Update app.py

app.py

@@ -126,22 +126,24 @@ def main():
             start_index = (tabs - 1) * images_per_page
             end_index = min(start_index + images_per_page, length)
 
-            # Loop through each similar image
-            for index in range(start_index, end_index):
-                img_id = similar_images[index]
-                img_path = df.loc[df['seller_img_id'] == img_id, 'img_path'].values[0]
-                product_id = df.loc[df['seller_img_id'] == img_id, 'product_id'].values[0]
-
-                # Construct the full path to the image
-                full_img_path = img_path
-
-                # Open and resize the image to the desired dimensions
-                image = image_open(full_img_path)
-                resized_image = cv2.resize(image, (image_width, image_height))
-
-                # Determine the column to place the image in
-                col_index = index % num_columns
-                st.image(resized_image, caption=f'Product ID: {product_id}\nImage ID: {img_id}', width=image_width)
+            for img_id in similar_images:
+                row = df[df['seller_img_id'] == img_id]
+                if not row.empty:
+                    img_path = row['img_path'].values[0]
+                    product_id = row['product_id'].values[0]
+        
+                    # Construct the full path to the image
+                    full_img_path = img_path
+
+                    # Open and resize the image to the desired dimensions
+                    image = read_image(full_img_path)
+                    resized_image = cv2.resize(image, (image_width, image_height))
+
+                    # Determine the column to place the image in
+                    col_index = index % num_columns
+                    st.image(resized_image, caption=f'Product ID: {product_id}\nImage ID: {img_id}', width=image_width)
+                else:
+                    st.write(f"Could not find details for image with ID: {img_id}")
         
 
 if __name__ == '__main__':