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Catch case where input tensor can't be pre-defined

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This commit is contained in:
Nicolas Mowen 2025-09-15 06:49:41 -06:00
parent 562ad3d373
commit 13b7c0fce0
1 changed files with 9 additions and 4 deletions
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13
frigate/detectors/detection_runners.py
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@ -180,9 +180,14 @@ class OpenVINOModelRunner(BaseModelRunner):
# Create reusable inference request
self.infer_request = self.compiled_model.create_infer_request()
input_shape = self.compiled_model.inputs[0].get_shape()
input_element_type = self.compiled_model.inputs[0].get_element_type()
self.input_tensor = ov.Tensor(input_element_type, input_shape)
try:
input_shape = self.compiled_model.inputs[0].get_shape()
input_element_type = self.compiled_model.inputs[0].get_element_type()
self.input_tensor = ov.Tensor(input_element_type, input_shape)
except RuntimeError:
# model is complex and has dynamic shape
self.input_tensor = None
def get_input_names(self) -> list[str]:
"""Get input names for the model."""
@ -204,7 +209,7 @@ class OpenVINOModelRunner(BaseModelRunner):
List of output tensors
"""
# Handle single input case for backward compatibility
if len(inputs) == 1 and len(self.compiled_model.inputs) == 1:
if len(inputs) == 1 and len(self.compiled_model.inputs) == 1 and self.input_tensor is not None:
# Single input case - use the pre-allocated tensor for efficiency
input_data = list(inputs.values())[0]
np.copyto(self.input_tensor.data, input_data)