ultralytics 8.0.46 TFLite and Benchmarks updates (#1141)

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

ultralytics/yolo/engine/model.py

@@ -9,8 +9,9 @@ from ultralytics.nn.tasks import (ClassificationModel, DetectionModel, Segmentat
                                   guess_model_task, nn)
 from ultralytics.yolo.cfg import get_cfg
 from ultralytics.yolo.engine.exporter import Exporter
-from ultralytics.yolo.utils import DEFAULT_CFG, DEFAULT_CFG_DICT, DEFAULT_CFG_KEYS, LOGGER, RANK, callbacks, yaml_load
-from ultralytics.yolo.utils.checks import check_file, check_imgsz, check_yaml
+from ultralytics.yolo.utils import (DEFAULT_CFG, DEFAULT_CFG_DICT, DEFAULT_CFG_KEYS, LOGGER, RANK, ROOT, callbacks,
+                                    is_git_dir, is_pip_package, yaml_load)
+from ultralytics.yolo.utils.checks import check_file, check_imgsz, check_pip_update, check_yaml
 from ultralytics.yolo.utils.downloads import GITHUB_ASSET_STEMS
 from ultralytics.yolo.utils.torch_utils import smart_inference_mode
 
@@ -150,6 +151,13 @@ class YOLO:
                             f"'yolo export model=yolov8n.pt', but exported formats like ONNX, TensorRT etc. only "
                             f"support 'predict' and 'val' modes, i.e. 'yolo predict model=yolov8n.onnx'.")
 
+    def _check_pip_update(self):
+        """
+        Inform user of ultralytics package update availability
+        """
+        if is_pip_package():
+            check_pip_update()
+
     def reset(self):
         """
         Resets the model modules.
@@ -189,6 +197,10 @@ class YOLO:
         Returns:
             (List[ultralytics.yolo.engine.results.Results]): The prediction results.
         """
+        if source is None:
+            source = ROOT / 'assets' if is_git_dir() else 'https://ultralytics.com/images/bus.jpg'
+            LOGGER.warning(f"WARNING ⚠️ 'source' is missing. Using 'source={source}'.")
+
         overrides = self.overrides.copy()
         overrides['conf'] = 0.25
         overrides.update(kwargs)  # prefer kwargs
@@ -251,11 +263,12 @@ class YOLO:
         Args:
             **kwargs : Any other args accepted by the validators. To see all args check 'configuration' section in docs
         """
-        from ultralytics.yolo.utils.benchmarks import run_benchmarks
+        self._check_is_pytorch_model()
+        from ultralytics.yolo.utils.benchmarks import benchmark
         overrides = self.model.args.copy()
         overrides.update(kwargs)
         overrides = {**DEFAULT_CFG_DICT, **overrides}  # fill in missing overrides keys with defaults
-        return run_benchmarks(model=self, imgsz=overrides['imgsz'], half=overrides['half'], device=overrides['device'])
+        return benchmark(model=self, imgsz=overrides['imgsz'], half=overrides['half'], device=overrides['device'])
 
     def export(self, **kwargs):
         """
@@ -283,6 +296,7 @@ class YOLO:
             **kwargs (Any): Any number of arguments representing the training configuration.
         """
         self._check_is_pytorch_model()
+        self._check_pip_update()
         overrides = self.overrides.copy()
         overrides.update(kwargs)
         if kwargs.get('cfg'):