General console printout updates (#48)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

ultralytics/yolo/v8/segment/train.py

@@ -1,7 +1,3 @@
-import subprocess
-import time
-from pathlib import Path
-
 import hydra
 import torch
 import torch.nn as nn
@@ -10,7 +6,6 @@ import torch.nn.functional as F
 from ultralytics.yolo import v8
 from ultralytics.yolo.data import build_dataloader
 from ultralytics.yolo.engine.trainer import DEFAULT_CONFIG, BaseTrainer
-from ultralytics.yolo.utils.anchors import check_anchors
 from ultralytics.yolo.utils.metrics import FocalLoss, bbox_iou, smooth_BCE
 from ultralytics.yolo.utils.modeling.tasks import SegmentationModel
 from ultralytics.yolo.utils.ops import crop_mask, xywh2xyxy
@@ -24,7 +19,7 @@ class SegmentationTrainer(BaseTrainer):
         # TODO: manage splits differently
         # calculate stride - check if model is initialized
         gs = max(int(de_parallel(self.model).stride.max() if self.model else 0), 32)
-        loader = build_dataloader(
+        return build_dataloader(
             img_path=dataset_path,
             img_size=self.args.img_size,
             batch_size=batch_size,
@@ -38,18 +33,16 @@ class SegmentationTrainer(BaseTrainer):
             shuffle=self.args.shuffle,
             use_segments=True,
         )[0]
-        return loader
 
     def preprocess_batch(self, batch):
         batch["img"] = batch["img"].to(self.device, non_blocking=True).float() / 255
         return batch
 
     def load_model(self, model_cfg, weights, data):
-        model = SegmentationModel(model_cfg if model_cfg else weights["model"].yaml,
+        model = SegmentationModel(model_cfg or weights["model"].yaml,
                                   ch=3,
                                   nc=data["nc"],
                                   anchors=self.args.get("anchors"))
-        check_anchors(model, self.args.anchor_t, self.args.img_size)
         if weights:
             model.load(weights)
         return model