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ultralytics 8.0.53 DDP AMP and Edge TPU fixes (#1362)

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Co-authored-by: Richard Aljaste <richardaljasteabramson@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Vuong Kha Sieu <75152429+hotfur@users.noreply.github.com>
This commit is contained in:
Glenn Jocher
2023-03-12 02:08:13 +01:00
committed by GitHub
parent 177a68b39f
commit f921e1ac21
46 changed files with 1045 additions and 384 deletions
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14
ultralytics/yolo/data/augment.py
View File

@ -14,7 +14,7 @@ from ..utils.checks import check_version
from ..utils.instance import Instances
from ..utils.metrics import bbox_ioa
from ..utils.ops import segment2box
from .utils import IMAGENET_MEAN, IMAGENET_STD, polygons2masks, polygons2masks_overlap
from .utils import polygons2masks, polygons2masks_overlap
# TODO: we might need a BaseTransform to make all these augments be compatible with both classification and semantic
@ -682,12 +682,14 @@ def v8_transforms(dataset, imgsz, hyp):
# Classification augmentations -----------------------------------------------------------------------------------------
def classify_transforms(size=224):
def classify_transforms(size=224, mean=(0.0, 0.0, 0.0), std=(1.0, 1.0, 1.0)): # IMAGENET_MEAN, IMAGENET_STD
# Transforms to apply if albumentations not installed
if not isinstance(size, int):
raise TypeError(f'classify_transforms() size {size} must be integer, not (list, tuple)')
# T.Compose([T.ToTensor(), T.Resize(size), T.CenterCrop(size), T.Normalize(IMAGENET_MEAN, IMAGENET_STD)])
return T.Compose([CenterCrop(size), ToTensor(), T.Normalize(IMAGENET_MEAN, IMAGENET_STD)])
if any(mean) or any(std):
return T.Compose([CenterCrop(size), ToTensor(), T.Normalize(mean, std, inplace=True)])
else:
return T.Compose([CenterCrop(size), ToTensor()])
def classify_albumentations(
@ -697,8 +699,8 @@ def classify_albumentations(
hflip=0.5,
vflip=0.0,
jitter=0.4,
mean=IMAGENET_MEAN,
std=IMAGENET_STD,
mean=(0.0, 0.0, 0.0), # IMAGENET_MEAN
std=(1.0, 1.0, 1.0), # IMAGENET_STD
auto_aug=False,
):
# YOLOv8 classification Albumentations (optional, only used if package is installed)

2
ultralytics/yolo/data/dataloaders/v5loader.py
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@ -496,7 +496,7 @@ class LoadImagesAndLabels(Dataset):
# Display cache
nf, nm, ne, nc, n = cache.pop('results') # found, missing, empty, corrupt, total
if exists and LOCAL_RANK in {-1, 0}:
if exists and LOCAL_RANK in (-1, 0):
d = f'Scanning {cache_path}... {nf} images, {nm + ne} backgrounds, {nc} corrupt'
tqdm(None, desc=prefix + d, total=n, initial=n, bar_format=TQDM_BAR_FORMAT) # display cache results
if cache['msgs']:

2
ultralytics/yolo/data/dataset.py
View File

@ -133,7 +133,7 @@ class YOLODataset(BaseDataset):
# Display cache
nf, nm, ne, nc, n = cache.pop('results') # found, missing, empty, corrupt, total
if exists and LOCAL_RANK in {-1, 0}:
if exists and LOCAL_RANK in (-1, 0):
d = f'Scanning {cache_path}... {nf} images, {nm + ne} backgrounds, {nc} corrupt'
tqdm(None, desc=self.prefix + d, total=n, initial=n, bar_format=TQDM_BAR_FORMAT) # display cache results
if cache['msgs']: