otx.core.exporter.base#
Class definition for base model exporter used in OTX.
Classes
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Base class for the model exporters used in OTX. |
- class otx.core.exporter.base.OTXModelExporter(task_level_export_parameters: TaskLevelExportParameters, input_size: tuple[int, ...], mean: tuple[float, float, float] = (0.0, 0.0, 0.0), std: tuple[float, float, float] = (1.0, 1.0, 1.0), resize_mode: Literal['crop', 'standard', 'fit_to_window', 'fit_to_window_letterbox'] = 'standard', pad_value: int = 0, swap_rgb: bool = False, output_names: list[str] | None = None, input_names: list[str] | None = None)[source]#
Bases:
objectBase class for the model exporters used in OTX.
- Parameters:
task_level_export_parameters (TaskLevelExportParameters) – Collection of export parameters which can be defined at a task level.
mean (tuple[float, float, float], optional) – Mean values of 3 channels. Defaults to (0.0, 0.0, 0.0).
std (tuple[float, float, float], optional) – Std values of 3 channels. Defaults to (1.0, 1.0, 1.0).
resize_mode (Literal["crop", "standard", "fit_to_window", "fit_to_window_letterbox"], optional) – A resize type for model preprocess. “standard” resizes images without keeping ratio. “fit_to_window” resizes images while keeping ratio. “fit_to_window_letterbox” resizes images and pads images to fit the size. Defaults to “standard”.
pad_value (int, optional) – Padding value. Defaults to 0.
swap_rgb (bool, optional) – Whether to convert the image from BGR to RGB Defaults to False.
output_names (list[str] | None, optional) – Names for model’s outputs, which would be
Note (embedded into resulting model.) –
same (that order of the output names should be the) –
:param : :param as in the target model.: :param input_names: Names for model’s inputs, which would be :type input_names: list[str] | None, optional :param embedded into resulting model. Note: :param that order of the input names should be the same: :param : :param as in the target model.:
- export(model: OTXModel, output_dir: Path, base_model_name: str = 'exported_model', export_format: OTXExportFormatType = OTXExportFormatType.OPENVINO, precision: OTXPrecisionType = OTXPrecisionType.FP32, to_exportable_code: bool = False) Path[source]#
Exports input model to the specified deployable format, such as OpenVINO IR or ONNX.
- Parameters:
model (OTXModel) – OTXModel to be exported
output_dir (Path) – path to the directory to store export artifacts
base_model_name (str, optional) – exported model name
format (OTXExportFormatType) – final format of the exported model
precision (OTXExportPrecisionType, optional) – precision of the exported model’s weights
to_exportable_code (bool, optional) – whether to generate exportable code
- Returns:
path to the exported model
- Return type:
Path
- to_exportable_code(model: OTXModel, output_dir: Path, base_model_name: str = 'exported_model', precision: OTXPrecisionType = OTXPrecisionType.FP32) Path[source]#
Export to zip folder final OV IR model with runable demo.
- Parameters:
- Returns:
path to the exported model.
- Return type:
Path
- abstract to_onnx(model: OTXModel, output_dir: Path, base_model_name: str = 'exported_model', precision: OTXPrecisionType = OTXPrecisionType.FP32, embed_metadata: bool = True) Path[source]#
Abstract method for ONNX export.
Converts the given torch model to ONNX format and saves it to the specified output directory.
- Parameters:
model (OTXModel) – The input PyTorch model to be converted.
output_dir (Path) – The directory where the ONNX model will be saved.
base_model_name (str, optional) – The name of the exported ONNX model. Defaults to “exported_model”.
precision (OTXPrecisionType, optional) – The precision type for the exported model.
OTXPrecisionType.FP32. (Defaults to) –
embed_metadata (bool, optional) – Flag to embed metadata in the exported ONNX model. Defaults to True.
- Returns:
The file path where the ONNX model is saved.
- Return type:
Path