Update app.py

app.py

@@ -46,30 +46,64 @@ def yolov8_inference(
 
     return annotated_image
 
-image_input = gr.inputs.Image()  # Adjust the shape according to your requirements
-
-inputs = [
-    gr.inputs.Image(label="Input Image"),
-    gr.Slider(
-        minimum=0.0, maximum=1.0, value=0.25, step=0.05, label="Confidence Threshold"
-    ),
-    gr.Slider(minimum=0.0, maximum=1.0, value=0.45, step=0.05, label="IOU Threshold"),
-]
-
-outputs = gr.Image(type="filepath", label="Output Image")
-title = "Brain Tumor Demo"
+# image_input = gr.inputs.Image()  # Adjust the shape according to your requirements
+
+# inputs = [
+#     gr.inputs.Image(label="Input Image"),
+#     gr.Slider(
+#         minimum=0.0, maximum=1.0, value=0.25, step=0.05, label="Confidence Threshold"
+#     ),
+#     gr.Slider(minimum=0.0, maximum=1.0, value=0.45, step=0.05, label="IOU Threshold"),
+# ]
+
+# outputs = gr.Image(type="filepath", label="Output Image")
+# title = "Brain Tumor Demo"
 import os
 examples = [
     ["tu1.jpg", 0.6, 0.45],
     ["tu2.jpg", 0.25, 0.45],
     ["tu3.jpg", 0.25, 0.45],
 ]
-demo_app = gr.Interface(examples=examples,
-    fn=yolov8_inference,
-    inputs=inputs,
-    outputs=outputs,
-    title=title,
-    cache_examples=True,
-    theme="default",
-)
-demo_app.launch(debug=False, enable_queue=True)
+# demo_app = gr.Interface(examples=examples,
+#     fn=yolov8_inference,
+#     inputs=inputs,
+#     outputs=outputs,
+#     title=title,
+#     cache_examples=True,
+#     theme="default",
+# )
+# demo_app.launch(debug=False, enable_queue=True)
+gr.Examples(examples) # Add the examples to the app
+with gr.Blocks() as demo:
+    gr.Markdown(
+            """
+            # Tuba Brain Tumor Demo
+
+            [Tuba](https://Tuba.ai)
+            """
+        )
+    # Define the input components and add them to the layout
+    with gr.Row():
+        image_input = gr.inputs.Image()
+        
+        
+        outputs = gr.Image(type="filepath", label="Output Image")
+        
+    # Define the output component and add it to the layout
+    with gr.Row():
+        conf_slider=gr.Slider(minimum=0.0, maximum=1.0, value=0.25, step=0.05, label="Confidence Threshold" )
+    with gr.Row():
+        IOU_Slider=gr.Slider(minimum=0.0, maximum=1.0, value=0.45, step=0.05, label="IOU Threshold")
+    
+    gr.Examples(examples) # Add the examples to 
+
+    with gr.Row():
+        button = gr.Button("Run")
+        
+    # Define the event listener that connects the input and output components and triggers the function
+    button.click(fn=get_results, inputs=[image_input, conf_slider,IOU_Slider], outputs=output, api_name="yolov8_inference")
+    # Add the description below the layout
+    gr.Markdown(description_html)
+# Launch the app
+demo.launch(share=False)
+