Add TensorBoard graph for model visualization (#4464)

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

ultralytics/models/yolo/segment/train.py

@@ -56,14 +56,3 @@ class SegmentationTrainer(yolo.detect.DetectionTrainer):
     def plot_metrics(self):
         """Plots training/val metrics."""
         plot_results(file=self.csv, segment=True, on_plot=self.on_plot)  # save results.png
-
-
-def train(cfg=DEFAULT_CFG):
-    """Train a YOLO segmentation model based on passed arguments."""
-    args = dict(model=cfg.model or 'yolov8n-seg.pt', data=cfg.data or 'coco8-seg.yaml')
-    trainer = SegmentationTrainer(overrides=args)
-    trainer.train()
-
-
-if __name__ == '__main__':
-    train()

ultralytics/models/yolo/segment/val.py

@@ -8,7 +8,7 @@ import torch
 import torch.nn.functional as F
 
 from ultralytics.models.yolo.detect import DetectionValidator
-from ultralytics.utils import DEFAULT_CFG, LOGGER, NUM_THREADS, ops
+from ultralytics.utils import LOGGER, NUM_THREADS, ops
 from ultralytics.utils.checks import check_requirements
 from ultralytics.utils.metrics import SegmentMetrics, box_iou, mask_iou
 from ultralytics.utils.plotting import output_to_target, plot_images
@@ -243,14 +243,3 @@ class SegmentationValidator(DetectionValidator):
             except Exception as e:
                 LOGGER.warning(f'pycocotools unable to run: {e}')
         return stats
-
-
-def val(cfg=DEFAULT_CFG):
-    """Validate trained YOLO model on validation data."""
-    args = dict(model=cfg.model or 'yolov8n-seg.pt', data=cfg.data or 'coco8-seg.yaml')
-    validator = SegmentationValidator(args=args)
-    validator(model=args['model'])
-
-
-if __name__ == '__main__':
-    val()