From c49773227821fec1d73ef196400d09083ea83899 Mon Sep 17 00:00:00 2001 From: Kayzwer <68285002+Kayzwer@users.noreply.github.com> Date: Sat, 22 Jun 2024 02:48:10 +0800 Subject: [PATCH] Replace `+=` with faster list `.append()` (#13849) Co-authored-by: UltralyticsAssistant Co-authored-by: Glenn Jocher --- ultralytics/data/augment.py | 29 +++++++++++++---------------- 1 file changed, 13 insertions(+), 16 deletions(-) diff --git a/ultralytics/data/augment.py b/ultralytics/data/augment.py index a51bf235b..2400de11c 100644 --- a/ultralytics/data/augment.py +++ b/ultralytics/data/augment.py @@ -1223,16 +1223,13 @@ def classify_transforms( else: # Resize the shortest edge to matching target dim for non-square target tfl = [T.Resize(scale_size)] - tfl += [T.CenterCrop(size)] - - tfl += [ - T.ToTensor(), - T.Normalize( - mean=torch.tensor(mean), - std=torch.tensor(std), - ), - ] - + tfl.extend( + [ + T.CenterCrop(size), + T.ToTensor(), + T.Normalize(mean=torch.tensor(mean), std=torch.tensor(std)), + ] + ) return T.Compose(tfl) @@ -1284,9 +1281,9 @@ def classify_augmentations( ratio = tuple(ratio or (3.0 / 4.0, 4.0 / 3.0)) # default imagenet ratio range primary_tfl = [T.RandomResizedCrop(size, scale=scale, ratio=ratio, interpolation=interpolation)] if hflip > 0.0: - primary_tfl += [T.RandomHorizontalFlip(p=hflip)] + primary_tfl.append(T.RandomHorizontalFlip(p=hflip)) if vflip > 0.0: - primary_tfl += [T.RandomVerticalFlip(p=vflip)] + primary_tfl.append(T.RandomVerticalFlip(p=vflip)) secondary_tfl = [] disable_color_jitter = False @@ -1298,19 +1295,19 @@ def classify_augmentations( if auto_augment == "randaugment": if TORCHVISION_0_11: - secondary_tfl += [T.RandAugment(interpolation=interpolation)] + secondary_tfl.append(T.RandAugment(interpolation=interpolation)) else: LOGGER.warning('"auto_augment=randaugment" requires torchvision >= 0.11.0. Disabling it.') elif auto_augment == "augmix": if TORCHVISION_0_13: - secondary_tfl += [T.AugMix(interpolation=interpolation)] + secondary_tfl.append(T.AugMix(interpolation=interpolation)) else: LOGGER.warning('"auto_augment=augmix" requires torchvision >= 0.13.0. Disabling it.') elif auto_augment == "autoaugment": if TORCHVISION_0_10: - secondary_tfl += [T.AutoAugment(interpolation=interpolation)] + secondary_tfl.append(T.AutoAugment(interpolation=interpolation)) else: LOGGER.warning('"auto_augment=autoaugment" requires torchvision >= 0.10.0. Disabling it.') @@ -1321,7 +1318,7 @@ def classify_augmentations( ) if not disable_color_jitter: - secondary_tfl += [T.ColorJitter(brightness=hsv_v, contrast=hsv_v, saturation=hsv_s, hue=hsv_h)] + secondary_tfl.append(T.ColorJitter(brightness=hsv_v, contrast=hsv_v, saturation=hsv_s, hue=hsv_h)) final_tfl = [ T.ToTensor(),