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YOLOv5 updates (#90)

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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Glenn Jocher 2022-12-25 14:33:18 +01:00 • committed by GitHub
parent ebd3cfb2fd
commit 98815d560f
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27 changed files with 281 additions and 161 deletions
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12
ultralytics/yolo/data/dataset.py
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@ -124,13 +124,9 @@ class YOLODataset(BaseDataset):
# TODO: use hyp config to set all these augmentations
def build_transforms(self, hyp=None):
mosaic = self.augment and not self.rect
# mosaic = False
if self.augment:
if mosaic:
transforms = mosaic_transforms(self.imgsz, hyp)
else:
transforms = affine_transforms(self.imgsz, hyp)
mosaic = self.augment and not self.rect
transforms = mosaic_transforms(self.imgsz, hyp) if mosaic else affine_transforms(self.imgsz, hyp)
else:
transforms = Compose([LetterBox(new_shape=(self.imgsz, self.imgsz))])
transforms.append(
@ -143,7 +139,7 @@ class YOLODataset(BaseDataset):
def update_labels_info(self, label):
"""custom your label format here"""
# NOTE: cls is not with bboxes now, since other tasks like classification and semantic segmentation need a independent cls label
# NOTE: cls is not with bboxes now, classification and semantic segmentation need an independent cls label
# we can make it also support classification and semantic segmentation by add or remove some dict keys there.
bboxes = label.pop("bboxes")
segments = label.pop("segments")
@ -206,7 +202,7 @@ class ClassificationDataset(torchvision.datasets.ImageFolder):
sample = self.album_transforms(image=cv2.cvtColor(im, cv2.COLOR_BGR2RGB))["image"]
else:
sample = self.torch_transforms(im)
return OrderedDict(img=sample, cls=j)
return {'img': sample, 'cls': j}
def __len__(self) -> int:
return len(self.samples)