Update app.py

app.py

@@ -1,44 +1,3 @@
-# import gradio as gr
-# import cv2
-# import numpy as np
-# from inspector_engine import AdvancedBlockInspector
-
-# # Initialize your engine
-# inspector = AdvancedBlockInspector()
-
-# def inspect(image):
-#     if image is None:
-#         return None, "No image uploaded"
-    
-#     # Gradio provides images in RGB, your engine uses BGR (OpenCV)
-#     frame = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
-    
-#     # Run your existing inspection logic
-#     result = inspector.inspect_block(frame)
-    
-#     # Generate the visualization using your existing method
-#     vis_frame = inspector.visualize_results(frame, result)
-    
-#     # Convert back to RGB for Gradio display
-#     vis_rgb = cv2.cvtColor(vis_frame, cv2.COLOR_BGR2RGB)
-    
-#     # Return visualized image and JSON data
-#     return vis_rgb, result.to_dict()
-
-# # Create the Interface
-# demo = gr.Interface(
-#     fn=inspect,
-#     inputs=gr.Image(type="numpy", label="Upload Engine Block Image"),
-#     outputs=[
-#         gr.Image(type="numpy", label="AI Analysis"),
-#         gr.JSON(label="Inspection Data")
-#     ],
-#     title="Industrial Engine Saddle Inspector",
-#     description="Uploading an image here will trigger YOLO-OBB and ResNet-18 analysis."
-# )
-
-# if __name__ == "__main__":
-#     demo.launch()
 import gradio as gr
 import cv2
 import numpy as np