ultralytics 8.0.135 remove deprecated v5loader (#3744)

ultralytics/yolo/v8/detect/val.py

@@ -7,9 +7,8 @@ import numpy as np
 import torch
 
 from ultralytics.yolo.data import build_dataloader, build_yolo_dataset
-from ultralytics.yolo.data.dataloaders.v5loader import create_dataloader
 from ultralytics.yolo.engine.validator import BaseValidator
-from ultralytics.yolo.utils import DEFAULT_CFG, LOGGER, colorstr, ops
+from ultralytics.yolo.utils import DEFAULT_CFG, LOGGER, ops
 from ultralytics.yolo.utils.checks import check_requirements
 from ultralytics.yolo.utils.metrics import ConfusionMatrix, DetMetrics, box_iou
 from ultralytics.yolo.utils.plotting import output_to_target, plot_images
@@ -186,28 +185,9 @@ class DetectionValidator(BaseValidator):
         return build_yolo_dataset(self.args, img_path, batch, self.data, mode=mode, stride=gs)
 
     def get_dataloader(self, dataset_path, batch_size):
-        """TODO: manage splits differently."""
-        # Calculate stride - check if model is initialized
-        if self.args.v5loader:
-            LOGGER.warning("WARNING ⚠️ 'v5loader' feature is deprecated and will be removed soon. You can train using "
-                           'the default YOLOv8 dataloader instead, no argument is needed.')
-            gs = max(int(de_parallel(self.model).stride if self.model else 0), 32)
-            return create_dataloader(path=dataset_path,
-                                     imgsz=self.args.imgsz,
-                                     batch_size=batch_size,
-                                     stride=gs,
-                                     hyp=vars(self.args),
-                                     cache=False,
-                                     pad=0.5,
-                                     rect=self.args.rect,
-                                     workers=self.args.workers,
-                                     prefix=colorstr(f'{self.args.mode}: '),
-                                     shuffle=False,
-                                     seed=self.args.seed)[0]
-
+        """Construct and return dataloader."""
         dataset = self.build_dataset(dataset_path, batch=batch_size, mode='val')
-        dataloader = build_dataloader(dataset, batch_size, self.args.workers, shuffle=False, rank=-1)
-        return dataloader
+        return build_dataloader(dataset, batch_size, self.args.workers, shuffle=False, rank=-1)  # return dataloader
 
     def plot_val_samples(self, batch, ni):
         """Plot validation image samples."""