Update app.py

app.py

@@ -200,8 +200,7 @@ class GradioApp:
     def process_image(
         self,
         image: Optional[np.ndarray],
-        confidence: float,
-        nms_threshold: float
+        confidence: float
     ) -> Tuple[Optional[Image.Image], str]:
         """
         Process image and return annotated result.
@@ -209,7 +208,6 @@ class GradioApp:
         Args:
             image: Input image
             confidence: Confidence threshold
-            nms_threshold: NMS threshold
         
         Returns:
             Tuple of (annotated_image, summary_text)
@@ -218,11 +216,11 @@ class GradioApp:
             return None, "Please upload an image."
         
         try:
-            # Perform detection
+            # Perform detection (NMS threshold from config)
             detections, image_bgr = self.pipeline.detect(
                 image,
                 confidence_threshold=confidence,
-                nms_threshold=nms_threshold
+                nms_threshold=None  # Use default from config
             )
             
             # Annotate image
@@ -256,13 +254,29 @@ class GradioApp:
             with gr.Row():
                 # Left column - Input and controls
                 with gr.Column(scale=1):
-                    gr.Markdown("### 📤 Upload Image")
+                    # Examples section BEFORE upload
+                    gr.Markdown("### 📋 Example Images")
                     input_img = gr.Image(
                         label="Input Image",
                         type="numpy",
                         interactive=True
                     )
                     
+                    example_root = os.path.dirname(__file__)
+                    example_images = [
+                        os.path.join(example_root, file)
+                        for file in os.listdir(example_root)
+                        if file.lower().endswith(('.jpg', '.jpeg', '.png'))
+                    ]
+                    
+                    if example_images:
+                        gr.Examples(
+                            examples=example_images,
+                            inputs=[input_img],
+                        )
+                    
+                    gr.Markdown("### 📤 Or Upload Your Own Image")
+                    
                     # Detection parameters
                     gr.Markdown("### ⚙️ Detection Parameters")
                     confidence_slider = gr.Slider(
@@ -274,15 +288,6 @@ class GradioApp:
                         info="Minimum confidence for a detection"
                     )
                     
-                    nms_slider = gr.Slider(
-                        minimum=0.0,
-                        maximum=1.0,
-                        value=0.0,
-                        step=0.05,
-                        label="NMS Threshold",
-                        info="IoU threshold for non-maximum suppression"
-                    )
-                    
                     # Action buttons
                     with gr.Row():
                         clear_btn = gr.Button("🗑️ Clear", variant="secondary")
@@ -300,24 +305,6 @@ class GradioApp:
                         label="Detection Summary"
                     )
             
-            # Examples section
-            gr.Markdown("### 📋 Example Images")
-            example_root = os.path.dirname(__file__)
-            example_images = [
-                [os.path.join(example_root, file), 0.1, 0.0]
-                for file in os.listdir(example_root)
-                if file.lower().endswith(('.jpg', '.jpeg', '.png'))
-            ]
-            
-            if example_images:
-                gr.Examples(
-                    examples=example_images,
-                    inputs=[input_img, confidence_slider, nms_slider],
-                    outputs=[output_img, detection_summary],
-                    fn=self.process_image,
-                    cache_examples=False
-                )
-            
             # Footer
             gr.Markdown(
                 """
@@ -328,17 +315,17 @@ class GradioApp:
             
             # Event handlers
             def reset_interface():
-                return None, None, "Results will appear here...", 0.1, 0.0
+                return None, None, "Results will appear here...", 0.1
             
             clear_btn.click(
                 fn=reset_interface,
                 inputs=None,
-                outputs=[input_img, output_img, detection_summary, confidence_slider, nms_slider]
+                outputs=[input_img, output_img, detection_summary, confidence_slider]
             )
             
             detect_btn.click(
                 fn=self.process_image,
-                inputs=[input_img, confidence_slider, nms_slider],
+                inputs=[input_img, confidence_slider],
                 outputs=[output_img, detection_summary]
             )