finished app no frills

app.py

@@ -95,18 +95,35 @@ def train_and_inference(api_key, ontology_id, model_run_id):
     import requests
     import os
 
-    def download_and_save_image(url, destination_folder, filename):
+    import os
+import requests
+from urllib.parse import unquote
+
+def download_and_save_image(url, destination_folder, filename):
+    try:
+        # Decode the URL
+        url = unquote(url)
+
+        # Ensure destination directory exists
         if not os.path.exists(destination_folder):
             os.makedirs(destination_folder)
 
+        # Start the download process
         response = requests.get(url, stream=True)
-        response.raise_for_status()
-        st.write(url)
 
-        with open(os.path.join(destination_folder, filename), 'wb') as file:
-            for chunk in response.iter_content(8192):
-                file.write(chunk)
-        file.close()
+        # Check if the request was successful
+        if response.status_code == 200:
+            file_path = os.path.join(destination_folder, filename)
+            with open(file_path, 'wb') as file:
+                for chunk in response.iter_content(8192):
+                    file.write(chunk)
+            st.write(f"Image downloaded and saved: {file_path}")
+        else:
+            st.write(f"Failed to download the image. Status code: {response.status_code}")
+    except Exception as e:
+        st.write(f"An error occurred: {e}")
+
+
 
     BASE_DIR = 'dataset'