Update README.md

README.md

@@ -79,34 +79,6 @@ This model is designed for **Edge AI deployment**, optimized via **ONNX** and **
 
 **Edge Optimization:** Model converted and optimized using `openvino.convert_model()`.
 
----
-
-## Inference Example
-```python
-from openvino.runtime import Core
-import cv2
-import numpy as np
-
-ie = Core()
-model = ie.read_model(model="casting_ir/model.xml")
-compiled_model = ie.compile_model(model=model, device_name="CPU")
-
-# Load and preprocess image
-img = cv2.imread('sample_casting.png', cv2.IMREAD_GRAYSCALE)
-img = cv2.resize(img, (128, 128)) / 255.0
-img = np.expand_dims(img, (0,1)).astype(np.float32)
-
-# Run inference
-infer_request = compiled_model.create_infer_request()
-result = infer_request.infer(inputs={compiled_model.inputs[0]: img})
-
-reconstructed = result[compiled_model.outputs[0]]
-error = np.mean((img - reconstructed)**2)
-if error > 0.01:
-    print("Defective Casting Detected")
-else:
-    print("Casting OK")
-```
 
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