additional_targets参数允许在同一个Compose中处理多张图像或图像及其对应的掩码: transform = A.Compose([ A.HorizontalFlip(p=0.5), A.Rotate(limit=40, p=0.7), ], additional_targets={'mask':'mask'})# 示例掩码mask = cv2.imread('path_to_mask.png', cv2.IMREAD_GRAYSCALE)# 应用增强augmented = ...
A.Perspective(p=0.8, scale=(0.05,0.3)), ], p=0.9, additional_targets={'image0':'image'})#训练时进行数据增广ifself.train: transformed = self.transform(image=data['ir'], image0=datax['speckle'], mask=data['gt']) data['ir'] = transformed['image'] data['speckle'] = transformed[...
additional_targets:key新target 名字,value 为旧 target 名字的 dict,如 {'image2': 'image'},dict 类型 p:使用这些变换的概率,默认值为 1.0 如下使用: image3=Compose([# 对比度受限直方图均衡#(Contrast Limited Adaptive Histogram Equalization)CLAHE(),# 随机旋转 90°RandomRotate90(),# 转置Transpose()...
),additional_targets={"keypoints2":"keypoints"}, ) Now you can also add them usingadd_targets: transform=A.Compose(transforms=[A.Rotate(limit=(90.0,90.0),p=1.0)],keypoint_params=A.KeypointParams(angle_in_degrees=True,check_each_transform=True,format="xyas",label_fields=None,remove_invi...
augmentation(image=image, additional_target_1=image, additional_target_2=image) # will raise exception if not# empty `transforms` augmentation = Compose([], p=1, augmentation = Compose([], p=1, additional_targets={"additional_target_1": "image", "additional_target_2": "image"}) ...
Pixel-level transforms will change just an input image and will leave any additional targets such as masks, bounding boxes, and keypoints unchanged. The list of pixel-level transforms: AdvancedBlur Blur CLAHE ChannelDropout ChannelShuffle ColorJitter ...
在 Torchvision 中有很多经典数据集可以下载使用，在官方文档中可以看到具体有哪些数据集可以使用：...
git config --global user.name userName git config --global user.email userEmail 分支20 标签15 Mikhail DruzhininAddRandomCropFromBordersand support fo...46e280f3年前 740 次提交 提交 .github boosted versions for checks (#1245) 3年前 albumentations ...
Custom taskssuch as autoencoders, more then three channel images - refer toComposeclassdocumentationto useadditional_targets. You can use thisGoogle Colaboratory notebookto adjust image augmentation parameters and see the resulting images. Authors ...
Targets, ) from . import functional as F from . import functional as fcrops __all__ = [ "RandomCrop", Expand Down Expand Up @@ -82,16 +82,16 @@ def __init__(self, height: int, width: int, always_apply: bool = False, p: float self.width = width def apply(self, img:...