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Implement all missing docstrings (#5298)

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Glenn Jocher 2023-10-10 20:07:13 +02:00 • committed by GitHub
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26 changed files with 649 additions and 79 deletions
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18
ultralytics/models/rtdetr/val.py
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@ -12,14 +12,19 @@ from ultralytics.utils import colorstr, ops
__all__ = 'RTDETRValidator', # tuple or list
# TODO: Temporarily RT-DETR does not need padding.
class RTDETRDataset(YOLODataset):
"""
Real-Time DEtection and TRacking (RT-DETR) dataset class extending the base YOLODataset class.
This specialized dataset class is designed for use with the RT-DETR object detection model and is optimized for
real-time detection and tracking tasks.
"""
def __init__(self, *args, data=None, **kwargs):
"""Initialize the RTDETRDataset class by inheriting from the YOLODataset class."""
super().__init__(*args, data=data, use_segments=False, use_keypoints=False, **kwargs)
# NOTE: add stretch version load_image for rtdetr mosaic
# NOTE: add stretch version load_image for RTDETR mosaic
def load_image(self, i, rect_mode=False):
"""Loads 1 image from dataset index 'i', returns (im, resized hw)."""
return super().load_image(i=i, rect_mode=rect_mode)
@ -46,7 +51,11 @@ class RTDETRDataset(YOLODataset):
class RTDETRValidator(DetectionValidator):
"""
A class extending the DetectionValidator class for validation based on an RT-DETR detection model.
RTDETRValidator extends the DetectionValidator class to provide validation capabilities specifically tailored for
the RT-DETR (Real-Time DETR) object detection model.
The class allows building of an RTDETR-specific dataset for validation, applies Non-maximum suppression for
post-processing, and updates evaluation metrics accordingly.
Example:
```python
@ -56,6 +65,9 @@ class RTDETRValidator(DetectionValidator):
validator = RTDETRValidator(args=args)
validator()
```
Note:
For further details on the attributes and methods, refer to the parent DetectionValidator class.
"""
def build_dataset(self, img_path, mode='val', batch=None):