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Create meta_data.json with ONNX export as well as OpenVINO export #636

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merged 6 commits into from
Oct 19, 2022
Merged

Create meta_data.json with ONNX export as well as OpenVINO export #636

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1f7dc0c
When exporting, create metadata.json for both ONNX and OpenVINO expor…
calebmm Oct 17, 2022
031b69a
Updated export to include metadata.json in both ONNX and OpenVINO exp…
calebmm Oct 17, 2022
044a0bb
code formatting
pmudgal-Intel Oct 17, 2022
bff658c
code formatting
pmudgal-Intel Oct 17, 2022
05e4d65
Merge branch 'main' into main
pmudgal-Intel Oct 18, 2022
b997a0f
Modified export_mode while exporting meta_data.json
pmudgal-Intel Oct 18, 2022
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18 changes: 9 additions & 9 deletions anomalib/deploy/optimize.py
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Original file line number Diff line number Diff line change
Expand Up @@ -47,7 +47,7 @@ def export_convert(
export_mode: str,
export_path: Optional[Union[str, Path]] = None,
):
"""Export the model to onnx format and convert to OpenVINO IR.
"""Export the model to onnx format and convert to OpenVINO IR. Metadata.json is generated regardless of export mode.

Args:
model (AnomalyModule): Model to convert.
Expand All @@ -65,14 +65,14 @@ def export_convert(
input_names=["input"],
output_names=["output"],
)
export_path = os.path.join(str(export_path), "openvino")
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if export_mode == "openvino":
export_path = os.path.join(str(export_path), "openvino")
optimize_command = "mo --input_model " + str(onnx_path) + " --output_dir " + str(export_path)
assert os.system(optimize_command) == 0, "OpenVINO conversion failed"
with open(Path(export_path) / "meta_data.json", "w", encoding="utf-8") as metadata_file:
meta_data = get_model_metadata(model)
# Convert metadata from torch
for key, value in meta_data.items():
if isinstance(value, Tensor):
meta_data[key] = value.numpy().tolist()
json.dump(meta_data, metadata_file, ensure_ascii=False, indent=4)
with open(Path(export_path) / "meta_data.json", "w", encoding="utf-8") as metadata_file:
meta_data = get_model_metadata(model)
# Convert metadata from torch
for key, value in meta_data.items():
if isinstance(value, Tensor):
meta_data[key] = value.numpy().tolist()
json.dump(meta_data, metadata_file, ensure_ascii=False, indent=4)