# MVTecAD

**Repository Path**: liujiyuan13/MVTecAD

## Basic Information

- **Project Name**: MVTecAD
- **Description**: A Pytorch loader for MVTecAD dataset.
- **Primary Language**: Unknown
- **License**: GPL-3.0
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2021-12-25
- **Last Updated**: 2021-12-27

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# MVTecAD

A Pytorch loader for MVTecAD dataset.

It strictly follows the code style of common Pytorch datasets, such as `torchvision.datasets.CIFAR10`.
Therefore, there is no need to worry about the consistence of your code !!! 

## Showcase
```
from torch.utils.data import DataLoader
from torchvision import transforms
from mvtec_ad import MVTecAD


def _convert_label(x):
    '''
    convert anomaly label. 0: normal; 1: anomaly.
    :param x (int): class label
    :return: 0 or 1
    '''
    return 0 if x == 0 else 1

if __name__ == '__main__':

    # define transforms
    transform = transforms.Compose([transforms.Resize((300, 300)), transforms.ToTensor()])
    target_transform = transforms.Lambda(_convert_label)

    # load data
    mvtec = MVTecAD('data',
                    subset_name='bottle',
                    train=True,
                    transform=transform,
                    mask_transform=transform,
                    target_transform=target_transform,
                    download=True)

    # feed to data loader
    data_loader = DataLoader(mvtec,
                             batch_size=2,
                             shuffle=True,
                             num_workers=8,
                             pin_memory=True,
                             drop_last=True)

    # obtain in batch
    for idx, (image, mask, target) in enumerate(data_loader):
        print(idx, target)
```

## Licence

This repository is under [GPL V3](https://github.com/liujiyuan13/MAE-code/blob/main/LICENSE).

## About

Homepage: <https://liujiyuan13.github.io>

Email: <liujiyuan13@163.com>