Fix PIL Image exif_size() function (#4355)

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

ultralytics/engine/model.py

@@ -282,6 +282,8 @@ class Model:
         overrides['rect'] = True  # rect batches as default
         overrides.update(kwargs)
         overrides['mode'] = 'val'
+        if overrides.get('imgsz') is None:
+            overrides['imgsz'] = self.model.args['imgsz']  # use trained imgsz unless custom value is passed
         args = get_cfg(cfg=DEFAULT_CFG, overrides=overrides)
         args.data = data or args.data
         if 'task' in overrides:
@@ -289,8 +291,6 @@ class Model:
         else:
             args.task = self.task
         validator = validator or self.smart_load('validator')
-        if args.imgsz == DEFAULT_CFG.imgsz and not isinstance(self.model, (str, Path)):
-            args.imgsz = self.model.args['imgsz']  # use trained imgsz unless custom value is passed
         args.imgsz = check_imgsz(args.imgsz, max_dim=1)
 
         validator = validator(args=args, _callbacks=self.callbacks)

ultralytics/engine/trainer.py

@@ -5,6 +5,7 @@ Train a model on a dataset
 Usage:
     $ yolo mode=train model=yolov8n.pt data=coco128.yaml imgsz=640 epochs=100 batch=16
 """
+
 import math
 import os
 import subprocess
@@ -48,8 +49,8 @@ class BaseTrainer:
         callbacks (defaultdict): Dictionary of callbacks.
         save_dir (Path): Directory to save results.
         wdir (Path): Directory to save weights.
-        last (Path): Path to last checkpoint.
-        best (Path): Path to best checkpoint.
+        last (Path): Path to the last checkpoint.
+        best (Path): Path to the best checkpoint.
         save_period (int): Save checkpoint every x epochs (disabled if < 1).
         batch_size (int): Batch size for training.
         epochs (int): Number of epochs to train for.