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openvinotoolkit · Nov 15, 2024 · 9989bb5 · 9989bb5
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diff --git a/examples/post_training_quantization/onnx/yolov8_quantize_with_accuracy_control/main.py b/examples/post_training_quantization/onnx/yolov8_quantize_with_accuracy_control/main.py
@@ -16,26 +16,22 @@
 import onnx
 import onnxruntime
 import torch
-import ultralytics.utils as ul_utils
 from ultralytics.cfg import get_cfg
 from ultralytics.data.converter import coco80_to_coco91_class
 from ultralytics.data.utils import check_det_dataset
 from ultralytics.models.yolo import YOLO
 from ultralytics.models.yolo.segment.val import SegmentationValidator
+from ultralytics.utils import DATASETS_DIR
 from ultralytics.utils import DEFAULT_CFG
-from ultralytics.utils import SETTINGS
 from ultralytics.utils import ops
 from ultralytics.utils.metrics import ConfusionMatrix
 
 import nncf
 from nncf.common.logging.track_progress import track
 
-ROOT = Path(__file__).parent.resolve()
-DATASET_PATH = Path().home() / ".cache" / "nncf" / "datasets"
+MODEL_NAME = "yolov8n-seg"
 
-# Overwrite dataset path to avoid downloading COCO dataset to NNCF git root directory
-SETTINGS.update(datasets_dir=DATASET_PATH.as_posix())
-ul_utils.DATASETS_DIR = DATASET_PATH
+ROOT = Path(__file__).parent.resolve()
 
 
 def validate(
@@ -118,7 +114,7 @@ def prepare_validation(model: YOLO, args: Any) -> Tuple[SegmentationValidator, t
     validator.process = ops.process_mask
     validator.plot_masks = []
 
-    coco_data_path = DATASET_PATH / "coco128-seg"
+    coco_data_path = DATASETS_DIR / "coco128-seg"
     data_loader = validator.get_dataloader(coco_data_path.as_posix(), 1)
 
     return validator, data_loader
@@ -218,8 +214,6 @@ def validation_ac(
 
 
 def run_example():
-    MODEL_NAME = "yolov8n-seg"
-
     model = YOLO(ROOT / f"{MODEL_NAME}.pt")
     args = get_cfg(cfg=DEFAULT_CFG)
     args.data = "coco128-seg.yaml"

diff --git a/examples/post_training_quantization/openvino/yolov8/main.py b/examples/post_training_quantization/openvino/yolov8/main.py
@@ -15,13 +15,13 @@
 
 import openvino as ov
 import torch
-import ultralytics.utils as ul_utils
 from ultralytics.cfg import get_cfg
 from ultralytics.data.converter import coco80_to_coco91_class
 from ultralytics.data.utils import check_det_dataset
 from ultralytics.models.yolo import YOLO
 from ultralytics.models.yolo.detect.val import DetectionValidator
-from ultralytics.utils import SETTINGS
+from ultralytics.utils import DATASETS_DIR
+from ultralytics.utils import DEFAULT_CFG
 from ultralytics.utils.metrics import ConfusionMatrix
 
 import nncf
@@ -30,11 +30,6 @@
 MODEL_NAME = "yolov8n"
 
 ROOT = Path(__file__).parent.resolve()
-DATASET_PATH = Path().home() / ".cache" / "nncf" / "datasets"
-
-# Overwrite dataset path to avoid downloading COCO dataset to NNCF git root directory
-SETTINGS.update(datasets_dir=DATASET_PATH.as_posix())
-ul_utils.DATASETS_DIR = DATASET_PATH
 
 
 def validate(
@@ -81,7 +76,7 @@ def prepare_validation(model: YOLO, args: Any) -> Tuple[DetectionValidator, torc
     validator.metrics.names = validator.names
     validator.nc = model.model.model[-1].nc
 
-    coco_data_path = DATASET_PATH / "coco128"
+    coco_data_path = DATASETS_DIR / "coco128"
     data_loader = validator.get_dataloader(coco_data_path.as_posix(), 1)
 
     return validator, data_loader
@@ -141,7 +136,7 @@ def transform_fn(data_item: Dict):
 
 def main():
     model = YOLO(ROOT / f"{MODEL_NAME}.pt")
-    args = get_cfg(cfg=ul_utils.DEFAULT_CFG)
+    args = get_cfg(cfg=DEFAULT_CFG)
     args.data = "coco128.yaml"
 
     # Prepare validation dataset and helper

diff --git a/examples/post_training_quantization/openvino/yolov8_quantize_with_accuracy_control/main.py b/examples/post_training_quantization/openvino/yolov8_quantize_with_accuracy_control/main.py
@@ -16,14 +16,13 @@
 
 import openvino as ov
 import torch
-import ultralytics.utils as ul_utils
 from ultralytics.cfg import get_cfg
 from ultralytics.data.converter import coco80_to_coco91_class
 from ultralytics.data.utils import check_det_dataset
 from ultralytics.models.yolo import YOLO
 from ultralytics.models.yolo.segment.val import SegmentationValidator
+from ultralytics.utils import DATASETS_DIR
 from ultralytics.utils import DEFAULT_CFG
-from ultralytics.utils import SETTINGS
 from ultralytics.utils import ops
 from ultralytics.utils.metrics import ConfusionMatrix
 
@@ -33,11 +32,6 @@
 MODEL_NAME = "yolov8n-seg"
 
 ROOT = Path(__file__).parent.resolve()
-DATASET_PATH = Path().home() / ".cache" / "nncf" / "datasets"
-
-# Overwrite dataset path to avoid downloading COCO dataset to NNCF git root directory
-SETTINGS.update(datasets_dir=DATASET_PATH.as_posix())
-ul_utils.DATASETS_DIR = DATASET_PATH
 
 
 def validate(
@@ -108,7 +102,7 @@ def prepare_validation(model: YOLO, args: Any) -> Tuple[SegmentationValidator, t
     validator.process = ops.process_mask
     validator.plot_masks = []
 
-    coco_data_path = DATASET_PATH / "coco128-seg"
+    coco_data_path = DATASETS_DIR / "coco128-seg"
     data_loader = validator.get_dataloader(coco_data_path.as_posix(), 1)
 
     return validator, data_loader