Python PyTorch CocoCaptions用法及代码示例

本文简要介绍python语言中 torchvision.datasets.CocoCaptions 的用法。

用法:

class torchvision.datasets.CocoCaptions(root: str, annFile: str, transform: Optional[Callable] = None, target_transform: Optional[Callable] = None, transforms: Optional[Callable] = None)

参数：

• root(string) -图像下载到的根目录。

• annFile(string) -json 注释文件的路径。

• transform(可调用的,可选的) -接受 PIL 图像并返回转换版本的函数/转换。例如，transforms.ToTensor

• target_transform(可调用的,可选的) -接收目标并对其进行转换的函数/转换。

• transforms(可调用的,可选的) -将输入样本及其目标作为条目并返回转换版本的函数/转换。

MS Coco Captions 数据集。

示例

import torchvision.datasets as dset
import torchvision.transforms as transforms
cap = dset.CocoCaptions(root = 'dir where images are',
                        annFile = 'json annotation file',
                        transform=transforms.ToTensor())

print('Number of samples: ', len(cap))
img, target = cap[3] # load 4th sample

print("Image Size: ", img.size())
print(target)

输出：

Number of samples: 82783
Image Size: (3L, 427L, 640L)
[u'A plane emitting smoke stream flying over a mountain.',
u'A plane darts across a bright blue sky behind a mountain covered in snow',
u'A plane leaves a contrail above the snowy mountain top.',
u'A mountain that has a plane flying overheard in the distance.',
u'A mountain view with a plume of smoke in the background']