ultralytics 8.0.81 single-line docstring updates (#2061)
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
This commit is contained in:
Glenn Jocher
GitHub
parent
5bce1c3021
commit
a38f227672
64 changed files with 620 additions and 58 deletions
|
|
@ -26,15 +26,19 @@ class BaseTransform:
|
|||
pass
|
||||
|
||||
def apply_image(self, labels):
|
||||
"""Applies image transformation to labels."""
|
||||
pass
|
||||
|
||||
def apply_instances(self, labels):
|
||||
"""Applies transformations to input 'labels' and returns object instances."""
|
||||
pass
|
||||
|
||||
def apply_semantic(self, labels):
|
||||
"""Applies semantic segmentation to an image."""
|
||||
pass
|
||||
|
||||
def __call__(self, labels):
|
||||
"""Applies label transformations to an image, instances and semantic masks."""
|
||||
self.apply_image(labels)
|
||||
self.apply_instances(labels)
|
||||
self.apply_semantic(labels)
|
||||
|
|
@ -43,20 +47,25 @@ class BaseTransform:
|
|||
class Compose:
|
||||
|
||||
def __init__(self, transforms):
|
||||
"""Initializes the Compose object with a list of transforms."""
|
||||
self.transforms = transforms
|
||||
|
||||
def __call__(self, data):
|
||||
"""Applies a series of transformations to input data."""
|
||||
for t in self.transforms:
|
||||
data = t(data)
|
||||
return data
|
||||
|
||||
def append(self, transform):
|
||||
"""Appends a new transform to the existing list of transforms."""
|
||||
self.transforms.append(transform)
|
||||
|
||||
def tolist(self):
|
||||
"""Converts list of transforms to a standard Python list."""
|
||||
return self.transforms
|
||||
|
||||
def __repr__(self):
|
||||
"""Return string representation of object."""
|
||||
format_string = f'{self.__class__.__name__}('
|
||||
for t in self.transforms:
|
||||
format_string += '\n'
|
||||
|
|
@ -74,6 +83,7 @@ class BaseMixTransform:
|
|||
self.p = p
|
||||
|
||||
def __call__(self, labels):
|
||||
"""Applies pre-processing transforms and mixup/mosaic transforms to labels data."""
|
||||
if random.uniform(0, 1) > self.p:
|
||||
return labels
|
||||
|
||||
|
|
@ -96,9 +106,11 @@ class BaseMixTransform:
|
|||
return labels
|
||||
|
||||
def _mix_transform(self, labels):
|
||||
"""Applies MixUp or Mosaic augmentation to the label dictionary."""
|
||||
raise NotImplementedError
|
||||
|
||||
def get_indexes(self):
|
||||
"""Gets a list of shuffled indexes for mosaic augmentation."""
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
|
@ -111,6 +123,7 @@ class Mosaic(BaseMixTransform):
|
|||
"""
|
||||
|
||||
def __init__(self, dataset, imgsz=640, p=1.0, border=(0, 0)):
|
||||
"""Initializes the object with a dataset, image size, probability, and border."""
|
||||
assert 0 <= p <= 1.0, 'The probability should be in range [0, 1]. ' f'got {p}.'
|
||||
super().__init__(dataset=dataset, p=p)
|
||||
self.dataset = dataset
|
||||
|
|
@ -118,9 +131,11 @@ class Mosaic(BaseMixTransform):
|
|||
self.border = border
|
||||
|
||||
def get_indexes(self):
|
||||
"""Return a list of 3 random indexes from the dataset."""
|
||||
return [random.randint(0, len(self.dataset) - 1) for _ in range(3)]
|
||||
|
||||
def _mix_transform(self, labels):
|
||||
"""Apply mixup transformation to the input image and labels."""
|
||||
mosaic_labels = []
|
||||
assert labels.get('rect_shape', None) is None, 'rect and mosaic is exclusive.'
|
||||
assert len(labels.get('mix_labels', [])) > 0, 'There are no other images for mosaic augment.'
|
||||
|
|
@ -166,6 +181,7 @@ class Mosaic(BaseMixTransform):
|
|||
return labels
|
||||
|
||||
def _cat_labels(self, mosaic_labels):
|
||||
"""Return labels with mosaic border instances clipped."""
|
||||
if len(mosaic_labels) == 0:
|
||||
return {}
|
||||
cls = []
|
||||
|
|
@ -190,6 +206,7 @@ class MixUp(BaseMixTransform):
|
|||
super().__init__(dataset=dataset, pre_transform=pre_transform, p=p)
|
||||
|
||||
def get_indexes(self):
|
||||
"""Get a random index from the dataset."""
|
||||
return random.randint(0, len(self.dataset) - 1)
|
||||
|
||||
def _mix_transform(self, labels):
|
||||
|
|
@ -400,6 +417,7 @@ class RandomHSV:
|
|||
self.vgain = vgain
|
||||
|
||||
def __call__(self, labels):
|
||||
"""Applies random horizontal or vertical flip to an image with a given probability."""
|
||||
img = labels['img']
|
||||
if self.hgain or self.sgain or self.vgain:
|
||||
r = np.random.uniform(-1, 1, 3) * [self.hgain, self.sgain, self.vgain] + 1 # random gains
|
||||
|
|
@ -427,6 +445,7 @@ class RandomFlip:
|
|||
self.flip_idx = flip_idx
|
||||
|
||||
def __call__(self, labels):
|
||||
"""Resize image and padding for detection, instance segmentation, pose."""
|
||||
img = labels['img']
|
||||
instances = labels.pop('instances')
|
||||
instances.convert_bbox(format='xywh')
|
||||
|
|
@ -453,6 +472,7 @@ class LetterBox:
|
|||
"""Resize image and padding for detection, instance segmentation, pose."""
|
||||
|
||||
def __init__(self, new_shape=(640, 640), auto=False, scaleFill=False, scaleup=True, stride=32):
|
||||
"""Initialize LetterBox object with specific parameters."""
|
||||
self.new_shape = new_shape
|
||||
self.auto = auto
|
||||
self.scaleFill = scaleFill
|
||||
|
|
@ -460,6 +480,7 @@ class LetterBox:
|
|||
self.stride = stride
|
||||
|
||||
def __call__(self, labels=None, image=None):
|
||||
"""Return updated labels and image with added border."""
|
||||
if labels is None:
|
||||
labels = {}
|
||||
img = labels.get('img') if image is None else image
|
||||
|
|
@ -556,6 +577,7 @@ class CopyPaste:
|
|||
class Albumentations:
|
||||
# YOLOv8 Albumentations class (optional, only used if package is installed)
|
||||
def __init__(self, p=1.0):
|
||||
"""Initialize the transform object for YOLO bbox formatted params."""
|
||||
self.p = p
|
||||
self.transform = None
|
||||
prefix = colorstr('albumentations: ')
|
||||
|
|
@ -581,6 +603,7 @@ class Albumentations:
|
|||
LOGGER.info(f'{prefix}{e}')
|
||||
|
||||
def __call__(self, labels):
|
||||
"""Generates object detections and returns a dictionary with detection results."""
|
||||
im = labels['img']
|
||||
cls = labels['cls']
|
||||
if len(cls):
|
||||
|
|
@ -618,6 +641,7 @@ class Format:
|
|||
self.batch_idx = batch_idx # keep the batch indexes
|
||||
|
||||
def __call__(self, labels):
|
||||
"""Return formatted image, classes, bounding boxes & keypoints to be used by 'collate_fn'."""
|
||||
img = labels.pop('img')
|
||||
h, w = img.shape[:2]
|
||||
cls = labels.pop('cls')
|
||||
|
|
@ -647,6 +671,7 @@ class Format:
|
|||
return labels
|
||||
|
||||
def _format_img(self, img):
|
||||
"""Format the image for YOLOv5 from Numpy array to PyTorch tensor."""
|
||||
if len(img.shape) < 3:
|
||||
img = np.expand_dims(img, -1)
|
||||
img = np.ascontiguousarray(img.transpose(2, 0, 1)[::-1])
|
||||
|
|
@ -668,6 +693,7 @@ class Format:
|
|||
|
||||
|
||||
def v8_transforms(dataset, imgsz, hyp):
|
||||
"""Convert images to a size suitable for YOLOv8 training."""
|
||||
pre_transform = Compose([
|
||||
Mosaic(dataset, imgsz=imgsz, p=hyp.mosaic, border=[-imgsz // 2, -imgsz // 2]),
|
||||
CopyPaste(p=hyp.copy_paste),
|
||||
|
|
@ -749,6 +775,7 @@ def classify_albumentations(
|
|||
class ClassifyLetterBox:
|
||||
# YOLOv8 LetterBox class for image preprocessing, i.e. T.Compose([LetterBox(size), ToTensor()])
|
||||
def __init__(self, size=(640, 640), auto=False, stride=32):
|
||||
"""Resizes image and crops it to center with max dimensions 'h' and 'w'."""
|
||||
super().__init__()
|
||||
self.h, self.w = (size, size) if isinstance(size, int) else size
|
||||
self.auto = auto # pass max size integer, automatically solve for short side using stride
|
||||
|
|
@ -768,6 +795,7 @@ class ClassifyLetterBox:
|
|||
class CenterCrop:
|
||||
# YOLOv8 CenterCrop class for image preprocessing, i.e. T.Compose([CenterCrop(size), ToTensor()])
|
||||
def __init__(self, size=640):
|
||||
"""Converts an image from numpy array to PyTorch tensor."""
|
||||
super().__init__()
|
||||
self.h, self.w = (size, size) if isinstance(size, int) else size
|
||||
|
||||
|
|
@ -781,6 +809,7 @@ class CenterCrop:
|
|||
class ToTensor:
|
||||
# YOLOv8 ToTensor class for image preprocessing, i.e. T.Compose([LetterBox(size), ToTensor()])
|
||||
def __init__(self, half=False):
|
||||
"""Initialize YOLOv8 ToTensor object with optional half-precision support."""
|
||||
super().__init__()
|
||||
self.half = half
|
||||
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue