added comments

app.py

@@ -2,20 +2,30 @@ import gradio as gr
 import os
 from SolarPanelDetector import solar_panel_predict, detector
 
+# Custom CSS for styling the app
 custom_css = """
 .feedback textarea {font-size: 20px !important;}
 .centered-text {text-align: center; width: 100%;}
 .center-image {display: flex; justify-content: center; align-items: center;}
 """
+# URL for the logo image
 logo_url = 'https://raw.githubusercontent.com/ArielDrabkin/Solar-Panel-Detector/master/deployment/examples/DALL-E.jpeg'
 
+# Starting Gradio app configuration
 with gr.Blocks(theme="HaleyCH/HaleyCH_Theme", title="Solar Panel Detector", css=custom_css) as app:
+    # Main title for the app
     gr.Markdown("# **Solar Panel Detector 2.0** 🛰️☀️", elem_classes="centered-text")
+
+    # Displaying the logo
     with gr.Row(elem_classes="center-image"):
         gr.Image(logo_url, scale=1, height=450, width=700, show_label=False, show_download_button=False,
                  show_share_button=False)
-    gr.Markdown("## This app provides the ability to detect solar panels in a given address or a given satellite image.")
 
+    # Description for using the app with address and Google Maps API
+    gr.Markdown(
+        "## This app provides the ability to detect solar panels in a given address or a given satellite image.")
+
+    # Instructions for address-based detection
     gr.Markdown("### Using by address with google maps:\n1. Enter an address or geographic coordinates.\n"
                 "2. Insert your Google maps api key which you can get from - "
                 "https://developers.google.com/maps/documentation/maps-static/get-api-key .\n"
@@ -25,20 +35,26 @@ with gr.Blocks(theme="HaleyCH/HaleyCH_Theme", title="Solar Panel Detector", css=
     zoom = gr.Slider(minimum=18, maximum=22, step=1, value=19, label="zoom")
     btn = gr.Button(value="Submit")
 
+    # Layout for displaying predictions for address-based detection
     with gr.Row():
         predicted_image_address = gr.Image(type="pil", show_label=False, scale=1)
         prediction_address = gr.Textbox(type="text", show_label=False, scale=1, elem_classes="feedback")
     btn.click(detector, inputs=[address, api_key, zoom], outputs=[predicted_image_address, prediction_address])
 
+    # Description for image-based detection
     gr.Markdown("### Using by a given image:\nUpload an image or use the examples below.")
     with gr.Row():
         im = gr.Image(type="pil", show_label=False, scale=1)
         predicted_image = gr.Image(type="pil", show_label=False, scale=1)
 
+    # Layout for displaying predictions for image-based detection
     prediction = gr.Textbox(type="text", show_label=False, elem_classes="feedback")
     btn = gr.Button(value="Submit")
+
+    # Function call for image-based detection
     btn.click(solar_panel_predict, inputs=im, outputs=[predicted_image, prediction])
 
+    # Providing example images for quick testing
     gr.Markdown("### Image Examples")
     gr.Examples(
         examples=[os.path.join(os.path.dirname(__file__), "examples/Gottingen.jpg"),