Update app.py

app.py

@@ -1,78 +1,78 @@
-# --- Gradio Interface Definition ---
-import gradio as gr
-from regenerate import on_upload_image, handle_generate_button
-with gr.Blocks() as demo:
-
-
-    gr.Markdown(
-        """
-        # Interior Design AI: Regenerate Mode
-        Upload an image, select objects to regenerate, and provide prompts.
-        """
-    )
-
-    with gr.Row():
-        with gr.Column():
-            input_image_component = gr.Image(
-                type="pil",
-                label="Upload an image of your room (PNG/JPG)",
-                sources=["upload"],
-                height=300,
-                interactive=True # Allow direct image upload
-            )
-
-
-            gr.Markdown("---")
-            gr.Markdown("### Prompts & Seed")
-            positive_prompt_textbox = gr.Textbox(
-                label="Enter prompt",
-                placeholder="a photograph of a room, interior design, 4k, high resolution",
-                interactive=False
-            )
-
-
-            gr.Markdown("---")
-            # gr.Markdown("### Regeneration Options")
-            # # This replaces the st.expander and st.write explanation
-            # gr.Markdown("This mode allows you to choose which objects you want to re-generate in the image. "
-            #             "Use the selection dropdown to add or remove objects. If you are ready, press the generate button"
-            #             " to generate the image, which can take up to 30 seconds. If you want to improve the generated image, click"
-            #             " the 'move image to input' button.")
-
-            regenerate_objects_checkboxes = gr.CheckboxGroup(
-                label="Choose which concepts you want to regenerate in the image",
-                choices=[], # Populated after image processing
-                interactive=False
-            )
-
-
-            generate_button = gr.Button("Generate Output", interactive=False)
-
-        with gr.Column():
-            output_image_display = gr.Image(type="pil", label="Output Image", height=400)
-
-
-    # --- Event Listeners ---
-
-    # When an image is uploaded or the "Process Image" button is clicked
-    input_image_component.upload(
-        fn=on_upload_image,
-        inputs=[input_image_component],
-        outputs=[
-            input_image_component,
-            regenerate_objects_checkboxes,
-            positive_prompt_textbox,
-            generate_button # Now correctly matched in outputs and function signature
-        ]
-    )
-
-    generate_button.click(
-        fn=handle_generate_button,
-        inputs=[
-            positive_prompt_textbox,
-            regenerate_objects_checkboxes, # This passes the list of selected RGB tuples
-        ],
-        outputs=[output_image_display] # Removed the second output
-    )
-
-demo.launch(debug=True, share = True)
+# --- Gradio Interface Definition ---
+import gradio as gr
+from regenerate import on_upload_image, handle_generate_button
+with gr.Blocks() as demo:
+
+
+    gr.Markdown(
+        """
+        # Interior Design AI: Regenerate Mode
+        Upload an image, select objects to regenerate, and provide prompts.
+        """
+    )
+
+    with gr.Row():
+        with gr.Column():
+            input_image_component = gr.Image(
+                type="pil",
+                label="Upload an image of your room (PNG/JPG)",
+                sources=["upload"],
+                height=300,
+                interactive=True # Allow direct image upload
+            )
+
+
+            gr.Markdown("---")
+            gr.Markdown("### Prompts & Seed")
+            positive_prompt_textbox = gr.Textbox(
+                label="Enter prompt",
+                placeholder="a photograph of a room, interior design, 4k, high resolution",
+                interactive=False
+            )
+
+
+            gr.Markdown("---")
+            # gr.Markdown("### Regeneration Options")
+            # # This replaces the st.expander and st.write explanation
+            # gr.Markdown("This mode allows you to choose which objects you want to re-generate in the image. "
+            #             "Use the selection dropdown to add or remove objects. If you are ready, press the generate button"
+            #             " to generate the image, which can take up to 30 seconds. If you want to improve the generated image, click"
+            #             " the 'move image to input' button.")
+
+            regenerate_objects_checkboxes = gr.CheckboxGroup(
+                label="Choose which concepts you want to regenerate in the image",
+                choices=[], # Populated after image processing
+                interactive=False
+            )
+
+
+            generate_button = gr.Button("Generate Output", interactive=False)
+
+        with gr.Column():
+            output_image_display = gr.Image(type="pil", label="Output Image", height=400)
+
+
+    # --- Event Listeners ---
+
+    # When an image is uploaded or the "Process Image" button is clicked
+    input_image_component.upload(
+        fn=on_upload_image,
+        inputs=[input_image_component],
+        outputs=[
+            input_image_component,
+            regenerate_objects_checkboxes,
+            positive_prompt_textbox,
+            generate_button # Now correctly matched in outputs and function signature
+        ]
+    )
+
+    generate_button.click(
+        fn=handle_generate_button,
+        inputs=[
+            positive_prompt_textbox,
+            regenerate_objects_checkboxes, # This passes the list of selected RGB tuples
+        ],
+        outputs=[output_image_display] # Removed the second output
+    )
+
+demo.launch(debug=True)