ultralytics 8.0.158 add benchmarks to coverage (#4432)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Yonghye Kwon <developer.0hye@gmail.com>

ultralytics/models/yolo/pose/__init__.py

@@ -1,7 +1,7 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
-from .predict import PosePredictor, predict
-from .train import PoseTrainer, train
-from .val import PoseValidator, val
+from .predict import PosePredictor
+from .train import PoseTrainer
+from .val import PoseValidator
 
-__all__ = 'PoseTrainer', 'train', 'PoseValidator', 'val', 'PosePredictor', 'predict'
+__all__ = 'PoseTrainer', 'PoseValidator', 'PosePredictor'

ultralytics/models/yolo/pose/predict.py

@@ -2,10 +2,23 @@
 
 from ultralytics.engine.results import Results
 from ultralytics.models.yolo.detect.predict import DetectionPredictor
-from ultralytics.utils import ASSETS, DEFAULT_CFG, LOGGER, ops
+from ultralytics.utils import DEFAULT_CFG, LOGGER, ops
 
 
 class PosePredictor(DetectionPredictor):
+    """
+    A class extending the DetectionPredictor class for prediction based on a pose model.
+
+    Example:
+        ```python
+        from ultralytics.utils import ASSETS
+        from ultralytics.models.yolo.pose import PosePredictor
+
+        args = dict(model='yolov8n-pose.pt', source=ASSETS)
+        predictor = PosePredictor(overrides=args)
+        predictor.predict_cli()
+        ```
+    """
 
     def __init__(self, cfg=DEFAULT_CFG, overrides=None, _callbacks=None):
         super().__init__(cfg, overrides, _callbacks)
@@ -40,21 +53,3 @@ class PosePredictor(DetectionPredictor):
                         boxes=pred[:, :6],
                         keypoints=pred_kpts))
         return results
-
-
-def predict(cfg=DEFAULT_CFG, use_python=False):
-    """Runs YOLO to predict objects in an image or video."""
-    model = cfg.model or 'yolov8n-pose.pt'
-    source = cfg.source or ASSETS
-
-    args = dict(model=model, source=source)
-    if use_python:
-        from ultralytics import YOLO
-        YOLO(model)(**args)
-    else:
-        predictor = PosePredictor(overrides=args)
-        predictor.predict_cli()
-
-
-if __name__ == '__main__':
-    predict()

ultralytics/models/yolo/pose/train.py

@@ -9,6 +9,18 @@ from ultralytics.utils.plotting import plot_images, plot_results
 
 
 class PoseTrainer(yolo.detect.DetectionTrainer):
+    """
+    A class extending the DetectionTrainer class for training based on a pose model.
+
+    Example:
+        ```python
+        from ultralytics.models.yolo.pose import PoseTrainer
+
+        args = dict(model='yolov8n-pose.pt', data='coco8-pose.yaml', epochs=3)
+        trainer = PoseTrainer(overrides=args)
+        trainer.train()
+        ```
+    """
 
     def __init__(self, cfg=DEFAULT_CFG, overrides=None, _callbacks=None):
         """Initialize a PoseTrainer object with specified configurations and overrides."""
@@ -59,22 +71,3 @@ class PoseTrainer(yolo.detect.DetectionTrainer):
     def plot_metrics(self):
         """Plots training/val metrics."""
         plot_results(file=self.csv, pose=True, on_plot=self.on_plot)  # save results.png
-
-
-def train(cfg=DEFAULT_CFG, use_python=False):
-    """Train the YOLO model on the given data and device."""
-    model = cfg.model or 'yolov8n-pose.yaml'
-    data = cfg.data or 'coco8-pose.yaml'
-    device = cfg.device if cfg.device is not None else ''
-
-    args = dict(model=model, data=data, device=device)
-    if use_python:
-        from ultralytics import YOLO
-        YOLO(model).train(**args)
-    else:
-        trainer = PoseTrainer(overrides=args)
-        trainer.train()
-
-
-if __name__ == '__main__':
-    train()

ultralytics/models/yolo/pose/val.py

@@ -6,13 +6,25 @@ import numpy as np
 import torch
 
 from ultralytics.models.yolo.detect import DetectionValidator
-from ultralytics.utils import DEFAULT_CFG, LOGGER, ops
+from ultralytics.utils import LOGGER, ops
 from ultralytics.utils.checks import check_requirements
 from ultralytics.utils.metrics import OKS_SIGMA, PoseMetrics, box_iou, kpt_iou
 from ultralytics.utils.plotting import output_to_target, plot_images
 
 
 class PoseValidator(DetectionValidator):
+    """
+    A class extending the DetectionValidator class for validation based on a pose model.
+
+    Example:
+        ```python
+        from ultralytics.models.yolo.pose import PoseValidator
+
+        args = dict(model='yolov8n-pose.pt', data='coco8-pose.yaml')
+        validator = PoseValidator(args=args)
+        validator(model=args['model'])
+        ```
+    """
 
     def __init__(self, dataloader=None, save_dir=None, pbar=None, args=None, _callbacks=None):
         """Initialize a 'PoseValidator' object with custom parameters and assigned attributes."""
@@ -201,21 +213,3 @@ class PoseValidator(DetectionValidator):
             except Exception as e:
                 LOGGER.warning(f'pycocotools unable to run: {e}')
         return stats
-
-
-def val(cfg=DEFAULT_CFG, use_python=False):
-    """Performs validation on YOLO model using given data."""
-    model = cfg.model or 'yolov8n-pose.pt'
-    data = cfg.data or 'coco8-pose.yaml'
-
-    args = dict(model=model, data=data)
-    if use_python:
-        from ultralytics import YOLO
-        YOLO(model).val(**args)
-    else:
-        validator = PoseValidator(args=args)
-        validator(model=args['model'])
-
-
-if __name__ == '__main__':
-    val()