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ultralytics 8.0.24 mosaic, DDP, download fixes (#703)

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Co-authored-by: Laughing <61612323+Laughing-q@users.noreply.github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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Glenn Jocher 2023-01-29 18:10:25 +01:00 • committed by GitHub
parent 899abe9f82
commit aecd17d455
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15 changed files with 120 additions and 98 deletions
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20
ultralytics/yolo/data/dataset.py
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@ -136,8 +136,9 @@ class YOLODataset(BaseDataset):
# TODO: use hyp config to set all these augmentations
def build_transforms(self, hyp=None):
if self.augment:
mosaic = self.augment and not self.rect
transforms = mosaic_transforms(self, self.imgsz, hyp) if mosaic else affine_transforms(self.imgsz, hyp)
hyp.mosaic = hyp.mosaic if self.augment and not self.rect else 0.0
hyp.mixup = hyp.mixup if self.augment and not self.rect else 0.0
transforms = v8_transforms(self, self.imgsz, hyp)
else:
transforms = Compose([LetterBox(new_shape=(self.imgsz, self.imgsz), scaleup=False)])
transforms.append(
@ -151,15 +152,10 @@ class YOLODataset(BaseDataset):
return transforms
def close_mosaic(self, hyp):
self.transforms = affine_transforms(self.imgsz, hyp)
self.transforms.append(
Format(bbox_format="xywh",
normalize=True,
return_mask=self.use_segments,
return_keypoint=self.use_keypoints,
batch_idx=True,
mask_ratio=hyp.mask_ratio,
mask_overlap=hyp.overlap_mask))
hyp.mosaic = 0.0 # set mosaic ratio=0.0
hyp.copy_paste = 0.0 # keep the same behavior as previous v8 close-mosaic
hyp.mixup = 0.0 # keep the same behavior as previous v8 close-mosaic
self.transforms = self.build_transforms(hyp)
def update_labels_info(self, label):
"""custom your label format here"""
@ -175,8 +171,6 @@ class YOLODataset(BaseDataset):
@staticmethod
def collate_fn(batch):
# TODO: returning a dict can make thing easier and cleaner when using dataset in training
# but I don't know if this will slow down a little bit.
new_batch = {}
keys = batch[0].keys()
values = list(zip(*[list(b.values()) for b in batch]))