images from their paths
 def display_images(image_ids):
+    images = []
     for img_id in image_ids:
         image_path = df.loc[df['seller_img_id'] == img_id, 'img_path'].values[0]
         image = Image.open(image_path)
-        st.image(image, caption=img_id, use_column_width=True)
+        images.append(image)
+    return images
 
-def main():
-    st.title('Image Similarity Finder')
-    st.write('Upload an image to find similar image IDs in the database.')
+iface = gr.Interface(
+    fn=find_similar_images, 
+    inputs=gr.inputs.Image(label="Upload Image"), 
+    outputs=gr.outputs.Image(label="Similar Image"),
+    title="Image Similarity Finder",
+    description="Upload an image to find similar image IDs in the database."
+)
 
-    uploaded_image_id = st.text_input('Enter Image ID', value='')
-
-    if st.button('Find Similar Images'):
-        similar_image_ids = find_similar_images(uploaded_image_id)
-        st.write('Similar Image IDs:', similar_image_ids)
-        st.write('Similar Images:')
-        display_images(similar_image_ids)
-
-if __name__ == '__main__':
-    main()
+if __name__ == "__main__":
+    iface.launch()