ultralytics 8.0.133 add torchvision compatibility check (#3703)

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Glenn Jocher 2023-07-13 01:40:50 +02:00 committed by GitHub
parent 0821ccb618
commit c55a98ab8e
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17 changed files with 140 additions and 68 deletions

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@ -642,7 +642,8 @@ class CopyPaste:
class Albumentations:
# YOLOv8 Albumentations class (optional, only used if package is installed)
"""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
@ -819,7 +820,7 @@ def classify_albumentations(
std=(1.0, 1.0, 1.0), # IMAGENET_STD
auto_aug=False,
):
# YOLOv8 classification Albumentations (optional, only used if package is installed)
"""YOLOv8 classification Albumentations (optional, only used if package is installed)."""
prefix = colorstr('albumentations: ')
try:
import albumentations as A
@ -851,7 +852,8 @@ def classify_albumentations(
class ClassifyLetterBox:
# YOLOv8 LetterBox class for image preprocessing, i.e. T.Compose([LetterBox(size), ToTensor()])
"""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__()
@ -871,7 +873,8 @@ class ClassifyLetterBox:
class CenterCrop:
# YOLOv8 CenterCrop class for image preprocessing, i.e. T.Compose([CenterCrop(size), ToTensor()])
"""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__()
@ -885,7 +888,8 @@ class CenterCrop:
class ToTensor:
# YOLOv8 ToTensor class for image preprocessing, i.e. T.Compose([LetterBox(size), 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__()