New ASSETS and trackers GMC cleanup (#4425)

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

ultralytics/utils/benchmarks.py

@@ -37,9 +37,8 @@ from tqdm import tqdm
 from ultralytics import YOLO
 from ultralytics.cfg import TASK2DATA, TASK2METRIC
 from ultralytics.engine.exporter import export_formats
-from ultralytics.utils import LINUX, LOGGER, MACOS, ROOT, SETTINGS
+from ultralytics.utils import ASSETS, LINUX, LOGGER, MACOS, SETTINGS
 from ultralytics.utils.checks import check_requirements, check_yolo
-from ultralytics.utils.downloads import download
 from ultralytics.utils.files import file_size
 from ultralytics.utils.torch_utils import select_device
 
@@ -68,6 +67,13 @@ def benchmark(model=Path(SETTINGS['weights_dir']) / 'yolov8n.pt',
     Returns:
         df (pandas.DataFrame): A pandas DataFrame with benchmark results for each format, including file size,
             metric, and inference time.
+
+    Example:
+        ```python
+        from ultralytics.utils.benchmarks import benchmark
+
+        benchmark(model='yolov8n.pt', imgsz=640)
+        ```
     """
 
     import pandas as pd
@@ -106,9 +112,7 @@ def benchmark(model=Path(SETTINGS['weights_dir']) / 'yolov8n.pt',
             assert model.task != 'pose' or i != 7, 'GraphDef Pose inference is not supported'
             assert i not in (9, 10), 'inference not supported'  # Edge TPU and TF.js are unsupported
             assert i != 5 or platform.system() == 'Darwin', 'inference only supported on macOS>=10.13'  # CoreML
-            if not (ROOT / 'assets/bus.jpg').exists():
-                download(url='https://ultralytics.com/images/bus.jpg', dir=ROOT / 'assets')
-            export.predict(ROOT / 'assets/bus.jpg', imgsz=imgsz, device=device, half=half)
+            export.predict(ASSETS / 'bus.jpg', imgsz=imgsz, device=device, half=half)
 
             # Validate
             data = data or TASK2DATA[model.task]  # task to dataset, i.e. coco8.yaml for task=detect
@@ -163,6 +167,13 @@ class ProfileModels:
 
     Methods:
         profile(): Profiles the models and prints the result.
+
+    Example:
+        ```python
+        from ultralytics.utils.benchmarks import ProfileModels
+
+        ProfileModels(['yolov8n.yaml', 'yolov8s.yaml'], imgsz=640).profile()
+        ```
     """
 
     def __init__(self,
@@ -353,11 +364,3 @@ class ProfileModels:
         print(separator)
         for row in table_rows:
             print(row)
-
-
-if __name__ == '__main__':
-    # Benchmark all export formats
-    benchmark()
-
-    # Profiling models on ONNX and TensorRT
-    ProfileModels(['yolov8n.yaml', 'yolov8s.yaml'])