Create model.py

model.py

@@ -0,0 +1,28 @@
+import numpy as np
+import triton_python_backend_utils as pb_utils
+from omnicloudmask import predict_from_array
+
+class TritonPythonModel:
+    def initialize(self, args):
+        pass
+
+    def execute(self, requests):
+        responses = []
+        for request in requests:
+            # Get input tensor
+            input_tensor = pb_utils.get_input_tensor_by_name(request, "input_array")
+            input_array = input_tensor.as_numpy()
+
+            # Perform inference
+            pred_mask = predict_from_array(input_array)
+
+            # Create output tensor
+            output_tensor = pb_utils.Tensor(
+                "output_mask", 
+                pred_mask.astype(np.uint8)
+            )
+            responses.append(pb_utils.InferenceResponse([output_tensor]))
+        return responses
+
+    def finalize(self):
+        pass