深度学习从入门到精通——利用torchvision transforms自定义函数

自定义函数import randomfrom torchvision.transforms import functional as F### 随机组合```pythonclass Compose(object):"""组合多个transform函数"""def __init__(self, transforms):self.transforms = transformsdef __call__(

小陈phd

413人浏览 · 2021-11-17 17:29:49

小陈phd · 2021-11-17 17:29:49 发布

自定义函数

import random
from torchvision.transforms import functional as F


### 随机组合
```python
class Compose(object):
    """组合多个transform函数"""

    def __init__(self, transforms):
        self.transforms = transforms

    def __call__(self, image, target):
        for t in self.transforms:
            image, target = t(image, target)
        return image, target

class ToTensor(object):
    """将PIL图像转为Tensor"""

    def __call__(self, image, target):
        image = F.to_tensor(image)
        return image, target

随机

class RandomHorizontalFlip(object):
    """随机水平翻转图像以及bboxes"""

    def __init__(self, prob=0.5):
        self.prob = prob

    def __call__(self, image, target):
        if random.random() < self.prob:
            height, width = image.shape[-2:]
            image = image.flip(-1)  # 水平翻转图片
            bbox = target["boxes"]
            # bbox: xmin, ymin, xmax, ymax
            bbox[:, [0, 2]] = width - bbox[:, [2, 0]]  # 翻转对应bbox坐标信息
            target["boxes"] = bbox
        return image, target