Update app.py

app.py

@@ -10,69 +10,24 @@ if not os.path.exists(MODEL_PATH):
 model = YOLO(MODEL_PATH)
 
 def detect_defects(image):
-    """Run object detection and return annotated image with results."""
+    """Run detection and return annotated image + detection data"""
     try:
-        # Run inference
         results = model(image)
-        
-        # Get detection results
-        boxes = results[0].boxes
-        class_names = model.names
-        detections = []
-        
-        for box in boxes:
-            class_id = int(box.cls)
-            confidence = float(box.conf)
-            detections.append({
-                "class": class_names[class_id],
-                "confidence": confidence,
-                "box": box.xyxy[0].tolist()  # [x1,y1,x2,y2]
-            })
-        
-        # Plot results
-        annotated_img = results[0].plot(line_width=2, font_size=10)
-        annotated_img = cv2.cvtColor(annotated_img, cv2.COLOR_BGR2RGB)
-        
-        return annotated_img, detections
-    
+        annotated_img = results[0].plot(line_width=2)
+        return cv2.cvtColor(annotated_img, cv2.COLOR_BGR2RGB)
     except Exception as e:
-        print(f"Error during detection: {e}")
-        return image, []
+        print(f"Error: {e}")
+        return image
 
-# Custom CSS for better UI
-css = """
-.gradio-container {max-width: 800px !important}
-.output-image {border-radius: 8px}
-"""
-
-# Interface components
-with gr.Blocks(css=css, title="Steel Defect Detector") as app:
-    gr.Markdown("## 🔍 Steel Surface Defect Detector (YOLOv8)")
-    gr.Markdown("Upload or drag-and-drop an image of steel surface to detect defects")
-    
-    with gr.Row():
-        with gr.Column():
-            image_input = gr.Image(label="Input Image", type="numpy")
-            submit_btn = gr.Button("Detect Defects", variant="primary")
-        
-        with gr.Column():
-            image_output = gr.Image(label="Detected Defects", elem_classes=["output-image"])
-            json_output = gr.JSON(label="Detection Results")
-    
-    # Example images
-    gr.Examples(
-        examples=[["example1.jpg"], ["example2.jpg"]],
-        inputs=image_input,
-        outputs=[image_output, json_output],
-        fn=detect_defects,
-        cache_examples=False
-    )
-    
-    submit_btn.click(
-        fn=detect_defects,
-        inputs=image_input,
-        outputs=[image_output, json_output]
-    )
+# Simple UI
+interface = gr.Interface(
+    fn=detect_defects,
+    inputs=gr.Image(label="Upload Steel Surface Image", type="numpy"),
+    outputs=gr.Image(label="Detected Defects"),
+    title="🔧 Steel Surface Defect Detector",
+    description="Upload an image to detect surface defects (crazing, scratches, etc.)",
+    allow_flagging="never"
+)
 
 if __name__ == "__main__":
-    app.launch(debug=True)
+    interface.launch()