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ultralytics 8.1.11
expand OpenVINO INT8 ops for improved mAP (#7516)
Co-authored-by: AdamP <7806910+adamp87@users.noreply.github.com> Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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# Ultralytics YOLO 🚀, AGPL-3.0 license
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# Ultralytics YOLO 🚀, AGPL-3.0 license
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__version__ = "8.1.10"
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__version__ = "8.1.11"
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from ultralytics.data.explorer.explorer import Explorer
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from ultralytics.data.explorer.explorer import Explorer
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from ultralytics.models import RTDETR, SAM, YOLO
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from ultralytics.models import RTDETR, SAM, YOLO
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@ -454,7 +454,21 @@ class Exporter:
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if n < 300:
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if n < 300:
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LOGGER.warning(f"{prefix} WARNING ⚠️ >300 images recommended for INT8 calibration, found {n} images.")
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LOGGER.warning(f"{prefix} WARNING ⚠️ >300 images recommended for INT8 calibration, found {n} images.")
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quantization_dataset = nncf.Dataset(dataset, transform_fn)
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quantization_dataset = nncf.Dataset(dataset, transform_fn)
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ignored_scope = nncf.IgnoredScope(types=["Multiply", "Subtract", "Sigmoid"]) # ignore operation
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ignored_scope = None
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if isinstance(self.model.model[-1], (Detect, RTDETRDecoder)): # Segment and Pose use Detect base class
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# get detection module name in onnx
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head_module_name = ".".join(list(self.model.named_modules())[-1][0].split(".")[:2])
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ignored_scope = nncf.IgnoredScope( # ignore operations
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patterns=[
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f"/{head_module_name}/Add",
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f"/{head_module_name}/Sub",
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f"/{head_module_name}/Mul",
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f"/{head_module_name}/Div",
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f"/{head_module_name}/dfl",
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],
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names=[f"/{head_module_name}/Sigmoid"],
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)
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quantized_ov_model = nncf.quantize(
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quantized_ov_model = nncf.quantize(
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ov_model, quantization_dataset, preset=nncf.QuantizationPreset.MIXED, ignored_scope=ignored_scope
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ov_model, quantization_dataset, preset=nncf.QuantizationPreset.MIXED, ignored_scope=ignored_scope
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)
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)
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