Updated app.py

app.py

@@ -102,28 +102,66 @@ It can recognize subtle object differences such as **color, texture, and materia
 📘 [Training & evaluation code](https://github.com/lorebianchi98/FG-OVD/NoctOWL)
 """
 
-# --- Gradio Interface ---
-demo = gr.Interface(
-    fn=query_image,
-    inputs=[
-        gr.Image(label="Input Image"),
-        gr.Textbox(label="Text Queries (comma-separated)", placeholder="e.g., red shoes, striped shirt, yellow ball"),
-        gr.Slider(0, 1, value=0.1, step=0.01, label="Score Threshold"),
-        gr.Dropdown(
-            choices=["NoctOWLv2-Base", "NoctOWLv2-Large"],
-            label="Select Model",
-            value=None,
-            info="Select which model to use for detection",
-        ),
-    ],
-    outputs=gr.AnnotatedImage(label="Detected Objects"),
-    title="NoctOWLv2 — Fine-Grained Zero-Shot Object Detection",
-    description=description,
-    examples=[
-        ["assets/desciglio.jpg", "striped football shirt, plain red football shirt, yellow shoes, red shoes", 0.07],
-        ["assets/pool.jpg", "white ball, blue ball, black ball, yellow ball", 0.1],
-        ["assets/patio.jpg", "ceramic mug, glass mug, pink flowers, blue flowers", 0.09],
-    ],
-)
+# --- Create Interface Layout ---
+with gr.Blocks(title="NoctOWLv2 — Fine-Grained Zero-Shot Object Detection") as demo:
+    gr.Markdown(description)
+
+    with gr.Row():
+        with gr.Column():
+            input_image = gr.Image(label="Input Image")
+
+            text_queries = gr.Textbox(
+                label="Text Queries (comma-separated)",
+                placeholder="e.g., red shoes, striped shirt, yellow ball"
+            )
+
+            score_threshold = gr.Slider(
+                0, 1, value=0.1, step=0.01, label="Score Threshold"
+            )
+
+            model_dropdown = gr.Dropdown(
+                choices=["NoctOWLv2-Base", "NoctOWLv2-Large"],
+                label="Select Model",
+                value=None,
+                info="Select which model to use for detection",
+            )
+
+            run_button = gr.Button("🚀 Run Detection", interactive=False)
+
+        with gr.Column():
+            output_image = gr.AnnotatedImage(label="Detected Objects")
+
+    # --- Enable / Disable Run Button ---
+    def toggle_button(model, text):
+        return gr.update(interactive=bool(model and text.strip()))
+
+    model_dropdown.change(
+        fn=toggle_button,
+        inputs=[model_dropdown, text_queries],
+        outputs=run_button,
+    )
+
+    text_queries.change(
+        fn=toggle_button,
+        inputs=[model_dropdown, text_queries],
+        outputs=run_button,
+    )
+
+    # --- Connect Button to Inference ---
+    run_button.click(
+        fn=query_image,
+        inputs=[input_image, text_queries, score_threshold, model_dropdown],
+        outputs=output_image,
+    )
+
+    # --- Example Images (without predefined model) ---
+    gr.Examples(
+        examples=[
+            ["assets/desciglio.jpg", "striped football shirt, plain red football shirt, yellow shoes, red shoes", 0.07],
+            ["assets/pool.jpg", "white ball, blue ball, black ball, yellow ball", 0.1],
+            ["assets/patio.jpg", "ceramic mug, glass mug, pink flowers, blue flowers", 0.09],
+        ],
+        inputs=[input_image, text_queries, score_threshold],
+    )
 
 demo.launch()