Update app.py

app.py

@@ -12,45 +12,33 @@ matplotlib.use('Agg')  # Use Agg backend
 
 # Check for CUDA availability
 if not torch.cuda.is_available():
-    # If CUDA isn't available, create a simple Gradio interface to notify users
+    # If CUDA isn't available, create the Gradio interface but disable all elements and show a warning
     with gr.Blocks() as demo:
-        gr.HTML("""
-            <style>
-                body {
-                    position: relative;
-                    height: 100vh;
-                    width: 100%;
-                    display: flex;
-                    justify-content: center;
-                    align-items: center;
-                    background: rgba(0, 0, 0, 0.1);
-                    filter: blur(10px);
-                }
-                .overlay {
-                    position: absolute;
-                    z-index: 10;
-                    color: white;
-                    font-size: 20px;
-                    text-align: center;
-                    padding: 20px;
-                    background-color: rgba(0, 0, 0, 0.7);
-                    border-radius: 10px;
-                    box-shadow: 0px 0px 20px rgba(0, 0, 0, 0.5);
-                }
-                .message {
-                    font-size: 22px;
-                    margin-top: 20px;
-                }
-            </style>
-            <div class="overlay">
-                <h1>CUDA is not available</h1>
-                <p>Please clone the repository or run it in Colab:</p>
-                <a href="https://github.com/SanshruthR/Stable-Diffusion-Inpainting_with_SAM" style="color: #1e90ff; text-decoration: underline;">GitHub Repository</a>
-                <div class="message">
-                    <p>We are currently unable to run on this machine because CUDA is missing.</p>
-                </div>
-            </div>
-        """)
+        gr.Markdown("# Segment Anything + Stable Diffusion Inpainting")
+        
+        # Show warning message for users with a link to the GitHub repository
+        gr.Markdown("**CUDA is not available.** Please run it on Google Colab. You can find the Colab here: [Colab Link](https://github.com/SanshruthR/Stable-Diffusion-Inpainting_with_SAM)")
+
+        # Step 1: Segment Image Tab
+        with gr.Tab("Step 1: Segment Image"):
+            with gr.Row():
+                input_image = gr.Image(label="Input Image", interactive=False)
+                mask_output = gr.Plot(label="Available Masks", interactive=False)
+            segment_btn = gr.Button("Generate Masks", interactive=False)
+        
+        # Step 2: Inpainting Tab
+        with gr.Tab("Step 2: Inpaint"):
+            with gr.Row():
+                with gr.Column():
+                    mask_index = gr.Slider(minimum=0, maximum=20, step=1, 
+                                         label="Mask Index (select based on mask numbers from Step 1)", interactive=False)
+                    prompt1 = gr.Textbox(label="Prompt 1", placeholder="Enter first inpainting prompt", interactive=False)
+                    prompt2 = gr.Textbox(label="Prompt 2", placeholder="Enter second inpainting prompt", interactive=False)
+                    prompt3 = gr.Textbox(label="Prompt 3", placeholder="Enter third inpainting prompt", interactive=False)
+                    prompt4 = gr.Textbox(label="Prompt 4", placeholder="Enter fourth inpainting prompt", interactive=False)
+                inpaint_output = gr.Plot(label="Inpainting Results", interactive=False)
+            inpaint_btn = gr.Button("Generate Inpainting", interactive=False)
+
         demo.launch(share=True, debug=True)
     exit()  # Exit the program if CUDA is not available